Abstract: In the present era of aviation technology, autonomous navigation and control have emerged as a prime area of active research. Owing to the tremendous developments in the field, autonomous controls have led today’s engineers to claim that future of aerospace vehicle is unmanned. Development of guidance and navigation algorithms for an unmanned aerial vehicle (UAV) is an extremely challenging task, which requires efforts to meet strict, and at times, conflicting goals of guidance and control. In this paper, aircraft altitude and heading controllers and an efficient algorithm for self-governing navigation using MATLAB® mapping toolbox is presented which also enables loitering of a fixed wing UAV over a specified area. For this purpose, a nonlinear mathematical model of a UAV is used. The nonlinear model is linearized around a stable trim point and decoupled for controller design. The linear controllers are tested on the nonlinear aircraft model and navigation algorithm is subsequently developed for for autonomous flight of the UAV. The results are presented for trajectory controllers and waypoint based navigation. Our investigation reveals that MATLAB® mapping toolbox can be exploited to successfully deliver an efficient algorithm for autonomous aerial navigation for a UAV.
Abstract: Echocardiography imaging is one of the most common diagnostic tests that are widely used for assessing the abnormalities of the regional heart ventricle function. The main goal of the image enhancement task in 2D-echocardiography (2DE) is to solve two major anatomical structure problems; speckle noise and low quality. Therefore, speckle noise reduction is one of the important steps that used as a pre-processing to reduce the distortion effects in 2DE image segmentation. In this paper, we present the common filters that based on some form of low-pass spatial smoothing filters such as Mean, Gaussian, and Median. The Laplacian filter was used as a high-pass sharpening filter. A comparative analysis was presented to test the effectiveness of these filters after being applied to original 2DE images of 4-chamber and 2-chamber views. Three statistical quantity measures: root mean square error (RMSE), peak signal-to-ratio (PSNR) and signal-tonoise ratio (SNR) are used to evaluate the filter performance quantitatively on the output enhanced image.
Abstract: In this paper, a mathematical model of human immunodeficiency
virus (HIV) is utilized and an optimization problem is
proposed, with the final goal of implementing an optimal 900-day
structured treatment interruption (STI) protocol. Two type of commonly
used drugs in highly active antiretroviral therapy (HAART),
reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are
considered. In order to solving the proposed optimization problem an
adaptive memetic algorithm with population management (AMAPM)
is proposed. The AMAPM uses a distance measure to control the
diversity of population in genotype space and thus preventing the
stagnation and premature convergence. Moreover, the AMAPM uses
diversity parameter in phenotype space to dynamically set the population
size and the number of crossovers during the search process.
Three crossover operators diversify the population, simultaneously.
The progresses of crossover operators are utilized to set the number
of each crossover per generation. In order to escaping the local optima
and introducing the new search directions toward the global optima,
two local searchers assist the evolutionary process. In contrast to
traditional memetic algorithms, the activation of these local searchers
is not random and depends on both the diversity parameters in
genotype space and phenotype space. The capability of AMAPM in
finding optimal solutions compared with three popular metaheurestics
is introduced.
Abstract: Twelve lactating Etawah Crossedbred goats were used
in this study. Goat feed consisted of Cally andra callothyrsus,
Pennisetum purpureum, wheat bran and dried fermented cassava
peel. The cassava peels were fermented with a traditional culture
called “ragi tape" (mixed culture of Saccharomyces cerevisae,
Aspergillus sp, Candida, Hasnula and Acetobacter). The goats were
divided into 2 groups (Control and Treated) of six does. The
experimental diet of the Control group consisted of 70% of roughage
(fresh Callyandra callothyrsus and Pennisetum purpureum 60:40)
and 30% of wheat bran on dry matter (DM) base. In the Treated
group 30% of wheat bran was replaced with dried fermented cassava
peels. Data were statistically analyzed using analysis of variance
followed SPSS program. The concentration of HCN in fermented
cassava peel decreased to non toxic level. Nutrient composition of
dried fermented cassava peel consisted of 85.75% dry matter;
5.80% crude protein and 82.51% total digestible nutrien (TDN).
Substitution of 30% of wheat bran with dried fermented cassava peel
in the diet had no effect on dry matter and organic matter intake but
significantly (P< 0.05) decreased crude protein and TDN
consumption as well as milk yields and milk composition. The study
recommended to reduced the level of substitution to less than 30% of
concentrates in the diet in order to avoid low nutrient intake and milk
production of goats.
Abstract: We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.
