Abstract: Power line channel is proposed as an alternative for broadband data transmission especially in developing countries like Tanzania [1]. However the channel is affected by stochastic attenuation and deep notches which can lead to the limitation of channel capacity and achievable data rate. Various studies have characterized the channel without giving exactly the maximum performance and limitation in data transfer rate may be this is due to complexity of channel modeling being used. In this paper the channel performance of medium voltage, low voltage and indoor power line channel is presented. In the investigations orthogonal frequency division multiplexing (OFDM) with phase shift keying (PSK) as carrier modulation schemes is considered, for indoor, medium and low voltage channels with typical ten branches and also Golay coding is applied for medium voltage channel. From channels, frequency response deep notches are observed in various frequencies which can lead to reduce the achievable data rate. However, is observed that data rate up to 240Mbps is realized for a signal to noise ratio of about 50dB for indoor and low voltage channels, however for medium voltage a typical link with ten branches is affected by strong multipath and coding is required for feasible broadband data transfer.
Abstract: A robust still image face localization algorithm
capable of operating in an unconstrained visual environment is
proposed. First, construction of a robust skin classifier within a
shifted HSV color space is described. Then various filtering
operations are performed to better isolate face candidates and
mitigate the effect of substantial non-skin regions. Finally, a novel
Bhattacharyya-based face detection algorithm is used to compare
candidate regions of interest with a unique illumination-dependent
face model probability distribution function approximation.
Experimental results show a 90% face detection success rate despite
the demands of the visually noisy environment.
Abstract: This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with
stock dependent demand rate and nonlinear holding costs by taking deterioration rate θ0 as a triangular fuzzy number (θ0 −δ 1, θ0, θ0 +δ 2), where 1 2 0 0
Abstract: Accurate software cost estimates are critical to both
developers and customers. They can be used for generating request
for proposals, contract negotiations, scheduling, monitoring and
control. The exact relationship between the attributes of the effort
estimation is difficult to establish. A neural network is good at
discovering relationships and pattern in the data. So, in this paper a
comparative analysis among existing Halstead Model, Walston-Felix
Model, Bailey-Basili Model, Doty Model and Neural Network
Based Model is performed. Neural Network has outperformed the
other considered models. Hence, we proposed Neural Network
system as a soft computing approach to model the effort estimation
of the software systems.
Abstract: In this paper, a single period inventory model with resalable returns has been analyzed in an imprecise and uncertain mixed environment. Demand has been introduced as a fuzzy random variable. In this model, a single order is placed before the start of the selling season. The customer, for a full refund, may return purchased products within a certain time interval. Returned products are resalable, provided they arrive back before the end of the selling season and are found to be undamaged. Products remaining at the end of the season are salvaged. All demands not met directly are lost. The probabilities that a sold product is returned and that a returned product is resalable, both imprecise in a real situation, have been assumed to be fuzzy in nature.
Abstract: Particle swarm optimization (PSO) technique is applied to design the water distribution pipeline network. A simulation-optimization model is formulated with the objective of minimizing cost and is applied to a benchmark water distribution system optimization problem. The benchmark problem taken for the application of PSO technique to optimize the pipe size of the water distribution network is New York City water supply system problem. The results from the analysis infer that PSO is a potential alternative optimization technique when compared to other heuristic techniques for optimal sizing of water distribution systems.
Abstract: When dealing with safety in structures, the connections between structural components play an important role. Robustness of a structure as a whole depends both on the load- bearing capacity of the structural component and on the structures capacity to resist total failure, even though a local failure occurs in a component or a connection between components. To avoid progressive collapse it is necessary to be able to carry out a design for connections. A connection may be executed with anchors to withstand local failure of the connection in structures built with prefabricated components. For the design of these anchors, a model is developed for connections in structures performed in prefabricated autoclaved aerated concrete components. The design model takes into account the effect of anchors placed close to the edge, which may result in splitting failure. Further the model is developed to consider the effect of reinforcement diameter and anchor depth. The model is analytical and theoretically derived assuming a static equilibrium stress distribution along the anchor. The theory is compared to laboratory test, including the relevant parameters and the model is refined and theoretically argued analyzing the observed test results. The method presented can be used to improve safety in structures or even optimize the design of the connections
Abstract: Diesel Engines emit complex mixtures of inorganic
and organic compounds in the form of both solid and vapour phase
particles. Most of the particulates released are ultrafine nanoparticles
which are detrimental to human health and can easily enter the body
by respiration. The emissions standards on particulate matter release
from diesel engines are constantly upgraded within the European
Union and with future regulations based on the particles numbers
released instead of merely mass, the need for effective aftertreatment
devices will increase. Standard particulate filters in the form of wall
flow filters can have problems with high soot accumulation,
producing a large exhaust backpressure. A potential solution would
be to combine the standard filter with a flow through filter to reduce
the load on the wall flow filter. In this paper soot particle trapping has
been simulated in different continuous flow filters of monolithic
structure including the use of promoters, at laminar flow conditions.
