Abstract: Lately management strategy that put Industrial Design (ID) in its core is recognized more important, as technology and price alone cannot differentiate a product. The needs to shorten the time to develop a product also shorten the development period of ID, and it necessitates the ID process management. This research analyzes the status of integration process of ID and Engineering Design (ED) of office equipment that requires the collaboration of ID and ED to clarify the issues for the efficiency of the development and to propose solutions.
Abstract: So much energy is used in high rise buildings to fulfill
the basic needs of users such as lighting and thermal comfort.
Malaysia has hot and humid climate, buildings especially high rise
buildings receive unnecessary solar radiation that cause more solar
heat gain. Energy use specially electricity consumption in high rise
buildings has increased. There have been growing concerns about
energy consumption and its effect on environment. Building, energy
and the environment are important issues that the designers should
consider to them. Self protected form is one of possible ways against
the impact of solar radiation in high rise buildings. The Energy
performance of building envelopes was investigated in term of the
Overall Thermal Transfer Value (OTTV ).In this paper, the amount
of OTTV reduction was calculated through OTTV Equations to
clear the effectiveness of self shading strategy on minimizing energy
consumption for cooling interior spaces in high rise buildings which
has considerable envelope areas against solar radiation. Also increasing
the optimum window area was investigated using self-shading
strategy in designing high rise buildings. As result, the significant
reduction in OTTV was shown based on WWR.In addition slight
increase was demonstrated in WWR that can influence on visible
comfort interior spaces.
Abstract: One of the most important parameters to develop and
manage urban areas is appropriate selection of land surface to
develop green spaces in these areas. In this study, in order to identify
the most appropriate sites and areas cultivated for ornamental species
in Jiroft, Landsat Enhanced Thematic Mapper Plus (ETM+) images
due to extract the most important effective climatic and adaphic
parameters for growth ornamental species were used. After geometric
and atmospheric corrections applied, to enhance accuracy of multi
spectral (XS) bands, the fusion of Landsat XS bands by IRS-1D
panchromatic band (PAN) was performed. After field sampling to
evaluate the correlation between different factors in surface soil
sampling location and different bands digital number (DN) of ETM+
sensor on the same points, correlation tables formed using the best
computational model and the map of physical and chemical
parameters of soil was produced. Then the accuracy of them was
investigated by using kappa coefficient. Finally, according to
produced maps, the best areas for cultivation of recommended
species were introduced.
Abstract: Until recently, researchers have developed various
tools and methodologies for effective clinical decision-making.
Among those decisions, chest pain diseases have been one of
important diagnostic issues especially in an emergency department. To
improve the ability of physicians in diagnosis, many researchers have
developed diagnosis intelligence by using machine learning and data
mining. However, most of the conventional methodologies have been
generally based on a single classifier for disease classification and
prediction, which shows moderate performance. This study utilizes an
ensemble strategy to combine multiple different classifiers to help
physicians diagnose chest pain diseases more accurately than ever.
Specifically the ensemble strategy is applied by using the integration
of decision trees, neural networks, and support vector machines. The
ensemble models are applied to real-world emergency data. This study
shows that the performance of the ensemble models is superior to each
of single classifiers.
Abstract: Ranking of fuzzy numbers play an important role in
decision making, optimization, forecasting etc. Fuzzy numbers must
be ranked before an action is taken by a decision maker. In this
paper, with the help of several counter examples it is proved that
ranking method proposed by Chen and Chen (Expert Systems with
Applications 36 (2009) 6833-6842) is incorrect. The main aim of this
paper is to propose a new approach for the ranking of generalized
trapezoidal fuzzy numbers. The main advantage of the proposed
approach is that the proposed approach provide the correct ordering
of generalized and normal trapezoidal fuzzy numbers and also the
proposed approach is very simple and easy to apply in the real life
problems. It is shown that proposed ranking function satisfies all
the reasonable properties of fuzzy quantities proposed by Wang and
Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).
Abstract: This paper presented a collaborative education model,
which consists four parts: collaborative teaching, collaborative
working, collaborative training and interaction. Supported by an
e-learning platform, collaborative education was practiced in a data
structure e-learning course. Data collected shows that most of students
accept collaborative education. This paper goes one step attempting to
determine which aspects appear to be most important or helpful in
collaborative education.
Abstract: Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.
Abstract: In sport, human resources management gives special
attention to method of applying volunteers, their maintenance, and
participation of volunteers with each other and management
approaches for better operation of events celebrants. The recognition
of volunteers- characteristics and motives is important to notice,
because it makes the basis of their participation and commitment at
sport environment. The motivation and commitment of 281
volunteers were assessed using the organizational commitment scale,
motivation scale and personal characteristics questionnaire.The
descriptive results showed that; 64% of volunteers were women with
age average 21/24 years old. They were physical education student,
single (71/9%), without occupation (53%) and with average of 5
years sport experience. Their most important motivation was career
factor and the most important commitment factor was normative
factor. The results of examining the hypothesized showed that; age,
sport experience and education are effective in the amount of
volunteers- commitment. And the motive factors such as career,
material, purposive and protective factors also have the power to
predict the amount of sports volunteers- commitment value.
