Abstract: The paper deals with the analysis of triggering
conditions and evolution processes of piping phenomena, in relation
to both mechanical and hydraulic aspects. In particular, the aim of
the study is to predict slope instabilities triggered by piping,
analysing the conditions necessary for a flow failure to occur. Really,
the mechanical effect involved in the loads redistribution around the
pipe is coupled to the drainage process arising from higher
permeability of the pipe. If after the pipe formation, the drainage
goes prevented for pipe clogging, the porewater pressure increase can
lead to the failure or even the liquefaction, with a subsequent flow
slide. To simulate the piping evolution and to verify relevant stability
conditions, a iterative coupled modelling approach has been pointed
out. As example, the proposed tool has been applied to the Stava
Valley disaster (July, 1985), demonstrating that piping might be one
of triggering phenomena of the tailings dams collapse.
Abstract: Sports Sciences has been historically supported by the positivism idea of science, especially by the mechanistic/reductionist and becomes a field that views experimentation and measurement as the mayor research domains. The disposition to simplify nature and the world by parts has fragmented and reduced the idea of bodyathletes as machine. In this paper we intent to re-think this perception lined by Complexity Theory. We come with the idea of athletes as a reflexive and active being (corporeity-body). Therefore, the construction of a training that considers the cultural, biological, psychological elements regarding the experience of the human corporal movements in a circumspect and responsible way could bring better chances of accomplishment. In the end, we hope to help coaches understand the intrinsic complexity of the body they are training, how better deal with it, and, in the field of a deep globalization among the different types of knowledge, to respect and accepted the peculiarities of knowledge that comprise this area.
Abstract: Water is the key of national development. Wherever a spring has been dried out or a river has changed its course, the area-s people have migrated and have been scattered and the area-s civilization has lost its brilliance. Today, air pollution, global warming and ozone layer damage are as the problems of countries, but certainly in the next decade the shortage and pollution of waters will be important issues of the world. The polluted waters are more dangerous in when they are used in agriculture. Because they infect plants and these plants are used in human and livestock consumption in food chain. With the increasing population growth and after that, the increase need to facilities and raw materials, human beings has started to do haste actions and wanted or unwanted destroyed his life basin. They try to overuse and capture his environment extremely, instead of having futurism approach in sustainable use of nature. This process includes Zayanderood recession, and caused its pollution after the transition from industrial and urban areas. Zayandehrood River in Isfahan is a vital artery of a living ecosystem. Now is the location of disposal waste water of many cities, villages and existing industries. The central area of the province is an important industrial place, and its environmental situation has reached a critical stage. Not only a large number of pollution-generating industries are active in the city limits, but outside of the city and adjacent districts Zayandehrood River, heavy industries like steel, Mobarakeh Steel and other tens great units pollute wild life. This article tries to study contaminant sources of Zayanderood and their severity, and determine and discuss the share of each of these resources by major industrial centers located in areas. At the end, we represent suitable strategy.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: One part of the total employee’s reward is apart from basic wages or salary, employee’s benefits and intangible remuneration also so called contingent (variable) pay. Contingent pay is connected to performance, contribution, cap competency or skills of individual employees, and to team’s or company-wide performance or to combination of few of the mentioned possibilities. Sometimes among the contingent pay is also incorporated the remuneration based on length of employment, when the financial reward is not connected to performance or skills, but to length of continuous employment either on one working position or in one level of remuneration scale. Main aim of this article is to define, based on available information, contingent pay, describe individual forms, its advantages and disadvantages and possibilities to utilization in practice; but also bring information not only about its extent and level of utilization of contingent pay by companies in one of the Czech Republic’s regions, but also mention their practical experience with this type of remuneration.
Abstract: This paper examines the interplay of policy options
and cost-effective technology in providing sustainable distance
education. A case study has been conducted among the learners and
teachers. The emergence of learning technologies through CD,
internet, and mobile is increasingly adopted by distance institutes for
quick delivery and cost-effective factors. Their sustainability is
conditioned by the structure of learners and well as the teaching
community. The structure of learners in terms of rural and urban
background revealed similarity in adoption and utilization of mobile
learning. In other words, the technology transcended the rural-urban
dichotomy. The teaching community was divided into two groups on
policy issues. This study revealed both cost-effective as well as
sustainability impacts on different learners groups divided by rural
and urban location.
Abstract: Product customization is an essential requirement for
manufacturing firms to achieve higher customers- satisfaction and
fulfill business target. In order to achieve these objectives, firms need
to handle both external varieties such as customer preference,
government regulations, cultural considerations etc and internal
varieties such as functional requirements of product, production
efficiency, quality etc. Both of the varieties need to be accumulated
and integrated together for the purpose of producing customized
product. These varieties are presented and discussed in this paper
along with the perspectives of modular product design and
development process. Other development strategies such as
modularity, component commonality, product family design and
product platform are presented with a view to achieve product variety
quickly and economically. A case example both for the concept of
modular design and platform based product development process is
also presented with the help of design structure matrix (DSM) tool.
