Abstract: Heating systems are a necessity for regions which
brace extreme cold weather throughout the year. To maintain a comfortable temperature inside a given place, heating systems
making use of- Hydronic boilers- are used. The principle of a single
pipe system serves as a base for their working. It is mandatory for these heating systems to control the room temperature, thus
maintaining a warm environment. In this paper, the concept of regulation of the room temperature over a wide range is established
by using an Adaptive Fuzzy Controller (AFC). This fuzzy controller automatically detects the changes in the outside temperatures and
correspondingly maintains the inside temperature to a palatial value. Two separate AFC's are put to use to carry out this function: one to
determine the quantity of heat needed to reach the prospective temperature required and to set the desired temperature; the other to control the position of the valve, which is directly proportional to the
error between the present room temperature and the user desired temperature. The fuzzy logic controls the position of the valve as per
the requirement of the heat. The amount by which the valve opens or closes is controlled by 5 knob positions, which vary from minimum to maximum, thereby regulating the amount of heat flowing through the valve. For the given test system data, different de-fuzzifier
methods have been implemented and the results are compared. In order to validate the effectiveness of the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time
system. The simulations are performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time applications.
Abstract: Protein residue contact map is a compact
representation of secondary structure of protein. Due to the
information hold in the contact map, attentions from researchers in
related field were drawn and plenty of works have been done
throughout the past decade. Artificial intelligence approaches have
been widely adapted in related works such as neural networks,
genetic programming, and Hidden Markov model as well as support
vector machine. However, the performance of the prediction was not
generalized which probably depends on the data used to train and
generate the prediction model. This situation shown the importance
of the features or information used in affecting the prediction
performance. In this research, support vector machine was used to
predict protein residue contact map on different combination of
features in order to show and analyze the effectiveness of the
features.
Abstract: This paper features the proposed modeling and design
of a Robust Decentralized Periodic Output Feedback (RDPOF)
control technique for the active vibration control of smart flexible
multimodel Euler-Bernoulli cantilever beams for a multivariable
(MIMO) case by retaining the first 6 vibratory modes. The beam
structure is modeled in state space form using the concept of
piezoelectric theory, the Euler-Bernoulli beam theory and the Finite
Element Method (FEM) technique by dividing the beam into 4 finite
elements and placing the piezoelectric sensor / actuator at two finite
element locations (positions 2 and 4) as collocated pairs, i.e., as
surface mounted sensor / actuator, thus giving rise to a multivariable
model of the smart structure plant with two inputs and two outputs.
Five such multivariable models are obtained by varying the
dimensions (aspect ratios) of the aluminum beam, thus giving rise to
a multimodel of the smart structure system. Using model order
reduction technique, the reduced order model of the higher order
system is obtained based on dominant eigen value retention and the
method of Davison. RDPOF controllers are designed for the above 5
multivariable-multimodel plant. The closed loop responses with the
RDPOF feedback gain and the magnitudes of the control input are
observed and the performance of the proposed multimodel smart
structure system with the controller is evaluated for vibration control.
Abstract: Dilated cardiomyopathy (DCM) is a severe
cardiovascular disorder characterized by progressive systolic
dysfunction due to cardiac chamber dilatation and inefficient
myocardial contractility often leading to chronic heart failure.
Recently, a genome-wide association studies (GWASs) on DCM
indicate that the ZBTB17 gene rs10927875 single nucleotide
polymorphism is associated with DCM. The aim of the study was to
identify the distribution of ZBTB17 gene rs10927875 polymorphism
in 50 Slovak patients with DCM and 80 healthy control subjects
using the Custom Taqman®SNP Genotyping assays. Risk factors
detected at baseline in each group included age, sex, body mass
index, smoking status, diabetes and blood pressure. The mean age of
patients with DCM was 52.9±6.3 years; the mean age of individuals
in control group was 50.3±8.9 years. The distribution of investigated
genotypes of rs10927875 polymorphism within ZBTB17 gene in the
cohort of Slovak patients with DCM was as follows: CC (38.8%), CT
(55.1%), TT (6.1%), in controls: CC (43.8%), CT (51.2%), TT
(5.0%). The risk allele T was more common among the patients with
dilated cardiomyopathy than in normal controls (33.7% versus
30.6%). The differences in genotype or allele frequencies of ZBTB17
gene rs10927875 polymorphism were not statistically significant
(p=0.6908; p=0.6098). The results of this study suggest that ZBTB17
gene rs10927875 polymorphism may be a risk factor for
susceptibility to DCM in Slovak patients with DCM. Studies of
numerous files and additional functional investigations are needed to
fully understand the roles of genetic associations.
Abstract: The RK1GL2X3 method is a numerical method for solving initial value problems in ordinary differential equations, and is based on the RK1GL2 method which, in turn, is a particular case of the general RKrGLm method. The RK1GL2X3 method is a fourth-order method, even though its underlying Runge-Kutta method RK1 is the first-order Euler method, and hence, RK1GL2X3 is considerably more efficient than RK1. This enhancement is achieved through an implementation involving triple-nested two-point Gauss- Legendre quadrature.
