Abstract: This paper presents an exploration into the structure of the corporate governance network and interlocking directorates in the Czech Republic. First a literature overview and a basic terminology of the network theory is presented. Further in the text, statistics and other calculations relevant to corporate governance networks are presented. For this purpose an empirical data set consisting of 2 906 joint stock companies in the Czech Republic was examined. Industries with the highest average number of interlocks per company were healthcare, and energy and utilities. There is no observable link between the financial performance of the company and the number of its interlocks. Also interlocks with financial companies are very rare.
Abstract: Attempts to add fibre and polyphenols (PPs) into
popular beverages present challenges related to the properties of
finished products such as smoothies. Consumer acceptability,
viscosity and phenolic composition of smoothies containing high
levels of fruit fibre (2.5-7.5 g per 300 mL serve) and PPs (250-750
mg per 300 mL serve) were examined. The changes in total
extractable PP, vitamin C content, and colour of selected smoothies
over a storage stability trial (4°C, 14 days) were compared. A set of
acidic aqueous model beverages were prepared to further examine
the effect of two different heat treatments on the stability and
extractability of PPs. Results show that overall consumer
acceptability of high fibre and PP smoothies was low, with average
hedonic scores ranging from 3.9 to 6.4 (on a 1-9 scale). Flavour,
texture and overall acceptability decreased as fibre and polyphenol
contents increased, with fibre content exerting a stronger effect.
Higher fibre content resulted in greater viscosity, with an elevated PP
content increasing viscosity only slightly. The presence of fibre also
aided the stability and extractability of PPs after heating. A reduction
of extractable PPs, vitamin C content and colour intensity of
smoothies was observed after a 14-day storage period at 4°C. Two
heat treatments (75°C for 45 min or 85°C for 1 min) that are
normally used for beverage production, did not cause significant
reduction of total extracted PPs. It is clear that high levels of added
fibre and PPs greatly influence the consumer appeal of smoothies,
suggesting the need to develop novel formulation and processing
methods if a satisfactory functional beverage is to be developed
incorporating these ingredients.
Abstract: This paper examines the readability of the chairman’s narratives, as determined by the Flesch score, of a Malaysian public listed company’s corporate reports from 1962 to 2009. It partially supports earlier studies which demonstrated that corporate reports were difficult to read, and had shown very negligible decrease in difficulty over time. Net profit to sales and readability was significantly positively correlated but number of financial statements was significantly negatively correlated with readability.
Abstract: The role of entrepreneurs in generating the economy is
very important. Thus, nurturing entrepreneurship skills among
society is very crucial and should start from the early age. One of the
methods is to teach through game such as board game. Game
provides a fun and interactive platform for players to learn and play.
Besides that as today-s world is moving towards Islamic approach in
terms of finance, banking and entertainment but Islamic based game
is still hard to find in the market especially games on
entrepreneurship. Therefore, there is a gap in this segment that can be
filled by learning entrepreneurship through game. The objective of
this paper is to develop an entrepreneurship digital-based game
entitled “Catur Bistari" that is based on Islamic business approach.
Knowledge and skill of entrepreneurship and Islamic business
approach will be learned through the tasks that are incorporated
inside the game.
Abstract: The social force model which belongs to the
microscopic pedestrian studies has been considered as the supremacy
by many researchers and due to the main feature of reproducing the
self-organized phenomena resulted from pedestrian dynamic. The
Preferred Force which is a measurement of pedestrian-s motivation to
adapt his actual velocity to his desired velocity is an essential term on
which the model was set up. This Force has gone through stages of
development: first of all, Helbing and Molnar (1995) have modeled
the original force for the normal situation. Second, Helbing and his
co-workers (2000) have incorporated the panic situation into this
force by incorporating the panic parameter to account for the panic
situations. Third, Lakoba and Kaup (2005) have provided the
pedestrians some kind of intelligence by incorporating aspects of the
decision-making capability. In this paper, the authors analyze the
most important incorporations into the model regarding the preferred
force. They make comparisons between the different factors of these
incorporations. Furthermore, to enhance the decision-making ability
of the pedestrians, they introduce additional features such as the
familiarity factor to the preferred force to let it appear more
representative of what actually happens in reality.
Abstract: Delayed wound healing in diabetes is primarily
associated with hyperglycemia, over-expression of inflammatory
marker, oxidative stress and delayed collagen synthesis. This
unmanaged wound is producing high economic burden on the
society. Thus research is required to develop new and effective
treatment strategies to deal with this emerging issue. Our present
study incorporates the evaluation of wound healing effects of 50%
ethanol extract of Ocimum sanctum (OSE) in streptozotocin
(45mg/kg)-induced diabetic rats with concurrent wound ulcer. The
animals showing diabetes (Blood glucose level >140 and
Abstract: The paper presents the results of the European EIE
project “Realising the potential for small scale renewable energy
sources in the home – Kyotointhehome". The project's global aim is
to inform and educate teachers, students and their families so that
they can realise the need and can assess the potential for energy
efficiency (EE) measures and renewable energy sources (RES) in
their homes. The project resources were translated and trialled by 16
partners in 10 European countries.
