Abstract: Today's business environment requires that companies have access to highly relevant information in a matter of seconds.
Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by
star schemas. Dimensional modeling is already recognized as a
leading industry standard in the field of data warehousing although
several drawbacks and pitfalls were reported. This paper focuses on
the analysis of another data warehouse modeling technique - the
anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show
information about performance of queries executed on database
schemas structured according to principles of each database modeling
technique.
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: Twelve lactating Etawah Crossedbred goats were used
in this study. Goat feed consisted of Cally andra callothyrsus,
Pennisetum purpureum, wheat bran and dried fermented cassava
peel. The cassava peels were fermented with a traditional culture
called “ragi tape" (mixed culture of Saccharomyces cerevisae,
Aspergillus sp, Candida, Hasnula and Acetobacter). The goats were
divided into 2 groups (Control and Treated) of six does. The
experimental diet of the Control group consisted of 70% of roughage
(fresh Callyandra callothyrsus and Pennisetum purpureum 60:40)
and 30% of wheat bran on dry matter (DM) base. In the Treated
group 30% of wheat bran was replaced with dried fermented cassava
peels. Data were statistically analyzed using analysis of variance
followed SPSS program. The concentration of HCN in fermented
cassava peel decreased to non toxic level. Nutrient composition of
dried fermented cassava peel consisted of 85.75% dry matter;
5.80% crude protein and 82.51% total digestible nutrien (TDN).
Substitution of 30% of wheat bran with dried fermented cassava peel
in the diet had no effect on dry matter and organic matter intake but
significantly (P< 0.05) decreased crude protein and TDN
consumption as well as milk yields and milk composition. The study
recommended to reduced the level of substitution to less than 30% of
concentrates in the diet in order to avoid low nutrient intake and milk
production of goats.
Abstract: Although Face detection is not a recent activity in the
field of image processing, it is still an open area for research. The
greatest step in this field is the work reported by Viola and its recent
analogous is Huang et al. Both of them use similar features and also
similar training process. The former is just for detecting upright
faces, but the latter can detect multi-view faces in still grayscale
images using new features called 'sparse feature'. Finding these
features is very time consuming and inefficient by proposed methods.
Here, we propose a new approach for finding sparse features using a
genetic algorithm system. This method requires less computational
cost and gets more effective features in learning process for face
detection that causes more accuracy.
Abstract: Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.
Abstract: This paper presents an approach for an unequal error
protection of facial features of personal ID images coding. We
consider unequal error protection (UEP) strategies for the efficient
progressive transmission of embedded image codes over noisy
channels. This new method is based on the progressive image
compression embedded zerotree wavelet (EZW) algorithm and UEP
technique with defined region of interest (ROI). In this case is ROI
equal facial features within personal ID image. ROI technique is
important in applications with different parts of importance. In ROI
coding, a chosen ROI is encoded with higher quality than the
background (BG). Unequal error protection of image is provided by
different coding techniques and encoding LL band separately. In our
proposed method, image is divided into two parts (ROI, BG) that
consist of more important bytes (MIB) and less important bytes
(LIB). The proposed unequal error protection of image transmission
has shown to be more appropriate to low bit rate applications,
producing better quality output for ROI of the compresses image.
The experimental results verify effectiveness of the design. The
results of our method demonstrate the comparison of the UEP of
image transmission with defined ROI with facial features and the
equal error protection (EEP) over additive white gaussian noise
(AWGN) channel.
Abstract: The paper compares the treatment of fractions in a
typical undergraduate college curriculum and in abstract algebra
textbooks. It stresses that the main difference is that the
undergraduate curriculum treats equivalent fractions as equal, and
this treatment eventually leads to paradoxes and impairs the students-
ability to perceive ratios, proportions, radicals and rational exponents
adequately. The paper suggests a simplified version of rigorous
theory of fractions suitable for regular college curriculum.
Abstract: This paper presents a method of model selection and
identification of Hammerstein systems by hybridization of the genetic
algorithm (GA) and particle swarm optimization (PSO). An unknown
nonlinear static part to be estimated is approximately represented
by an automatic choosing function (ACF) model. The weighting
parameters of the ACF and the system parameters of the linear
dynamic part are estimated by the linear least-squares method. On
the other hand, the adjusting parameters of the ACF model structure
are properly selected by the hybrid algorithm of the GA and PSO,
where the Akaike information criterion is utilized as the evaluation
value function. Simulation results are shown to demonstrate the
effectiveness of the proposed hybrid algorithm.
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: 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: The need for multilingual communication in Japan has
increased due to an increase in the number of foreigners in the
country. When people communicate in their nonnative language,
the differences in language prevent mutual understanding among
the communicating individuals. In the medical field, communication
between the hospital staff and patients is a serious problem. Currently,
medical translators accompany patients to medical care facilities, and
the demand for medical translators is increasing. However, medical
translators cannot necessarily provide support, especially in cases in
which round-the-clock support is required or in case of emergencies.
