Abstract: Presented article outlines a rationale, why it is
necessary to develop competence about infrastructure risk in water
transport. Climate changes are evident and require special attention
and global monitoring. Current risk assessment methods for Inland
waterway transport just consider some dramatic events. We present a
new method for the assessment of risk and vulnerability of inland
waterway transport where river depth represents a crucial part. The
analysis of water level changes in the lower Danube was done for two
significant periods (1965-1979 and 1998-2012).
Abstract: Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.
Abstract: The moisture content of densified biomass is a
limiting parameter influencing the quality of this solid biofuel. It
influences its calorific value, density, mechanical strength and
dimensional stability as well as affecting its production process. This
paper deals with experimental research into the effect of moisture
content of the densified material on the final quality of biofuel in the
form of logs (briquettes or pellets). Experiments based on the singleaxis
densification of the spruce sawdust were carried out with a
hydraulic piston press (piston and die), where the densified logs were
produced at room temperature. The effect of moisture content on the
qualitative properties of the logs, including density, change of
moisture, expansion and physical changes, and compressive and
impact resistance were studied. The results show the moisture ranges
required for producing good-quality logs. The experiments were
evaluated and the moisture content of the tested material was
optimized to achieve the optimum value for the best quality of the
solid biofuel. The dense logs also have high-energy content per unit
volume. The research results could be used to develop and optimize
industrial technologies and machinery for biomass densification to
achieve high quality solid biofuel.
Abstract: Group decision making with multiple attribute has
attracted intensive concern in the decision analysis area. This paper
assumes that the contributions of all the decision makers (DMs) are not
equal to the decision process based on different knowledge and
experience in group setting. The aim of this paper is to develop a novel
approach to determine weights of DMs in the group decision making
problems. In this paper, the weights of DMs are determined in the
group decision environment via angle cosine and projection method.
First of all, the average decision of all individual decisions is defined
as the ideal decision. After that, we define the weight of each decision
maker (DM) by aggregating the angle cosine and projection between
individual decision and ideal decision with associated direction
indicator μ. By using the weights of DMs, all individual decisions are
aggregated into a collective decision. Further, the preference order of
alternatives is ranked in accordance with the overall row value of
collective decision. Finally, an example in a chemical company is
provided to illustrate the developed approach.
Abstract: Space Vector Pulse Width Modulation is popular for
variable frequency drives. The method has several advantages over
carried based PWM and is computation intensive. The
implementation of SVPWM for multilevel inverter requires special
attention and at the same time consumes considerable resources. Due
to faster processing power and reduced over all computational
burden, FPGAs are being investigated as an alternative for other
controllers. In this paper, a space vector PWM algorithm is
implemented using FPGA which requires less computational area and
is modular in structure. The algorithm is verified experimentally for
Neutral Point Clamped inverter using FPGA development board
xc3s5000-4fg900.
Abstract: In this communication, a low-cost circularly
polarized wire antenna exhibiting improved gain performance for
Dedicated Short Range Communications (DSRC), vehicle-to-vehicle
(V2V) and vehicle-to-infrastructure (V2I) communications is
presented. The proposed antenna comprises a Y-shaped quarterwavelength
monopole antenna surrounded by two iterations of eight
conductive arched walls acting as parasitic elements to enhance the
overall antenna gain and to shape the radiation pattern in the H-plane.
A hemispherical radome shell is added to protect the antenna
structure and its effect on the antenna performance is discussed. The
designed antenna demonstrates antenna gain of 8.2 dB with
omnidirectional far-field radiation pattern in the H-plane. The gain of
the proposed antenna is also compared with the characteristic of the
stand-alone Y-shaped monopole to highlight the advantages of the
proposed approach.
Abstract: Different designs of attenuator systems have been
studied in this research; new analysis have been done on existed
designs considering fibers effect on air flow; it was comprehended
that, at fibers presence, there is an air flow which agglomerates fibers
as a negative effect. So some new representations have been designed
and CFD analysis has been done on them. Afterwards, one of these
representations selected as the most optimum and effective design
which is brought in this paper.
