Abstract: This paper proposes improved delay-dependent stability conditions of the linear time-delay systems of neutral type. The proposed methods employ a suitable Lyapunov-Krasovskii’s functional and a new form of the augmented system. New delay-dependent stability criteria for the systems are established in terms of Linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical examples showed that the proposed method is effective and can provide less conservative results.
Abstract: Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.
Abstract: This work presents a low-cost and eco-friendly
building material named Agrostone panel. Africa-s urban population
is growing at an annual rate of 2.8% and 62% of its population will
live in urban areas by 2050. As a consequence, many of the least
urbanized and least developed African countries- will face serious
challenges in providing affordable housing to the urban dwellers.
Since the cost of building materials accounts for the largest
proportion of the overall construction cost, innovating low-cost
building material is vital. Agrostone panel is used in housing projects
in Ethiopia. It uses raw materials of agricultural/industrial wastes
and/or natural minerals as a filler, magnesium-based chemicals as a
binder and fiberglass as reinforcement. Agrostone panel reduces the
cost of wall construction by 50% compared with the conventional
building materials. The pros and cons of Agrostone panel as well as
the use of other waste materials as a raw material to make the panel
more sustainable, low-cost and better properties are discussed.
Abstract: An optical fault monitoring in FTTH-PON using ACS
is demonstrated. This device can achieve real-time fault monitoring
for protection feeder fiber. In addition, the ACS can distinguish
optical fiber fault from the transmission services to other customers
in the FTTH-PON. It is essential to use a wavelength different from
the triple-play services operating wavelengths for failure detection.
ACS is using the operating wavelength 1625 nm for monitoring and
failure detection control. Our solution works on a standard local area
network (LAN) using a specially designed hardware interfaced with a
microcontroller integrated Ethernet.
Abstract: The breakdown strength characteristic of Low Density
Polyethylene films (LDPE) under DC voltage application and the
effect of water absorption have been studied. Mainly, our experiment
was investigated under two conditions; dry and heavy water
absorption. Under DC ramp voltage, the result found that the
breakdown strength under heavy water absorption has a lower value
than dry condition. In order to clarify the effect, the temperature rise of
film was observed using non contact thermograph until the occurrence
of the electrical breakdown and the conduction current of the sample
was also measured in correlation with the thermograph measurement.
From the observations, it was shown that under the heavy water
absorption, the hot spot in the samples appeared at lower voltage. At
the same voltage the temperature of the hot spot and conduction
current was higher than that under the dry condition. The measurement
result has a good correlation between the existence of a critical field
for conduction current and thermograph observation. In case of the
heavy water absorption, the occurrence of the threshold field was
earlier than the dry condition as result lead to higher of conduction
current and the temperature rise appears after threshold field was
significantly increased in increasing of field. The higher temperature
rise was caused by the higher current conduction as the result the
insulation leads to breakdown to the lower field application.
Abstract: Vermicomposting is the conversion of organic waste
into bio-fertilizers through the action of earthworm. This technology
is widely used for organic solid waste management. Waste corn pulp
blended with cow dung manure was vermicomposted over 30 days
using Eisenia fetida earthworms species. pH, temperature, moisture
content, and electrical conductivity were daily monitored. The
feedstock, vermicompost and vermiwash were analyzed for nutrient
composition. The average temperature and moisture content in the
vermi-reactor was 22.5°C and 42.5% respectively. The vermicompost
and vermiwash had an almost neutral pH whilst the electrical
conductivity was 21% higher in the vermicompost. The nitrogen and
potassium content was 57% and 79.6% richer in the vermicompost
respectively compared to the vermiwash. However, the vermiwash
was 84% richer in phosphorous as compared to vermicompost.
Furthermore, the vermiwash was 89.1% and 97.6% richer in Ca and
Mg respectively and was 97.8% richer in Na salts compared to the
vermicompost. The vermiwash also indicated a significantly higher
amount of micronutrients. Both bio-fertilizers were rich in nutrients
specification for fertilizers.