Therefore it is recommended to provide possible opportunities for
volunteers and carrying out appropriate instructional courses by
events executive managers.
Abstract: In this research, Forming Limit Diagrams for supertension
sheet metals which are using in automobile industry have
been obtained. The exerted strains to sheet metals have been
measured with four different methods and the errors of each method
have also been represented. These methods have been compared with
together and the most efficient and economic way of extracting of the
exerted strains to sheet metals has been introduced. In this paper total
error and uncertainty of FLD extraction procedures have been
derived. Determination of the measurement uncertainty in extracting
of FLD has a great importance in design and analysis of the sheet
metal forming process.
Abstract: The efficient knowledge management system (KMS)
is one of the important strategies to help firms to achieve sustainable
competitive advantages, but little research has been conducted to
understand what contributes to the KMS success. This study thus set
to investigate the determinants of KMS success in the context of Thai
banking industry. A questionnaire survey was conducted in four
major Thai Banks to test the proposed KMS Success model.
The result of this study shows that KMS use and user satisfaction
relate significantly to the success of KMS, and knowledge quality,
service quality and trust lead to system use, and knowledge quality,
system quality and trust lead to user satisfaction. However, this
research focuses only on system and user-related factors. Future
research thus can extend to study factors such as management support
and organization readiness.
Abstract: The growing outsourcing of logistics services
resulting from the ongoing current in firms of costs
reduction/increased efficiency means that it is becoming more and
more important for the companies doing the outsourcing to carry out
a proper evaluation.
The multiple definitions and measures of logistics service
performance found in research on the topic create a certain degree of
confusion and do not clear the way towards the proper measurement
of their performance. Do a model and a specific set of indicators exist
that can be considered appropriate for measuring the performance of
logistics services outsourcing in industrial environments? Are said
indicators in keeping with the objectives pursued by outsourcing? We
aim to answer these and other research questions in the study we have
initiated in the field within the framework of the international High
Performance Manufacturing (HPM) project of which this paper
forms part.
As the first stage of this research, this paper reviews articles
dealing with the topic published in the last 15 years with the aim of
detecting the models most used to make this measurement and
determining which performance indicators are proposed as part of
said models and which are most used. The first steps are also taken in
determining whether these indicators, financial and operational, cover
the aims that are being pursued when outsourcing logistics services.
The findings show there is a wide variety of both models and
indicators used. This would seem to testify to the need to continue
with our research in order to try to propose a model and a set of
indicators for measuring the performance of logistics services
outsourcing in industrial environments.
Abstract: This paper describes a 3D modeling system in
Augmented Reality environment, named 3DARModeler. It can be
considered a simple version of 3D Studio Max with necessary
functions for a modeling system such as creating objects, applying
texture, adding animation, estimating real light sources and casting
shadows. The 3DARModeler introduces convenient, and effective
human-computer interaction to build 3D models by combining both
the traditional input method (mouse/keyboard) and the tangible input
method (markers). It has the ability to align a new virtual object with
the existing parts of a model. The 3DARModeler targets nontechnical
users. As such, they do not need much knowledge of
computer graphics and modeling techniques. All they have to do is
select basic objects, customize their attributes, and put them together
to build a 3D model in a simple and intuitive way as if they were
doing in the real world. Using the hierarchical modeling technique,
the users are able to group several basic objects to manage them as a
unified, complex object. The system can also connect with other 3D
systems by importing and exporting VRML/3Ds Max files. A
module of speech recognition is included in the system to provide
flexible user interfaces.
Abstract: Recent financial international scandals around the world have led to a number of investigations into the effectiveness of corporate governance practices and audit quality. Although evidence of corporate governance practices and audit quality exists from developed economies, very scanty studies have been conducted in Egypt where corporate governance is just evolving. Therefore, this study provides evidence on the effectiveness of corporate governance practices and audit quality from a developing country. The data for analysis are gathered from the top 50 most active companies in the Egyptian Stock Exchange, covering the three year period 2007-2009. Logistic regression was used in investigating the questions that were raised in the study. Findings from the study show that board independence; CEO duality and audit committees significantly have relationship with audit quality. The results also, indicate that institutional investor and managerial ownership have no significantly relationship with audit quality. Evidence also exist that size of the company; complexity and business leverage are important factors in audit quality for companies quoted on the Egypt Stock Exchange.
