Abstract: In Both developed and developing countries,
governments play a basic role in making policies, programs and
instruments which support the development of micro, small and
medium enterprises. One of the mechanisms employed to nurture
small firms for more than two decades is business incubation. One of
the mechanisms employed to nurture small firms for more than two
decades is technology business incubation. The main aim of this
research was to establish influencing factors in Technology Business
Incubator's effectiveness and their explanatory model. Therefore,
among 56 Technology Business Incubators in Iran, 32 active
incubators were selected and by stratified random sampling, 528
start-ups were chosen. The validity of research questionnaires
was determines by expert consensus, item analysis and factor
analysis; and their reliability calculated by Cronbach-s alpha.
Data analysis was then made through SPSS and LISREL soft wares.
Both organizational procedures and entrepreneurial behaviors were
the meaningful mediators. Organizational procedures with (P < .01, β
=0.45) was stronger mediator for the improvement of Technology
Business Incubator's effectiveness comparing to entrepreneurial
behavior with (P < .01, β =0.36).
Abstract: This research paper is based upon the simulation of
gradient of mathematical functions and scalar fields using MATLAB.
Scalar fields, their gradient, contours and mesh/surfaces are
simulated using different related MATLAB tools and commands for
convenient presentation and understanding. Different mathematical
functions and scalar fields are examined here by taking their
gradient, visualizing results in 3D with different color shadings and
using other necessary relevant commands. In this way the outputs of
required functions help us to analyze and understand in a better way
as compared to just theoretical study of gradient.
Abstract: Starting with an analysis of the financial and
operational indicators that can be found in the specialised literature,
this study aims to contribute to improvements in the performance
measurement systems used when the unit of analysis is the
manufacturing plant. For this a search was done in the highest impact
Journals of Production and Operations Management and
Management Accounting , with the aim of determining the financial
and operational indicators used to evaluate performance when
Advanced Production Practices have been implemented, more
specifically when the practices implemented are Total Quality
Management, JIT/Lean Manufacturing and Total Productive
Maintenance. This has enabled us to obtain a classification of the two
types of indicators based on how much each is used. For the financial
indicators we have also prepared a proposal that can be adapted to
manufacturing plants- accounting features. In the near future we will
propose a model that links practices implementation with financial
and operational indicators and these two last with each other. We aim
to will test this model empirically with the data obtained in the High
Performance Manufacturing Project.
Abstract: In July 1, 2007, Taiwan Stock Exchange (TWSE) on
market observation post system (MOPS) adds a new "Financial
reference database" for investors to do investment reference. This
database as a warning to public offering companies listed on the
public financial information and it original within eight targets. In
this paper, this database provided by the indicators for the application
of company financial crisis early warning model verify that the
database provided by the indicator forecast for the financial crisis,
whether or not companies have a high accuracy rate as opposed to
domestic and foreign scholars have positive results. There is use of
Logistic Regression Model application of the financial early warning
model, in which no joined back-conditions is the first model, joined it
in is the second model, has been taken occurred in the financial crisis
of companies to research samples and then business took place
before the financial crisis point with T-1 and T-2 sample data to do
positive analysis. The results show that this database provided the
debt ratio and net per share for the best forecast variables.
Abstract: One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.
Abstract: Social cognitive theory explains the power to inaugurate change is determined by the mutual influence of personal proclivity and social factors which will shape ones- motivations and expectations. In construction industry, green concept offers an opportunity to leave a lighter footprint on the environment. This opportunity, however, has not been fully grasped by many countries. As such, venturing into green construction for many practitioners would be their maiden experience. Decision to venture into new practice such as green construction will be influenced by certain drivers. This paper explores these drivers which is further expanded into motivational factors and later becomes the platform upon which expectation for green construction stands. This theoretical concept of motivation and expectations, which is adapted from social cognitive theory, focus on developers- view because of their crucial role in green application. This conceptual framework, which serves as the basis for further research, will benefit the industry as it elucidate cognitive angles to attract more new entrants to green business.
Abstract: Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.
Abstract: An attempt was made to study of nitrogen
components response of corn (Zea mays L.) to drought stress. A farm
research was done in RCBD as split-plot with four replications in
Khorramabad, west Iran. Drought stress levels as irrigation regimes
after 75 (control), 100, and 120 (stress) mm cumulative evaporation
were in main plots, and four seed corn varieties include 500 (medium
maturity), 647, 700, and 704 (long maturity) were as subplots.
Soluble protein, nitrate and proline amino acid were measured in
shoot and root at flowering stage, and grain yield was measured in
harvesting stage. As the drought progressed, the amount of nitrate
and proline followed an increasing trend, but soluble protein
decreased in shoot and root. The highest amount of nitrate and
proline was observed in longer maturity varieties than shorter ones,
but decrease yield of long maturity varieties was higher than medium
maturity varieties in drought condition, because of long duration of
stress.