Abstract: At present time, competition, unpredictable fluctuations have made communication engineering education in the global sphere really difficult. Confront with new situation in the engineering education sector. Communication engineering education has to be reformed and ready to use more advanced technologies. We realized that one of the general problems of student`s education is that after graduating from their universities, they are not prepared to face the real life challenges and full skilled to work in industry. They are prepared only to think like engineers and professionals but they also need to possess some others non-technical skills. In today-s environment, technical competence alone is not sufficient for career success. Employers want employees (graduate engineers) who have good oral and written communication (soft) skills. It does require for team work, business awareness, organization, management skills, responsibility, initiative, problem solving and IT competency. This proposed curriculum brings interactive, creative, interesting, effective learning methods, which includes online education, virtual labs, practical work, problem-based learning (PBL), and lectures given by industry experts. Giving short assignments, presentations, reports, research papers and projects students can significantly improve their non-technical skills. Also, we noticed the importance of using ICT technologies in engineering education which used by students and teachers, and included that into proposed teaching and learning methods. We added collaborative learning between students through team work which builds theirs skills besides course materials. The prospective on this research that we intent to update communication engineering curriculum in order to get fully constructed engineer students to ready for real industry work.
Abstract: Recently, Northeast Asia has become one of the three
largest trade areas, covering approximately 30% of the total trade
volume of the world. However, the distribution facilities are saturated
due to the increase in the transportation volume within the area and
with the European countries. In order to accommodate the increase of
the transportation volume, the transportation networking with the
major countries in Northeast Asia and Europe is absolutely necessary.
The Eurasian Logistics Network will develop into an international
passenger transportation network covering the Northeast Asian region
and an international freight transportation network connecting across
Eurasia Continent. This paper surveys the changes and trend of the
distribution network in the Eurasian Region according to the political,
economic and environmental changes of the region, analyses the
distribution network according to the changes in the transportation
policies of the related countries, and provides the direction of the
development of composite transportation on the basis of the present
conditions of transportation means. The transportation means optimal
for the efficiency of transportation system are suggested to be train
ferries, sea & rail or sea & rail & sea. It is suggested to develop
diversified composite transportation means and routes within the
boundary of international cooperation system.
Abstract: To increase precision and reliability of automatic control systems, we have to take into account of random factors affecting the control system. Thus, operational matrix technique is used for statistical analysis of first order plus time delay system with uniform random parameter. Examples with deterministic and stochastic disturbance are considered to demonstrate the validity of the method. Comparison with Monte Carlo method is made to show the computational effectiveness of the method.
Abstract: Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.
Abstract: In this paper three different approaches for person
verification and identification, i.e. by means of fingerprints, face and
voice recognition, are studied. Face recognition uses parts-based
representation methods and a manifold learning approach. The
assessment criterion is recognition accuracy. The techniques under
investigation are: a) Local Non-negative Matrix Factorization
(LNMF); b) Independent Components Analysis (ICA); c) NMF with
sparse constraints (NMFsc); d) Locality Preserving Projections
(Laplacianfaces). Fingerprint detection was approached by classical
minutiae (small graphical patterns) matching through image
segmentation by using a structural approach and a neural network as
decision block. As to voice / speaker recognition, melodic cepstral
and delta delta mel cepstral analysis were used as main methods, in
order to construct a supervised speaker-dependent voice recognition
system. The final decision (e.g. “accept-reject" for a verification
task) is taken by using a majority voting technique applied to the
three biometrics. The preliminary results, obtained for medium
databases of fingerprints, faces and voice recordings, indicate the
feasibility of our study and an overall recognition precision (about
92%) permitting the utilization of our system for a future complex
biometric card.
Abstract: This paper proposes the novel model order
formulation scheme to design a discrete PID controller for higher
order linear time invariant discrete systems. Modified PSO (MPSO)
based model order formulation technique has used to obtain the
successful formulated second order system. PID controller is tuned to
meet the desired performance specification by using pole-zero
cancellation and proposed design procedures. Proposed PID
controller is attached with both higher order system and formulated
second order system. System specifications are tabulated and closed
loop response is observed for stabilization process. The proposed
method is illustrated through numerical examples from literature.
Abstract: In this paper, a self starting two step continuous block
hybrid formulae (CBHF) with four Off-step points is developed using
collocation and interpolation procedures. The CBHF is then used to
produce multiple numerical integrators which are of uniform order
and are assembled into a single block matrix equation. These
equations are simultaneously applied to provide the approximate
solution for the stiff ordinary differential equations. The order of
accuracy and stability of the block method is discussed and its
accuracy is established numerically.