An Euler Lagrange model, the discrete phase model in Ansys used
with user defined functions for forces acting on particles. A method
to quickly screen trapping of 5 nm and 10 nm particles in different
catalysts designs with tracers was also developed.
Simulations of square duct monoliths with promoters show that the
strength of the vortices produced are not enough to give a high
amount of particle deposition on the catalyst walls. The smallest
particles in the simulations, 5 and 10 nm particles were trapped to a
higher extent, than larger particles up to 1000 nm, in all studied
geometries with the predominant deposition mechanism being
Brownian diffusion. The comparison of the different filters designed
with a wall flow filter does show that the options for altering a design
of a flow through filter, without imposing a too large pressure drop
penalty are good.
Abstract: A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.
Abstract: The management of the health-care wastes is one of
the most important problems in Istanbul, a city with more than 12
million inhabitants, as it is in most of the developing countries.
Negligence in appropriate treatment and final disposal of the healthcare
wastes can lead to adverse impacts to public health and to the
environment. This paper employs a fuzzy multi-criteria group
decision making approach, which is based on the principles of fusion
of fuzzy information, 2-tuple linguistic representation model, and
technique for order preference by similarity to ideal solution
(TOPSIS), to evaluate health-care waste (HCW) treatment
alternatives for Istanbul. The evaluation criteria are determined
employing nominal group technique (NGT), which is a method of
systematically developing a consensus of group opinion. The
employed method is apt to manage information assessed using multigranularity
linguistic information in a decision making problem with
multiple information sources. The decision making framework
employs ordered weighted averaging (OWA) operator that
encompasses several operators as the aggregation operator since it
can implement different aggregation rules by changing the order
weights. The aggregation process is based on the unification of
information by means of fuzzy sets on a basic linguistic term set
(BLTS). Then, the unified information is transformed into linguistic
2-tuples in a way to rectify the problem of loss information of other
fuzzy linguistic approaches.
Abstract: Wireless Sensor and Actor Networks (WSANs) constitute an emerging and pervasive technology that is attracting increasing interest in the research community for a wide range of applications. WSANs have two important requirements: coordination interactions and real-time communication to perform correct and timely actions. This paper introduces a methodology to facilitate the task of the application programmer focusing on the coordination and real-time requirements of WSANs. The methodology proposed in this model uses a real-time component model, UM-RTCOM, which will help us to achieve the design and implementation of applications in WSAN by using the component oriented paradigm. This will help us to develop software components which offer some very interesting features, such as reusability and adaptability which are very suitable for WSANs as they are very dynamic environments with rapidly changing conditions. In addition, a high-level coordination model based on tuple channels (TC-WSAN) is integrated into the methodology by providing a component-based specification of this model in UM-RTCOM; this will allow us to satisfy both sensor-actor and actor-actor coordination requirements in WSANs. Finally, we present in this paper the design and implementation of an application which will help us to show how the methodology can be easily used in order to achieve the development of WSANs applications.
Abstract: This paper investigates the impact of the hand-hold
positions on both antenna performance and the specific absorption
rate (SAR) induced in the user-s head. A cellular handset with
external antenna operating at GSM-900 frequency is modeled and
simulated using a finite difference time-domain (FDTD)-based
platform SEMCAD-X. A specific anthropomorphic mannequin
(SAM) is adopted to simulate the user-s head, whereas a semirealistic
CAD-model of three-tissues is designed to simulate the
user-s hand. The results show that in case of the handset in hand close
to head at different positions; the antenna total efficiency gets
reduced to (14.5% - 5.9%) at cheek-position and to (27.5% to 11.8%)
at tilt-position. The peak averaged SAR1g values in head close to
handset without hand, are 4.67 W/Kg and 2.66 W/Kg at cheek and
tilt-position, respectively. Due to the presence of hand, the SAR1g in
head gets reduced to (3.67-3.31 W/Kg) at cheek-position and to
(1.84-1.64 W/Kg) at tilt-position, depending on the hand-hold
position.
Abstract: In this study, the performance of a high-frequency arc
welding machine including a two-switch inverter is analyzed. The
control of the system is achieved using two different control
techniques i- fuzzy logic control (FLC) ii- state space averaging
based sliding control. Fuzzy logic control does not need accurate
mathematical model of a plant and can be used in nonlinear
applications. The second method needs the mathematical model of
the system. In this method the state space equations of the system are
derived for two different “on" and “off" states of the switches. The
derived state equations are combined with the sliding control rule
considering the duty-cycle of the converter. The performance of the
system is analyzed by simulating the system using SIMULINK tool
box of MATLAB. The simulation results show that fuzzy logic
controller is more robust and less sensitive to parameter variations.
Abstract: Recent fifteen years witnessed fast improvements in the field of humanoid robotics. The human-like robot structure is
more suitable to human environment with its supreme obstacle avoidance properties when compared with wheeled service robots.
However, the walking control for bipedal robots is a challenging task
due to their complex dynamics. Stable reference generation plays a very important role in control.
Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) criterion are applied in a number of studies for stable
walking reference generation of biped walking robots. This paper follows this main approach too. We propose a natural and continuous ZMP reference trajectory for a stable and human-like walk. The ZMP reference trajectories move forward under the sole of the support foot when the robot body is supported by a single leg. Robot center of mass trajectory is obtained
from predefined ZMP reference trajectories by a Fourier series
approximation method. The Gibbs phenomenon problem common with Fourier approximations of discontinuous functions is avoided by employing continuous ZMP references. Also, these ZMP reference
trajectories possess pre-assigned single and double support phases,
which are very useful in experimental tuning work.
The ZMP based reference generation strategy is tested via threedimensional
full-dynamics simulations of a 12-degrees-of-freedom
biped robot model. Simulation results indicate that the proposed reference trajectory generation technique is successful.
Abstract: The purpose of this paper is to present the design and
instrumentation of a new benchmark multivariable nonlinear control
laboratory. The mathematical model of this system may be used to
test the applicability and performance of various nonlinear control
procedures. The system is a two degree-of-freedom robotic arm with
soft and hard (discontinuous) nonlinear terms. Two novel
mechanisms are designed to allow the implementation of adjustable
Coulomb friction and backlash.
Abstract: Using ab initio theoretical calculations, we present
analysis of fragmentation process. The analysis is performed in two
steps. The first step is calculation of fragmentation energies by ab
initio calculations. The second step is application of the energies to
kinetic description of process. The energies of fragments are
presented in this paper. The kinetics of fragmentation process can be
described by numerical models. The method for kinetic analysis is
described in this paper. The result - composition of fragmentation
products - will be calculated in future. The results from model can be
compared to the concentrations of fragments from mass spectrum.
Abstract: In today-s competitive market, most companies
develop manufacturing systems that can help in cost reduction and
maximum quality. Human issues are an important part of
manufacturing systems, yet most companies ignore their effects on
production performance. This paper aims to developing an integrated
workforce planning system that incorporates the human being.
Therefore, a multi-objective mixed integer nonlinear programming
model is developed to determine the amount of hiring, firing,
training, overtime for each worker type. This paper considers a
workforce planning model including human aspects such as skills,
training, workers- personalities, capacity, motivation, and learning
rates. This model helps to minimize the hiring, firing, training and
overtime costs, and maximize the workers- performance. The results
indicate that the workers- differences should be considered in
workforce scheduling to generate realistic plans with minimum costs.
This paper also investigates the effects of human learning rates on the
performance of the production systems.
Abstract: Learning using labeled and unlabelled data has
received considerable amount of attention in the machine learning
community due its potential in reducing the need for expensive
labeled data. In this work we present a new method for combining
labeled and unlabeled data based on classifier ensembles. The model
we propose assumes each classifier in the ensemble observes the
input using different set of features. Classifiers are initially trained
using some labeled samples. The trained classifiers learn further
through labeling the unknown patterns using a teaching signals that is
generated using the decision of the classifier ensemble, i.e. the
classifiers self-supervise each other. Experiments on a set of object
images are presented. Our experiments investigate different classifier
models, different fusing techniques, different training sizes and
different input features. Experimental results reveal that the proposed
self-supervised ensemble learning approach reduces classification
error over the single classifier and the traditional ensemble classifier
approachs.
Abstract: Despite the fact that Knowledge Sharing (KS) is very important, we found only little discussion about the reasons why people have the willingness to share knowledge at such platform even though there is no immediate benefit to the persons who contribute knowledge in it. The aim of this study is to develop an integrative understanding of the factors that support or inhibit individuals- knowledge sharing intentions in virtual communities and to find whether habit would generate people-s willingness to be involved. We apply Social Capital Theory (SCT), and we also add two dimensions for discussion: member incentive and habitual domain (HD). This research assembles the questionnaire from individuals who have experienced knowledge sharing in virtual communities, and applies survey and Structural Equation Model (SEM) to analyze the results from the questionnaires. Finally, results confirm that individuals are willing to share knowledge in virtual communities: (1) if they consider reciprocity, centrality, and have longer tenure in their field, and enjoy helping. (2) if they have the habit of sharing knowledge. This study is useful for the developers of virtual communities to insight into knowledge sharing in cyberspace.
Abstract: Nowadays the devices of night vision are widely used both for military and civil applications. The variety of night vision applications require a variety of the night vision devices designs. A web-based architecture of a software system for design assessment before producing of night vision devices is developed. The proposed architecture of the web-based system is based on the application of a mathematical model for designing of night vision devices. An algorithm with two components – for iterative design and for intelligent design is developed and integrated into system architecture. The iterative component suggests compatible modules combinations to choose from. The intelligent component provides compatible combinations of modules satisfying given user requirements to device parameters. The proposed web-based architecture of a system for design assessment of night vision devices is tested via a prototype of the system. The testing showed the applicability of both iterative and intelligent components of algorithm.