Abstract: With the rapid growth and development of information and communication technology, the Internet has played a definite and irreplaceable role in people-s social lives in Taiwan like in other countries. In July 2008, on a general social website, an unexpected phenomenon was noticed – that there were more than one hundred users who started forming clubs voluntarily and having face-to-face gatherings for specific purposes. In this study, it-s argued whether or not teenagers- social contact on the Internet is involved in their life context, and tried to reveal the teenagers- social preferences, values, and needs, which merge with and influence teenagers- social activities. Therefore, the study conducts multiple user experience research methods, which include practical observations and qualitative analysis by contextual inquiries and in-depth interviews. Based on the findings, several design implications for software related to social interactions and cultural inheritance are offered. It is concluded that the inherent values of a social behaviors might be a key issue in developing computer-mediated communication or interaction designs in the future.
Abstract: In face recognition, feature extraction techniques
attempts to search for appropriate representation of the data. However,
when the feature dimension is larger than the samples size, it brings
performance degradation. Hence, we propose a method called
Normalization Discriminant Independent Component Analysis
(NDICA). The input data will be regularized to obtain the most
reliable features from the data and processed using Independent
Component Analysis (ICA). The proposed method is evaluated on
three face databases, Olivetti Research Ltd (ORL), Face Recognition
Technology (FERET) and Face Recognition Grand Challenge
(FRGC). NDICA showed it effectiveness compared with other
unsupervised and supervised techniques.
Abstract: Changing in consumers lifestyles and food
consumption patterns provide a great opportunity in developing the
functional food sector in Malaysia. There is only a little knowledge
about whether Malaysian consumers are aware of functional food and
if so what image consumers have of this product. The objective of
this research is to determine the extent to which selected socioeconomic
characteristics and attitudes influence consumers-
awareness of functional food. A survey was conducted in the Klang
Valley, Malaysia where 439 respondents were interviewed using a
structured questionnaire. The result shows that most respondents
have a positive attitude towards functional food. For the binary
logistic estimation, the results indicate that age, income and other
factors such as concern about food safety, subscribing to cooking or
health magazines, being a vegetarian and consumers who have been
involved in a food production company significantly influence
Malaysian consumers- awareness towards functional food.
Abstract: Weblogs are resource of social structure to discover and track the various type of information written by blogger. In this paper, we proposed to use mining weblogs technique for identifying the trends of influenza where blogger had disseminated their opinion for the anomaly disease. In order to identify the trends, web crawler is applied to perform a search and generated a list of visited links based on a set of influenza keywords. This information is used to implement the analytics report system for monitoring and analyzing the pattern and trends of influenza (H1N1). Statistical and graphical analysis reports are generated. Both types of the report have shown satisfactory reports that reflect the awareness of Malaysian on the issue of influenza outbreak through blogs.
Abstract: One of the basic concepts in marketing is the concept
of meeting customers- needs. Since customer satisfaction is essential
for lasting survival and development of a business, screening and
observing customer satisfaction and recognizing its underlying
factors must be one of the key activities of every business.
The purpose of this study is to recognize the drivers that effect
customer satisfaction in a business-to-business situation in order to
improve marketing activities. We conducted a survey in which 93
business customers of a manufacturer of Diesel Generator in Iran
participated and they talked about their ideas and satisfaction of
supplier-s services related to its products. We developed the measures
for drivers of satisfaction first by as investigative research (by means
of feedback from executives and customers of sponsoring firm). Then
based on these measures, we created a mail survey, and asked the
respondents to explain their opinion about the sponsoring firm which
was a supplier of diesel generator and similar products. Furthermore,
the survey required the participants to mention their functional areas
and their company features.
In Conclusion we found that there are three drivers for customer
satisfaction, which are reliability, information about product, and
commercial features. Buyers/users from different functional areas
attribute different degree of importance to the last two drivers. For
instance, people from buying and management areas believe that
commercial features are more important than information about
products. But people in engineering, maintenance and production
areas believe that having information about products is more
important than commercial aspects. Marketing experts should
consider the attribute of customers regarding information about the
product and commercial features to improve market share.
Abstract: Recommender Systems act as personalized decision
guides, aiding users in decisions on matters related to personal taste.
Most previous research on Recommender Systems has focused on the
statistical accuracy of the algorithms driving the systems, with no
emphasis on the trustworthiness of the user. RS depends on
information provided by different users to gather its knowledge. We
believe, if a large group of users provide wrong information it will
not be possible for the RS to arrive in an accurate conclusion. The
system described in this paper introduce the concept of Testing the
knowledge of user to filter out these “bad users".