Abstract: The birdhouses and dovecotes, which are the indicator
of naturalness and human-animal relationship, are one of the
traditional cultural values of Turkey. With their structures compatible
with nature and respectful to humans the bird houses and dovecotes,
which have an important position in local urbanization models as a
representative of the civil architecture with their unique form and
function are important subjects that should be evaluated in a wide
frame comprising from architecture to urbanism, from ecologic
agriculture to globalization. The traditional bird houses and
dovecotes are disregarded due to the insensitivity affecting the city
life and the change in the public sense of art. In this study, the
characteristic properties of traditional dovecotes and birdhouses,
started in 13th century and ended in 19th century in Anatolia, are
tried to be defined for the sustainability of the tradition and for giving
a new direction to the designers.
Abstract: carrot is one of the important root vegetable crops,
and it is highly nutritious as it contains appreciable amount of
vitamins, minerals and β-carotene. The major objective of current
research was to evaluate the chemical composition of carrot variety
'Nante' hybrids in general and to select the best samples for fresh-cut
salad production. The research was accomplished on fresh in Latvia
cultivated carrots harvested in Zemgale region in the first part of
October, 2011 and immediately used for experiments. Late-bearing
variety 'Nante' hybrid carrots were used for analysis:
'Nante/Berlikum', 'Nante/Maestro', 'Nante/Forto', 'Nante/Bolero'
and 'Nante/Champion'. The quality parameters as moisture, soluble
solid, firmness, b-carotene, carotenoid, color, polyphenols, total
phenolic compounds and total antioxidant capacity were analyzed
using standard methods. For fresh-cut salad production as more
applicable could be recommended hybrids 'Nante/Forto' and
'Nante/Berlikum' - mainly because it-s higher nutritive value, as
higher total phenolic compounds, polyphenols and pronounced
antioxidant capacity.
Abstract: This paper describes the application of a model
predictive controller to the problem of batch reactor temperature
control. Although a great deal of work has been done to improve
reactor throughput using batch sequence control, the control of the
actual reactor temperature remains a difficult problem for many
operators of these processes. Temperature control is important as
many chemical reactions are sensitive to temperature for formation of
desired products. This controller consist of two part (1) a nonlinear
control method GLC (Global Linearizing Control) to create a linear
model of system and (2) a Model predictive controller used to obtain
optimal input control sequence. The temperature of reactor is tuned
to track a predetermined temperature trajectory that applied to the
batch reactor. To do so two input signals, electrical powers and the
flow of coolant in the coil are used. Simulation results show that the
proposed controller has a remarkable performance for tracking
reference trajectory while at the same time it is robust against noise
imposed to system output.
Abstract: One of the most important problems in production planning of flexible manufacturing system (FMS) is machine tool selection and operation allocation problem that directly influences the production costs and times .In this paper minimizing machining cost, set-up cost and material handling cost as a multi-objective problem in flexible manufacturing systems environment are considered. We present a 0-1 integer linear programming model for the multiobjective machine tool selection and operation allocation problem and due to the large scale nature of the problem, solving the problem to obtain optimal solution in a reasonable time is infeasible, Paretoant colony optimization (P-ACO) approach for solving the multiobjective problem in reasonable time is developed. Experimental results indicate effectiveness of the proposed algorithm for solving the problem.
Abstract: The evolutionary tree is an important topic in bioinformation. In 2006, Chen and Lindsay proposed a new method to build the mixture tree from DNA sequences. Mixture tree is a new type evolutionary tree, and it has two additional information besides the information of ordinary evolutionary tree. One of the information is time parameter, and the other is the set of mutated sites. In 2008, Lin and Juan proposed an algorithm to compute the distance between two mixture trees. Their algorithm computes the distance with only considering the time parameter between two mixture trees. In this paper, we proposes a method to measure the similarity of two mixture trees with considering the set of mutated sites and develops two algorithm to compute the distance between two mixture trees. The time complexity of these two proposed algorithms are O(n2 × max{h(T1), h(T2)}) and O(n2), respectively
Abstract: Association rules are an important problem in data
mining. Massively increasing volume of data in real life databases
has motivated researchers to design novel and incremental algorithms
for association rules mining. In this paper, we propose an incremental
association rules mining algorithm that integrates shocking
interestingness criterion during the process of building the model. A
new interesting measure called shocking measure is introduced. One
of the main features of the proposed approach is to capture the user
background knowledge, which is monotonically augmented. The
incremental model that reflects the changing data and the user beliefs
is attractive in order to make the over all KDD process more
effective and efficient. We implemented the proposed approach and
experiment it with some public datasets and found the results quite
promising.
Abstract: Mitochondria are dynamic organelles, capable to
interact with each other. While the number of mitochondria in a cell
varies, their quality and functionality depends on the operation of
fusion, fission, motility and mitophagy. Nowadays, several
researches declare as an important factor in neurogenerative diseases
the disruptions in the regulation of mitochondrial dynamics. In this
paper a stochastic model in BioAmbients calculus is presented,
concerning mitochondrial fusion and its distribution in the renewal of
mitochondrial population in a cell. This model describes the
successive and dependent stages of protein synthesis, protein-s
activation and merging of two independent mitochondria.