Abstract: The major goal in defining and examining game
scenarios is to find good strategies as solutions to the game. A
plausible solution is a recommendation to the players on how to play
the game, which is represented as strategies guided by the various
choices available to the players. These choices invariably compel the
players (decision makers) to execute an action following some
conscious tactics. In this paper, we proposed a refinement-based
heuristic as a machine learning technique for human-like decision
making in playing Ayo game. The result showed that our machine
learning technique is more adaptable and more responsive in making
decision than human intelligence. The technique has the advantage
that a search is astutely conducted in a shallow horizon game tree.
Our simulation was tested against Awale shareware and an appealing
result was obtained.
Abstract: Unified Modeling Language (UML) extensions for real time embedded systems (RTES) co-design, are taking a growing interest by a great number of industrial and research communities. The extension mechanism is provided by UML profiles for RTES. It aims at improving an easily-understood method of system design for non-experts. On the other hand, one of the key items of the co- design methods is the Hardware/Software partitioning and scheduling tasks. Indeed, it is mandatory to define where and when tasks are implemented and run. Unfortunately the main goals of co-design are not included in the usual practice of UML profiles. So, there exists a need for mapping used models to an execution platform for both schedulability test and HW/SW partitioning. In the present work, test schedulability and design space exploration are performed at an early stage. The proposed approach adopts Model Driven Engineering MDE. It starts from UML specification annotated with the recent profile for the Modeling and Analysis of Real Time Embedded systems MARTE. Following refinement strategy, transformation rules allow to find a feasible schedule that satisfies timing constraints and to define where tasks will be implemented. The overall approach is experimented for the design of a football player robot application.
Abstract: The existing information system (IS) developments
methods are not met the requirements to resolve the security related
IS problems and they fail to provide a successful integration of
security and systems engineering during all development process
stages. Hence, the security should be considered during the whole
software development process and identified with the requirements
specification. This paper aims to propose an integrated security and
IS engineering approach in all software development process stages
by using i* language. This proposed framework categorizes into three
separate parts: modelling business environment part, modelling
information technology system part and modelling IS security part.
The results show that considering security IS goals in the whole
system development process can have a positive influence on system
implementation and better meet business expectations.
Abstract: This study considers priorities of primary goals to increase policy efficiency of Green ICT. Recently several studies have been published that address how IT is linked to climate change. However, most of the previous studies are limited to Green ICT industrial statute and policy directions. This paper present Green ICT
policy making processes systematically. As a result of the analysis of
Korean Green ICT policy, the following emerged as important to accomplish for Green ICT policy: eco-friendliness, technology evolution, economic efficiency, energy efficiency, and stable supply
of energy. This is an initial study analyzing Green ICT policy, which provides an academic framework that can be used a guideline to
establish Green ICT policy.
Abstract: The most reliable and accurate description of the actual behavior of a software system is its source code. However, not all questions about the system can be answered directly by resorting to this repository of information. What the reverse engineering methodology aims at is the extraction of abstract, goal-oriented “views" of the system, able to summarize relevant properties of the computation performed by the program. While concentrating on reverse engineering we had modeled the C++ files by designing the translator.
Abstract: This paper addresses one of the most important issues
have been considered in hybrid MTS/MTO production environments. To cope with the problem, a mathematical programming model is
applied from a tactical point of view. The model is converted to a fuzzy goal programming model, because a degree of uncertainty is involved in hybrid MTS/MTO context. Finally, application of the
proposed model in an industrial center is reported and the results prove the validity of the model.
Abstract: Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.
Abstract: Understanding proteins functions is a major goal in
the post-genomic era. Proteins usually work in context of other
proteins and rarely function alone. Therefore, it is highly relevant to
study the interaction partners of a protein in order to understand its
function. Machine learning techniques have been widely applied to
predict protein-protein interactions. Kernel functions play an
important role for a successful machine learning technique. Choosing
the appropriate kernel function can lead to a better accuracy in a
binary classifier such as the support vector machines. In this paper,
we describe a Bayesian kernel for the support vector machine to
predict protein-protein interactions. The use of Bayesian kernel can
improve the classifier performance by incorporating the probability
characteristic of the available experimental protein-protein
interactions data that were compiled from different sources. In
addition, the probabilistic output from the Bayesian kernel can assist
biologists to conduct more research on the highly predicted
interactions. The results show that the accuracy of the classifier has
been improved using the Bayesian kernel compared to the standard
SVM kernels. These results imply that protein-protein interaction can
be predicted using Bayesian kernel with better accuracy compared to
the standard SVM kernels.