This paper is concluded with several managerial implications and
future research direction.
Abstract: In this contribution is presented a complex design of
individual objects identification in the workplace of intelligent
assembly cell. Intelligent assembly cell is situated at Institute of
Manufacturing Systems and Applied Mechanics and is used for
pneumatic actuator assembly. Pneumatic actuator components are
pneumatic roller, cover, piston and spring. Two identification objects
alternatives for assembly are designed in the workplace of industrial
robot. In the contribution is evaluated and selected suitable
alternative for identification – 2D codes reader. The complex design
of individual object identification is going out of intelligent
manufacturing systems knowledge.
Intelligent assembly and manufacturing systems as systems of
new generation are gradually loaded in to the mechanical production,
when they are removeing human operation out of production process
and they also short production times.
Abstract: Data Mining aims at discovering knowledge out of
data and presenting it in a form that is easily comprehensible to
humans. One of the useful applications in Egypt is the Cancer
management, especially the management of Acute Lymphoblastic
Leukemia or ALL, which is the most common type of cancer in
children.
This paper discusses the process of designing a prototype that can
help in the management of childhood ALL, which has a great
significance in the health care field. Besides, it has a social impact
on decreasing the rate of infection in children in Egypt. It also
provides valubale information about the distribution and
segmentation of ALL in Egypt, which may be linked to the possible
risk factors.
Undirected Knowledge Discovery is used since, in the case of this
research project, there is no target field as the data provided is
mainly subjective. This is done in order to quantify the subjective
variables. Therefore, the computer will be asked to identify
significant patterns in the provided medical data about ALL. This
may be achieved through collecting the data necessary for the
system, determimng the data mining technique to be used for the
system, and choosing the most suitable implementation tool for the
domain.
The research makes use of a data mining tool, Clementine, so as to
apply Decision Trees technique. We feed it with data extracted from
real-life cases taken from specialized Cancer Institutes. Relevant
medical cases details such as patient medical history and diagnosis
are analyzed, classified, and clustered in order to improve the disease
management.
Abstract: With the advent of digital cinema and digital
broadcasting, copyright protection of video data has been one of the
most important issues.
We present a novel method of watermarking for video image data
based on the hardware and digital wavelet transform techniques and
name it as “traceable watermarking" because the watermarked data is
constructed before the transmission process and traced after it has been
received by an authorized user.
In our method, we embed the watermark to the lowest part of each
image frame in decoded video by using a hardware LSI.
Digital Cinema is an important application for traceable
watermarking since digital cinema system makes use of watermarking
technology during content encoding, encryption, transmission,
decoding and all the intermediate process to be done in digital cinema
systems. The watermark is embedded into the randomly selected
movie frames using hash functions.
Embedded watermark information can be extracted from the
decoded video data. For that, there is no need to access original movie
data. Our experimental results show that proposed traceable
watermarking method for digital cinema system is much better than the
convenient watermarking techniques in terms of robustness, image
quality, speed, simplicity and robust structure.
Abstract: The objective of this research is to study the technical
and economic performance of wind/diesel/battery (W/D/B) system
supplying a remote small gathering of six families using HOMER
software package. The electrical energy is to cater for the basic needs
for which the daily load pattern is estimated. Net Present Cost (NPC)
and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and
economic parameters are defined to estimate the feasibility of the
system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites
as the price of generated electricity is about 0.308 $/kWh, without
taking external benefits into considerations. W/D/B systems are more
economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.
Abstract: A novel nanofinishing process using improved ball
end magnetorheological (MR) finishing tool was developed for finishing of flat as well as 3D surfaces of ferromagnetic and non ferromagnetic workpieces. In this process a magnetically controlled
ball end of smart MR polishing fluid is generated at the tip surface of
the tool which is used as a finishing medium and it is guided to
follow the surface to be finished through computer controlled 3-axes
motion controller. The experiments were performed on ferromagnetic
workpiece surface in the developed MR finishing setup to study the effect of finishing time on final surface roughness. The performance
of present finishing process on final finished surface roughness was studied. The surface morphology was observed under scanning
electron microscopy and atomic force microscope. The final surface finish was obtained as low as 19.7 nm from the initial surface
roughness of 142.9 nm. The outcome of newly developed finishing process can be found useful in its applications in aerospace,
automotive, dies and molds manufacturing industries, semiconductor and optics machining etc.
Abstract: In this paper, we explore the applicability of the Sinc-
Collocation method to a three-dimensional (3D) oceanography model.