This paper emphasizes on the mechanism used to provide robust
and effective recommendation.
Abstract: This research tries to analyze the role that knowledge
about foreign markets has in increasing firms- exports in clustered
spaces. We consider two interrelated sources of knowledge: firms-
direct experience and indirect experience from other clustered firms –
export externalities. In particular, it is proposed that firms would
improve their export performance by accessing to export externalities
if they have some previous direct experience that allows them to
identify, understand and exploit them. Also, we propose that this
positive influence of previous direct experience on export
externalities keeps only up to a point, where it becomes negative,
creating an inverted “U" shape. Empirical evidence gathered among
wine producers located in La Rioja tends to confirm that firms enjoy
of export externalities if they have export experience along several
years and countries increase their export performance. While this
relationship becomes less relevant as they develop a higher
experience, we could not confirm the existence of a curvilinear
relationship in their influence on export externalities and export
performance.
Abstract: An intuitive user interface for the teleoperation of mobile rescue robots is one key feature for a successful exploration of inaccessible and no-go areas. Therefore, we have developed a novel framework to embed a flexible and modular user interface into a complete 3-D virtual reality simulation system. Our approach is based on a client-server architecture to allow for a collaborative control of the rescue robot together with multiple clients on demand. Further, it is important that the user interface is not restricted to any specific type of mobile robot. Therefore, our flexible approach allows for the operation of different robot types with a consistent concept and user interface. In laboratory tests, we have evaluated the validity and effectiveness of our approach with the help of two different robot platforms and several input devices. As a result, an untrained person can intuitively teleoperate both robots without needing a familiarization time when changing the operating robot.
Abstract: In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor,in a nonconcurrent form instead of being executed concurrently ina set of processors working and communicating through a network.This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies.
Abstract: Saffron (Crocus sativus) is cultivated as spices,
medicinal and aromatic plant species. At autumn season, heavy
rainfall can cause flooding stress and inhibits growth of saffron. Thus
this research was conducted to study the effect of silver ion (as an
ethylene inhibitor) on growth of saffron under flooding conditions.
The corms of saffron were soaked with one concentration of nano
silver (0, 40, 80 or 120 ppm) and then planting under flooding stress
or non flooding stress conditions. Results showed that number of
roots, root length, root fresh and dry weight, leaves fresh and dry
weight were reduced by 10 day flooding stress. Soaking saffron
corms with 40 or 80 ppm concentration of nano silver rewarded the
effect of flooding stress on the root number, by increasing it.
Furthermore, 40 ppm of nano silver increased root length in stress.
Nano silver 80 ppm in flooding stress, increased leaves dry weight.
Abstract: Proteomics is one of the largest areas of research for
bioinformatics and medical science. An ambitious goal of proteomics
is to elucidate the structure, interactions and functions of all proteins
within cells and organisms. Predicting Protein-Protein Interaction
(PPI) is one of the crucial and decisive problems in current research.
Genomic data offer a great opportunity and at the same time a lot of
challenges for the identification of these interactions. Many methods
have already been proposed in this regard. In case of in-silico
identification, most of the methods require both positive and negative
examples of protein interaction and the perfection of these examples
are very much crucial for the final prediction accuracy. Positive
examples are relatively easy to obtain from well known databases. But
the generation of negative examples is not a trivial task. Current PPI
identification methods generate negative examples based on some
assumptions, which are likely to affect their prediction accuracy.
Hence, if more reliable negative examples are used, the PPI prediction
methods may achieve even more accuracy. Focusing on this issue, a
graph based negative example generation method is proposed, which
is simple and more accurate than the existing approaches. An
interaction graph of the protein sequences is created. The basic
assumption is that the longer the shortest path between two
protein-sequences in the interaction graph, the less is the possibility of
their interaction. A well established PPI detection algorithm is
employed with our negative examples and in most cases it increases
the accuracy more than 10% in comparison with the negative pair
selection method in that paper.
Abstract: This paper presents a supervised clustering algorithm,
namely Grid-Based Supervised Clustering (GBSC), which is able to
identify clusters of any shapes and sizes without presuming any
canonical form for data distribution. The GBSC needs no prespecified
number of clusters, is insensitive to the order of the input
data objects, and is capable of handling outliers. Built on the
combination of grid-based clustering and density-based clustering,
under the assistance of the downward closure property of density
used in bottom-up subspace clustering, the GBSC can notably reduce
its search space to avoid the memory confinement situation during its
execution. On two-dimension synthetic datasets, the GBSC can
identify clusters with different shapes and sizes correctly. The GBSC
also outperforms other five supervised clustering algorithms when
the experiments are performed on some UCI datasets.