Abstract: The European countries that during the past two
decades based their exchange rate regimes on currency board
arrangement (CBA) are usually analysed from the perspective of
corner solution choice’s stabilisation effects. There is an open
discussion on the positive and negative background of a strict
exchange rate regime choice, although it should be seen as part of the
transition process towards the monetary union membership. The
focus of the paper is on the Baltic countries that after two decades of
a rigid exchange rate arrangement and strongly influenced by global
crisis are finishing their path towards the euro zone. Besides the
stabilising capacity, the CBA is highly vulnerable regime, with
limited developing potential. The rigidity of the exchange rate (and
monetary) system, despite the ensured credibility, do not leave
enough (or any) space for the adjustment and/or active crisis
management. Still, the Baltics are in a process of recovery, with fiscal
consolidation measures combined with (painful and politically
unpopular) measures of internal devaluation. Today, two of them
(Estonia and Latvia) are members of euro zone, fulfilling their
ultimate transition targets, but de facto exchanging one fixed regime
with another.
The paper analyses the challenges for the CBA in unstable
environment since the fixed regimes rely on imported stability and
are sensitive to external shocks. With limited monetary instruments,
these countries were oriented to the fiscal policies and used a
combination of internal devaluation and tax policy measures. Despite
their rather quick recovery, our second goal is to analyse the long
term influence that the measures had on the national economy.
Abstract: This paper describes various stages of design and prototyping of a modular robot for use in various industrial applications. The major goal of current research has been to design and make different robotic joints at low cost capable of being assembled together in any given order for achieving various robot configurations. Five different types of joins were designed and manufactured where extensive research has been carried out on the design of each joint in order to achieve optimal strength, size, modularity, and price. This paper presents various stages of research and development undertaken to engineer these joints that include material selection, manufacturing, and strength analysis. The outcome of this research addresses the birth of a new generation of modular industrial robots with a wider range of applications and greater efficiency.
Abstract: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
Abstract: The challenge for software development house in
Bangladesh is to find a path of using minimum process rather than CMMI or ISO type gigantic practice and process area. The small and medium size organization in Bangladesh wants to ensure minimum
basic Software Process Improvement (SPI) in day to day operational
activities. Perhaps, the basic practices will ensure to realize their company's improvement goals. This paper focuses on the key issues in basic software practices for small and medium size software
organizations, who are unable to effort the CMMI, ISO, ITIL etc. compliance certifications. This research also suggests a basic software process practices model for Bangladesh and it will show the mapping of our suggestions with international best practice. In this IT
competitive world for software process improvement, Small and medium size software companies that require collaboration and
strengthening to transform their current perspective into inseparable global IT scenario. This research performed some investigations and analysis on some projects- life cycle, current good practice, effective approach, reality and pain area of practitioners, etc. We did some
reasoning, root cause analysis, comparative analysis of various
approach, method, practice and justifications of CMMI and real life. We did avoid reinventing the wheel, where our focus is for minimal
practice, which will ensure a dignified satisfaction between
organizations and software customer.
Abstract: The case study was conducted to show the effect of milking method in goat called half day milking on the milk production and the growth of kids. Data were collected by interviewing farmers and investigating goat production in the communal goat housing from June 2008 to May 2009. The interview was conducted to collect data about goat management. The observations were conducted on 10 goats, which were selected based on the uniformity of age, number of kid born/goat and the milking method in practice. The samples were divided into two groups; those were full 3 months nursing and half day milked goats (in this group the kids were separated from goat during the previous night milking and then the kids were allowed to suck the goat during the day). The result showed that the communal goat housing had 138 goats and 25% of the farmers milked the goat. The implementation of half day milking increased the milk production significantly (P
Abstract: Green Lean Total Quality Management (TQM)
System is a system comprises of Environmental Management System
(EMS) practices which is integrated to TQM with Lean
Manufacturing (LM) principles. The ultimate goal of this system is to
focus on achieving total customer satisfaction and environmental care by removing eight wastes available in any process in an
organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by
SPSS v.17. It was found out that some vendors have been practicing TQM and LM while some have started to implement EMS. This
study is only focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development
Program. This is the first study conducted to know the current status of TQM, LM and EMS practices in highly active automotive companies in Malaysia. It was found out that EMS has been
practiced by 16 companies out of 30. Within these 16 companies the
approach is more holistic and green. This is a preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production
System SAEJ4000, MAJAICO Lean Production System and EMS.
Abstract: Surface water pollution is one of the serious
environmental problems in rural areas of South Africa due to
discharge of household waste into the streams, turning them into
open sewers. In this study, samples of water were collected from a
stream in Soshanguve and analysed. The result showed that pollution
in the area was caused by man and its activities. The water quality in
the area was found to have deterioted significantly after water runoff
from farms and household wastes. The result shows, fertilizer runoff
contributes 50% of the pollution while pesticides and sediments
contribute up to 10% respectively in the streams, while household
waste contributes up to 30%. This study gives an outline of the
sources of water pollution in the area and provides a process of
creating a clean and unpolluted environment for Soshanguve
community in Pretoria north in order to achieve the 7th aim of the
millennium development goals by 2015, which is ensuring
environmental sustainability.