Abstract: Geographical routing protocol requires node physical
location information to make forwarding decision. Geographical
routing uses location service or position service to obtain the position
of a node. The geographical information is a geographic coordinates
or can be obtained through reference points on some fixed coordinate
system. Link can be formed between two nodes. Link lifetime plays a
crucial role in MANET. Link lifetime represent how long the link is
stable without any failure between the nodes. Link failure may occur
due to mobility and because of link failure energy of nodes can be
drained. Thus this paper proposes survey about link lifetime
prediction using geographical information.
Abstract: HR is a department that enhances the power of
employee performance in regard with their services, and to make the
organization strategic objectives. The main concern of HR
department is to organize people, focus on policies and their system.
The empirical study shows the relationship between HRM (Human
Resource Management practices) and their Job Satisfaction. The
Hypothesis is testing on a sample of overall 320 employees of 5
different Pharmaceutical departments of different organizations in
Pakistan. The important thing as Relationship of Job satisfaction with
HR Practices, Impact on Job Satisfaction with HR Practices,
Participation of Staff of Different Departments, HR Practices effects
the Job satisfaction, Recruitment or Hiring and Selection effects the
Job satisfaction, Training and Development, Performance and
Appraisals, Compensation affects the Job satisfaction , and Industrial
Relationships affects the Job satisfaction. After finishing all data
analysis, the conclusion is that lots of Job related activities raise the
confidence of Job satisfaction of employees with their salary and
other benefits.
Abstract: This paper presents modeling and simulation of
flexible robot in an underwater environment. The underwater
environment completely contrasts with ground or space environment.
The robot in an underwater situation is subjected to various dynamic
forces like buoyancy forces, hydrostatic and hydrodynamic forces.
The underwater robot is modeled as Rayleigh beam. The developed
model further allows estimating the deflection of tip in two
directions. The complete dynamics of the underwater robot is
analyzed, which is the main focus of this investigation. The control of
robot trajectory is not discussed in this paper. Simulation is
performed using Symbol Shakti software.
Abstract: This paper examines the relationship between
corporate governance rating and stock prices of 26 Turkish firms
listed in Turkish stock exchange (Borsa Istanbul) by using panel data
analysis over five-year period. The paper also investigates the stock
performance of firms with governance rating with regards to the
market portfolio (i.e. BIST 100 Index) both prior and after
governance scoring began. The empirical results show that there is no
relation between corporate governance rating and stock prices when
using panel data for annual variation in both rating score and stock
prices. Further analysis indicates surprising results that while the
selected firms outperform the market significantly prior to rating, the
same performance does not continue afterwards.
Abstract: Residential block construction of big cities in China
began in the 1950s, and four models had far-reaching influence on
modern residential block in its development process, including unit
compound and residential district in 1950s to 1980s, and gated
community and open community in 1990s to now. Based on analysis
of the four models’ fabric, the article takes residential blocks in
Hangzhou west area as an example and carries on the studies from
urban structure level and block spacial level, mainly including urban
road network, land use, community function, road organization, public
space and building fabric. At last, the article puts forward “Semi-open
Sub-community” strategy to improve the current fabric.
Abstract: In this paper, we consider a cognitive relay network
(CRN) in which the primary receiver (PR) is protected by peak
transmit power ¯PST and/or peak interference power Q constraints.
In addition, the interference effect from the primary transmitter (PT)
is considered to show its impact on the performance of the CRN. We
investigate the outage probability (OP) and outage capacity (OC) of
the CRN by deriving closed-form expressions over Rayleigh fading
channel. Results show that both the OP and OC improve by increasing
the cooperative relay nodes as well as when the PT is far away from
the SR.
Abstract: This study compares the intensity of game load among
player positions and between the 1st and the 2nd half of the games.
Two guards, three forwards, and three centers (female basketball
players) participated in this study. The heart rate (HR) and its
development were monitored during two competitive games.