Abstract: This paper investigates the relationship between state and business in the context of structural and institutional transformations in Indonesia following the collapse of the New Order regime in 1998. Since 1998, Indonesia has embarked on a shift from an authoritarian to democratic polity and from a centralised to a decentralised system of governance, transforming the country into the third largest democracy and one of the most decentralised states in the world. This paper examines whether the transformation of the Indonesian state has altered the pattern of state and business relations with focus on clientism and corruption as the key dependent variable, and probes how/to what extent this has changed as a result of the transformation and the ensuring shifts in business and state relations. Based on interviews with key government and business actors as well as prominent scholars in Indonesia, it is found that since the demise of the New Order, business associations in Indonesia have become more independent of state control and more influential in public decision-making whereas the government has become more responsive of business concerns and more committed to combat corruption and clientism. However, these changes have not necessarily rendered business people completely leave individualclientelistic relationship with the government, and simply pursue wider sectoral and business-wide collectivism as an alternative way of channelling their aspirations, which is expected to help reduce corruption and clientism in Indonesia. This paper concludes that democratisation and a more open politics may have helped reduce corruption and clientism in Indonesia through changes in government. However, it is still difficult to imply that such political transformation has fostered business collective action and a broader, more encompassing pattern of business lobbying and activism, which is expected to help reduce corruption and clientism.
Abstract: The overlay approach has been widely used by many service providers for Traffic Engineering (TE) in large Internet backbones. In the overlay approach, logical connections are set up between edge nodes to form a full mesh virtual network on top of the physical topology. IP routing is then run over the virtual network. Traffic engineering objectives are achieved through carefully routing logical connections over the physical links. Although the overlay approach has been implemented in many operational networks, it has a number of well-known scaling issues. This paper proposes a new approach to achieve traffic engineering without full-mesh overlaying with the help of integrated approach and equal subset split method. Traffic engineering needs to determine the optimal routing of traffic over the existing network infrastructure by efficiently allocating resource in order to optimize traffic performance on an IP network. Even though constraint-based routing [1] of Multi-Protocol Label Switching (MPLS) is developed to address this need, since it is not widely tested or debugged, Internet Service Providers (ISPs) resort to TE methods under Open Shortest Path First (OSPF), which is the most commonly used intra-domain routing protocol. Determining OSPF link weights for optimal network performance is an NP-hard problem. As it is not possible to solve this problem, we present a subset split method to improve the efficiency and performance by minimizing the maximum link utilization in the network via a small number of link weight modifications. The results of this method are compared against results of MPLS architecture [9] and other heuristic methods.
Abstract: The nonlinear chaotic non-autonomous fourth order
system is algebraically simple but can generate complex chaotic
attractors. In this paper, non-autonomous fourth order chaotic
oscillator circuits were designed and simulated. Also chaotic nonautonomous
Attractor is addressed suitable for chaotic masking
communication circuits using Matlab® and MultiSIM® programs.
We have demonstrated in simulations that chaos can be synchronized
and applied to signal masking communications. We suggest that this
phenomenon of chaos synchronism may serve as the basis for little
known chaotic non-autonomous Attractor to achieve signal masking
communication applications. Simulation results are used to visualize
and illustrate the effectiveness of non-autonomous chaotic system in
signal masking. All simulations results performed on nonautonomous
chaotic system are verify the applicable of secure
communication.
Abstract: Let G be a graph of order n. The second stage adjacency matrix of G is the symmetric n × n matrix for which the ijth entry is 1 if the vertices vi and vj are of distance two; otherwise 0. The sum of the absolute values of this second stage adjacency matrix is called the second stage energy of G. In this paper we investigate a few properties and determine some upper bounds for the largest eigenvalue.
Abstract: The selection of appropriate requirements for product
releases can make a big difference in a product success. The selection
of requirements is done by different requirements prioritization
techniques. These techniques are based on pre-defined and
systematic steps to calculate the requirements relative weight.
Prioritization is complicated by new development settings, shifting
from traditional co-located development to geographically distributed
development. Stakeholders, connected to a project, are distributed all
over the world. These geographically distributions of stakeholders
make it hard to prioritize requirements as each stakeholder have their
own perception and expectations of the requirements in a software
project. This paper discusses limitations of the Analytical Hierarchy
Process with respect to geographically distributed stakeholders-
(GDS) prioritization of requirements. This paper also provides a
solution, in the form of a modified AHP, in order to prioritize
requirements for GDS. We will conduct two experiments in this
paper and will analyze the results in order to discuss AHP limitations
with respect to GDS. The modified AHP variant is also validated in
this paper.
Abstract: A kind of singularly perturbed boundary value problems is under consideration. In order to obtain its approximation, simple upwind difference discretization is applied. We use a moving mesh iterative algorithm based on equi-distributing of the arc-length function of the current computed piecewise linear solution. First, a maximum norm a posteriori error estimate on an arbitrary mesh is derived using a different method from the one carried out by Chen [Advances in Computational Mathematics, 24(1-4) (2006), 197-212.]. Then, basing on the properties of discrete Green-s function and the presented posteriori error estimate, we theoretically prove that the discrete solutions computed by the algorithm are first-order uniformly convergent with respect to the perturbation parameter ε.
Abstract: Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.