The model describes a wind-driven current with depth-dependent
eddy viscosity in the complex-velocity system. In general, the
Sinc-based methods excel over other traditional numerical methods
due to their exponentially decaying errors, rapid convergence and
handling problems in the presence of singularities in end-points.
Together with these advantages, the Sinc-Collocation approach that
we utilize exploits first derivative interpolation, whose integration
is much less sensitive to numerical errors. We bring up several
model problems to prove the accuracy, stability, and computational
efficiency of the method. The approximate solutions determined by
the Sinc-Collocation technique are compared to exact solutions and
those obtained by the Sinc-Galerkin approach in earlier studies. Our
findings indicate that the Sinc-Collocation method outperforms other
Sinc-based methods in past studies.
Abstract: The identification and classification of the spine deformity play an important role when considering surgical planning for adolescent patients with idiopathic scoliosis. The subject of this article is the Lenke classification of scoliotic spines using Cobb angle measurements. The purpose is two-fold: (1) design a rulebased diagram to assist clinicians in the classification process and (2) investigate a computer classifier which improves the classification time and accuracy. The rule-based diagram efficiency was evaluated in a series of scoliotic classifications by 10 clinicians. The computer classifier was tested on a radiographic measurement database of 603 patients. Classification accuracy was 93% using the rule-based diagram and 99% for the computer classifier. Both the computer classifier and the rule based diagram can efficiently assist clinicians in their Lenke classification of spine scoliosis.
Abstract: The empirical studies on High Performance Work Systems (HPWSs) and their impacts on firm performance have remarkably little in the developing countries. This paper reviews literatures on the HPWSs practices in different work settings, Western and Asian countries. A review on the empirical research leads to a conclusion that, country differences influence the Human Resource Management (HRM) practices. It is anticipated that there are similarities and differences in the extent of implementation of HPWSs practices by the Malaysian manufacturing firms due to the organizational contextual factors and, the HPWSs have a significant impact on firms- better performance amongst MNCs and local firms.
Abstract: In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.
Abstract: The aim of this paper is to determine the stress levels
at the end of a long slender shaft such as a drilling assembly used in
the oil or gas industry using a mathematical model in real-time. The
torsional deflection experienced by this type of drilling shaft (about 4
KM length and 20 cm diameter hollow shaft with a thickness of 1
cm) can only be determined using a distributed modeling technique.
The main objective of this project is to calculate angular velocity and
torque at the end of the shaft by TLM method and also analyzing of
the behavior of the system by transient response. The obtained result
is compared with lumped modeling technique the importance of these
results will be evident only after the mentioned comparison. Two
systems have different transient responses and in this project because
of the length of the shaft transient response is very important.
Abstract: The paper is dealing by testing of ceramic cutting
tools with an interrupted machining. Tests will be provided on fixture
– interrupted cut simulator. This simulator has 4 mouldings on
circumference and cutting edge is put a shocks during 1 revolution.
Criteria of tool wear are destruction of cutting tool or 6000 shocks.
Like testing cutting tool material will be products of Sandvik
Coromant 6190, 620, 650 and 670. Machined materials was be steels
15 128 (13MoCrV6). Cutting speed (408 m.min-1 and 580 m.min-1)
and cutting feed (0,15 mm; 0,2 mm; 0,25 mm and 0,3 mm) were
variable parameters and cutting depth was constant parameter.
Abstract: This paper aims at developing a multilevel fuzzy
decision support model for urban rail transit planning schemes in
China under the background that China is presently experiencing an
unprecedented construction of urban rail transit. In this study, an
appropriate model using multilevel fuzzy comprehensive evaluation
method is developed. In the decision process, the followings are
considered as the influential objectives: traveler attraction,
environment protection, project feasibility and operation. In addition,
consistent matrix analysis method is used to determine the weights
between objectives and the weights between the objectives-
sub-indictors, which reduces the work caused by repeated
establishment of the decision matrix on the basis of ensuring the
consistency of decision matrix. The application results show that
multilevel fuzzy decision model can perfectly deal with the
multivariable and multilevel decision process, which is particularly
useful in the resolution of multilevel decision-making problem of
urban rail transit planning schemes.
Abstract: The network traffic data provided for the design of
intrusion detection always are large with ineffective information and
enclose limited and ambiguous information about users- activities.
We study the problems and propose a two phases approach in our
intrusion detection design. In the first phase, we develop a
correlation-based feature selection algorithm to remove the worthless
information from the original high dimensional database. Next, we
design an intrusion detection method to solve the problems of
uncertainty caused by limited and ambiguous information. In the
experiments, we choose six UCI databases and DARPA KDD99
intrusion detection data set as our evaluation tools. Empirical studies
indicate that our feature selection algorithm is capable of reducing the
size of data set. Our intrusion detection method achieves a better
performance than those of participating intrusion detectors.