Statistically insignificant differences in the intensity of game load
were recorded between guards, forwards, and centers below and
above 85% of the maximal heart rate (HRmax) and in the mean HR as
% of HRmax (87.81±3.79%, 87.02±4.37%, and 88.76±3.54%,
respectively). Moreover, when the 1st and the 2nd half of the games
were compared in the mean HR (87.89±4.18% vs. 88.14±3.63% of
HRmax), no statistical significance was recorded. This information can
be useful for coaching staff, to manage and to precisely plan the
training process.
Abstract: In this paper, we present a new segmentation approach
for liver lesions in regions of interest within MRI (Magnetic
Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans
methodology, considers the parameter variable compactness
to handle uncertainty. Fine boundaries are detected by a local
recursive merging of ambiguous pixels with a sequential forward
floating selection with Zernike moments. The method has been tested
on both synthetic and real images. When applied on synthetic images,
the proposed approach provides good performance, segmentations
obtained are accurate, their shape is consistent with the ground truth,
and the extracted information is reliable. The results obtained on MR
images confirm such observations. Our approach allows, even for
difficult cases of MR images, to extract a segmentation with good
performance in terms of accuracy and shape, which implies that the
geometry of the tumor is preserved for further clinical activities (such
as automatic extraction of pharmaco-kinetics properties, lesion
characterization, etc.).
Abstract: The aim of the present study is to detect the chaotic
behavior in monetary economic relevant dynamical system. The
study employs three different forms of Taylor rules: current, forward,
and backward looking. The result suggests the existence of the
chaotic behavior in all three systems. In addition, the results strongly
represent that using expectations in policy rule especially rational
expectation hypothesis can increase complexity of the system and
leads to more chaotic behavior.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: Neural activity in the human brain starts from the
early stages of prenatal development. This activity or signals
generated by the brain are electrical in nature and represent not only
the brain function but also the status of the whole body. At the
present moment, three methods can record functional and
physiological changes within the brain with high temporal resolution
of neuronal interactions at the network level: the
electroencephalogram (EEG), the magnet oencephalogram (MEG),
and functional magnetic resonance imaging (fMRI); each of these has
advantages and shortcomings. EEG recording with a large number of
electrodes is now feasible in clinical practice. Multichannel EEG
recorded from the scalp surface provides very valuable but indirect
information about the source distribution. However, deep electrode
measurements yield more reliable information about the source
locations intracranial recordings and scalp EEG are used with the
source imaging techniques to determine the locations and strengths of
the epileptic activity. As a source localization method, Low
Resolution Electro-Magnetic Tomography (LORETA) is solved for
the realistic geometry based on both forward methods, the Boundary
Element Method (BEM) and the Finite Difference Method (FDM). In
this paper, we review the findings EEG- LORETA about epilepsy.
Abstract: Information generated from various computerization processes is a potential rich source of knowledge for its designated community. To pass this information from generation to generation without modifying the meaning is a challenging activity. To preserve and archive the data for future generations it’s very essential to prove the authenticity of the data. It can be achieved by extracting the metadata from the data which can prove the authenticity and create trust on the archived data. Subsequent challenge is the technology obsolescence. Metadata extraction and standardization can be effectively used to resolve and tackle this problem. Metadata can be categorized at two levels i.e. Technical and Domain level broadly. Technical metadata will provide the information that can be used to understand and interpret the data record, but only this level of metadata isn’t sufficient to create trustworthiness. We have developed a tool which will extract and standardize the technical as well as domain level metadata. This paper is about the different features of the tool and how we have developed this.
Abstract: This paper focuses on a critical component of the
situational awareness (SA), the control of autonomous vertical flight
for vectored thrust aerial vehicle (VTAV). With the SA strategy, we
proposed a neural network motion control procedure to address the
dynamics variation and performance requirement difference of flight
trajectory for a VTAV. This control strategy with using of NARMAL2
neurocontroller for chosen model of VTAV has been verified by
simulation of take-off and forward maneuvers using software
package Simulink and demonstrated good performance for fast
stabilization of motors, consequently, fast SA with economy in
energy can be asserted during search-and-rescue operations.