Abstract: A complete CAD procedure to model a twisted-bladed
vertical-axis wind turbine (VAWT) is presented with the aim of
determining some practical guidelines to be used for the generation
of an easily-meshable CAD geometry to be adopted as the basis of
both CFD and FEM numerical simulations.
Abstract: Female breast cancer is the second in frequency after cervical cancer. Surgery is the most common treatment for breast cancer, followed by chemotherapy as a treatment of choice. Although effective, it causes serious side effects. Controlled-release drug delivery is an alternative method to improve the efficacy and safety of the treatment. It can release the dosage of drug between the minimum effect concentration (MEC) and minimum toxic concentration (MTC) within tumor tissue and reduce the damage of normal tissue and the side effect. Because an in vivo experiment of this system can be time-consuming and labor-intensive, a mathematical model is desired to study the effects of important parameters before the experiments are performed. Here, we describe a 3D mathematical model to predict the release of doxorubicin from pluronic gel to treat human breast cancer. This model can, ultimately, be used to effectively design the in vivo experiments.
Abstract: We review a knowledge extractor model in
constructing 3G Killer Applications. The success of 3G is essential
for Government as it became part of Telecommunications National
Strategy. The 3G wireless technologies may reach larger area and
increase country-s ICT penetration. In order to understand future
customers needs, the operators require proper information
(knowledge) lying inside. Our work approached future customers as
complex system where the complex knowledge may expose regular
behavior. The hidden information from 3G future customers is
revealed by using fractal-based questionnaires. Afterward, further
statistical analysis is used to match the results with operator-s
strategic plan. The developments of 3G applications also consider its
saturation time and further improvement of the application.
Abstract: Uncertainties of a serial production line affect on the
production throughput. The uncertainties cannot be prevented in a
real production line. However the uncertain conditions can be
controlled by a robust prediction model. Thus, a hybrid model
including autoregressive integrated moving average (ARIMA) and
multiple polynomial regression, is proposed to model the nonlinear
relationship of production uncertainties with throughput. The
uncertainties under consideration of this study are demand, breaktime,
scrap, and lead-time. The nonlinear relationship of production
uncertainties with throughput are examined in the form of quadratic
and cubic regression models, where the adjusted R-squared for
quadratic and cubic regressions was 98.3% and 98.2%. We optimized
the multiple quadratic regression (MQR) by considering the time
series trend of the uncertainties using ARIMA model. Finally the
hybrid model of ARIMA and MQR is formulated by better adjusted
R-squared, which is 98.9%.
Abstract: Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.
Abstract: This research project is developed in order to study
managerial styles of modern Thai executives. The thorough
understanding will lead to continuous improvement and efficient
performance of Thai business organizations. Regarding managerial
skills, Thai executives focus heavily upon human skills. Also, the
negotiator roles are most emphasis in their management. In addition,
Thai executives pay most attention to the fundamental management
principles including Harmony and Unity of Direction of the
organizations. Moreover, the management techniques, consisting of
Team work and Career Planning are of their main concern. Finally,
Thai executives wish to enhance their firms- image and employees-
morale through conducting the ethical and socially responsible
activities. The major tactic deployed to stimulate employees- ethical
behaviors and mindset is Code of Ethics development.
Abstract: This paper presents a multi-objective order allocation
planning problem with the consideration of various real-world
production features. A novel hybrid intelligent optimization model,
integrating a multi-objective memetic optimization process, a Monte
Carlo simulation technique and a heuristic pruning technique, is
proposed to handle this problem. Experiments based on industrial data
are conducted to validate the proposed model. Results show that (1)
the proposed model can effectively solve the investigated problem by
providing effective production decision-making solutions, which
outperformsan NSGA-II-based optimization process and an industrial
method.