The medical field has high expectations from information technology.
Hence, a system that supports accurate multilingual communication is
required. Despite recent advances in machine translation technology,
it is very difficult to obtain highly accurate translations. We have
developed a support system called M3 for multilingual medical
reception. M3 provides support functions that aid foreign patients in
the following respects: conversation, questionnaires, reception procedures,
and hospital navigation; it also has a Q&A function. Users
can operate M3 using a touch screen and receive text-based support.
In addition, M3 uses accurate translation tools called parallel texts
to facilitate reliable communication through conversations between
the hospital staff and the patients. However, if there is no parallel
text that expresses what users want to communicate, the users cannot
communicate. In this study, we have developed a circulating support
environment for multilingual medical communication using parallel
texts. The proposed environment can circulate necessary parallel texts
through the following procedure: (1) a user provides feedback about
the necessary parallel texts, following which (2) these parallel texts
are created and evaluated.
Abstract: Experimental liquid-liquid equilibra of butan-2-ol -
ethanol -water; pentan-1-ol - ethanol - water and toluene - acetone -
water ternary systems were investigated at (25oC). The reliability of
the experimental tie-line data was ascertained by using Othmer-Tobias
and Hand plots. The distribution coefficients (D) and separation
factors (S) of the immiscibility region were evaluated for the three
systems.
Abstract: The article deals with the problems of political and
economic processes in Kazakhstan since independence in the context
of globalization. It analyzes the geopolitical situation and selfpositioning
processes in the world after the end of the "cold war". It
examines the problems of internal economization of the Republic for
20 years of independence. The authors argue that the reforms
proceeded in the economic sphere have brought ambiguous and
tangible results. Despite the difficult economic and political conditions
facing a world economical crisis the country has undergone
fundamental and radical transformations in the whole socio-economic
system
Abstract: Robust face recognition under various illumination
environments is very difficult and needs to be accomplished for
successful commercialization. In this paper, we propose an improved
illumination normalization method for face recognition. Illumination
normalization algorithm based on anisotropic smoothing is well known
to be effective among illumination normalization methods but
deteriorates the intensity contrast of the original image, and incurs less
sharp edges. The proposed method in this paper improves the previous
anisotropic smoothing-based illumination normalization method so
that it increases the intensity contrast and enhances the edges while
diminishing the effect of illumination variations. Due to the result of
these improvements, face images preprocessed by the proposed
illumination normalization method becomes to have more distinctive
feature vectors (Gabor feature vectors) for face recognition. Through
experiments of face recognition based on Gabor feature vector
similarity, the effectiveness of the proposed illumination
normalization method is verified.
Abstract: Natural frequencies and dynamic response of a spur
gear sector are investigated using a two dimensional finite element
model that offers significant advantages for dynamic gear analyses.
The gear teeth are analyzed for different operating speeds. A primary
feature of this modeling is determination of mesh forces using a
detailed contact analysis for each time step as the gears roll through
the mesh. ANSYS software has been used on the proposed model to
find the natural frequencies by Block Lanczos technique and
displacements and dynamic stresses by transient mode super position
method. The effect of rotational speed of the gear on the dynamic
response of gear tooth has been studied and design limits have been
discussed.
Abstract: There are many real world problems in which
parameters like the arrival time of new jobs, failure of resources, and
completion time of jobs change continuously. This paper tackles the
problem of scheduling jobs with random due dates on multiple
identical machines in a stochastic environment. First to assign jobs to
different machine centers LPT scheduling methods have been used,
after that the particular sequence of jobs to be processed on the
machine have been found using simple stochastic techniques. The
performance parameter under consideration has been the maximum
lateness concerning the stochastic due dates which are independent
and exponentially distributed. At the end a relevant problem has been
solved using the techniques in the paper..
Abstract: The new idea of analyze of power system failure with
use of artificial neural network is proposed. An analysis of the
possibility of simulating phenomena accompanying system faults and
restitution is described. It was indicated that the universal model for
the simulation of phenomena in whole analyzed range does not exist.
The main classic method of search of optimal structure and
parameter identification are described shortly. The example with
results of calculation is shown.
Abstract: Shoots, with three leaves, of Paphiopedilum 'Delrosi'
were used as explants for multiple shoot induction. Modified
Hyponex medium was supplemented with thidiazuron (TDZ), N6-
benzyladenine (BA) or kinetin (Kn) alone and in combinations with
2,4-dichlorophenoxyacetic acid (2,4-D). All explants were cultured
for 15 weeks. It was found that TDZ alone at the concentration of
0.45μM or in combination with 4.52μM 2,4-D and 8.88μM BA in
combination with 13.56μM 2,4-D promoted multiple shoots. The
highest shoot sprouting efficiencies (80.0, 90.0 and 80.0%) and new
shoot numbers (1.5, 1.3 and 1.1) were obtained, respectively. Fresh
weight, height, numbers of leaf and root of new shoots and initial
explants were discussed.