Abstract: This paper proposes the method combining artificial
neural network (ANN) with particle swarm optimization (PSO) to
implement the maximum power point tracking (MPPT) by controlling
the rotor speed of the wind generator. First, the measurements of wind
speed, rotor speed of wind power generator and output power of wind
power generator are applied to train artificial neural network and to
estimate the wind speed. Second, the method mentioned above is
applied to estimate and control the optimal rotor speed of the wind
turbine so as to output the maximum power. Finally, the result reveals
that the control system discussed in this paper extracts the maximum
output power of wind generator within the short duration even in the
conditions of wind speed and load impedance variation.
Abstract: The experiment was then conducted to investigate the
effect of cassava peel addition in the concentrate on the performance
of lactating dairy cows. Twenty four Holstein Friesian crossbred
(>87.5% Holstein Friesian) lactating dairy cows in mid lactation;
averaging 12.2+2.1 kg of milk, 119+45 days in milk, 44.1+6.2
months old and 449+33 kg live weight, were stratified for milk yield,
days in milk, age, stage of lactation and body weight, and then
randomly allocated to three treatment groups. The first, second and
third groups were fed concentrates containing the respective cassava
peel, 0, 20 and 40%. All cows were fed ad libitum corn silage and
freely access to clean water. Dry matter intake, 4%FCM, milk
composition and body weight change were affected (P
Abstract: This study was conducted to determine the
effect of abdominal exercises versus abdominal supporting
belt on abdominal efficiency and inter-recti separation
following vaginal delivery.30 primiparous post-natal women
participated in this study. Their age ranged from (25 - 35)
years and their BMI < 30 Kg/m2. Participants were assigned
randomly into 2groups, participants of group (A) used
abdominal belt from the 2nd day following delivery, till the end
of puerperium (6 weeks), while participants of group (B)
engaged into abdominal exercises program from the 2nd day
following delivery for 6 weeks. The results of the present
study revealed that although there was no statistical difference
in waist circumference between both groups, participation in
abdominal exercise program produced a pronounced reduction
in waist/hip ratio, and inter-recti separation and also caused
significant increase in abdominal muscles strength (peak
torque, maximum repetition total work and average power)
higher than the use of abdominal belt.
Abstract: This paper proposes a set of quasi-static mathematical
model of magnetic fields caused by high voltage conductors of
distribution transformer by using a set of second-order partial
differential equation. The modification for complex magnetic field
analysis and time-harmonic simulation are also utilized. In this
research, transformers were study in both balanced and unbalanced
loading conditions. Computer-based simulation utilizing the threedimensional
finite element method (3-D FEM) is exploited as a tool
for visualizing magnetic fields distribution volume a distribution
transformer. Finite Element Method (FEM) is one among popular
numerical methods that is able to handle problem complexity in
various forms. At present, the FEM has been widely applied in most
engineering fields. Even for problems of magnetic field distribution,
the FEM is able to estimate solutions of Maxwell-s equations
governing the power transmission systems. The computer simulation
based on the use of the FEM has been developed in MATLAB
programming environment.
Abstract: This study examines causal link between energy use and economic growth for five South Asian countries over period 1971-2006. Panel cointegration, ECM and FMOLS are applied for short and long run estimates. In short run unidirectional causality from per capita GDP to per capita energy consumption is found, but not vice versa. In long run one percent increase in per capita energy consumption tend to decrease 0.13 percent per capita GDP. i.e. Energy use discourage economic growth. This short and long run relationship indicate energy shortage crisis in South Asia due to increased energy use coupled with insufficient energy supply. Beside this long run estimated coefficient of error term suggest that short term adjustment to equilibrium are driven by adjustment back to long run equilibrium. Moreover, per capita energy consumption is responsive to adjustment back to equilibrium and it takes 59 years approximately. It specifies long run feedback between both variables.
Abstract: Reference point effects of top managers exerts an influence on managerial decision-making behaviors. We introduces the main idea of developing the decision behavior testing system designed for top manager in team task circumstance. According to the theory of the reference point effect, study of testing experiments in the reference point effect is carried out. Under managerial decision-making simulation environment, a platform is designed for testing reference point effect. The system uses the outcome of the value of the reference point to report the characteristics of the decision behavior of top managers.