A web-based methodology which will enable families to assess
how RES can be incorporated into energy efficient homes was
accomplished. The web application “KYOTOINHOME" will help
the citizens to identify what they can do to help their community
meet the Kyoto target for greenhouse gas reductions and prevent
global warming. This application provides useful information on how
the citizens can use renewable energy sources in their home to
provide space heating and cooling, hot water and electricity. A
methodology for assessing heat loss in a dwelling and application of
heat pump system was elaborated and will be implemented this year.
For schools, we developed a set of practical activities concerned with
preventing climate change through using renewable energy sources.
Complementary resources will also developed in the Romanian
research project “Romania Contribution to the European Targets
Regarding the Development of Renewable Energy Sources" -
PROMES.
Abstract: Gasoline Octane Number is the standard measure of
the anti-knock properties of a motor in platforming processes, that is
one of the important unit operations for oil refineries and can be
determined with online measurement or use CFR (Cooperative Fuel
Research) engines. Online measurements of the Octane number can
be done using direct octane number analyzers, that it is too
expensive, so we have to find feasible analyzer, like ANFIS
estimators.
ANFIS is the systems that neural network incorporated in fuzzy
systems, using data automatically by learning algorithms of NNs.
ANFIS constructs an input-output mapping based both on human
knowledge and on generated input-output data pairs.
In this research, 31 industrial data sets are used (21 data for training
and the rest of the data used for generalization). Results show that,
according to this simulation, hybrid method training algorithm in
ANFIS has good agreements between industrial data and simulated
results.
Abstract: Commercial nanocomposite food packaging type nano-silver containers were characterised using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). The presence of nanoparticles consistent with the incorporation of 1% nano-silver (Ag) and 0.1% titanium dioxide (TiO2) nanoparticle into polymeric materials formed into food containers was confirmed. Both nanomaterials used in this type of packaging appear to be embedded in a layered configuration within the bulk polymer. The dimensions of the incorporated nanoparticles were investigated using X-ray diffraction (XRD) and determined by calculation using the Scherrer Formula; these were consistent with Ag and TiO2 nanoparticles in the size range 20-70nm both were spherical shape nanoparticles. Antimicrobial assessment of the nanocomposite container has also been performed and the results confirm the antimicrobial activity of Ag and TiO2 nanoparticles in food packaging containers. Migration assessments were performed in a wide range of food matrices to determine the migration of nanoparticles from the packages. The analysis was based upon the relevant European safety Directives and involved the application of inductively coupled plasma mass spectrometry (ICP-MS) to identify the range of migration risk. The data pertain to insignificance levels of migration of Ag and TiO2 nanoparticles into the selected food matrices.
Abstract: In this study the effect of incorporation of recycled
glass-fibre reinforced polymer (GFRP) waste materials, obtained by
means of milling processes, on mechanical behaviour of polyester
polymer mortars was assessed. For this purpose, different contents of
recycled GFRP waste powder and fibres, with distinct size gradings,
were incorporated into polyester based mortars as sand aggregates
and filler replacements. Flexural and compressive loading capacities
were evaluated and found better than unmodified polymer mortars.
GFRP modified polyester based mortars also show a less brittle
behaviour, with retention of some loading capacity after peak load.
Obtained results highlight the high potential of recycled GFRP waste
materials as efficient and sustainable reinforcement and admixture for
polymer concrete and mortars composites, constituting an emergent
waste management solution.
Abstract: Sediment formation and its transport along the river course is considered as important hydraulic consideration in river engineering. Their impact on the morphology of rivers on one hand and important considerations of which in the design and construction of the hydraulic structures on the other has attracted the attention of experts in arid and semi-arid regions. Under certain conditions where the momentum energy of the flow stream reaches a specific rate, the sediment materials start to be transported with the flow. This can usually be analyzed in two different categories of suspended and bed load materials. Sedimentation phenomenon along the waterways and the conveyance of vast volume of materials into the canal networks can potentially influence water abstraction in the intake structures. This can pose a serious threat to operational sustainability and water delivery performance in the canal networks. The situation is serious where ineffective watershed management (poor vegetation cover in the water basin) is the underlying cause of soil erosion which feeds the materials into the waterways that intern would necessitate comprehensive study. The present paper aims to present an analytical investigation of the sediment process in the waterways on one hand and estimation of the sediment load transport into the lined canals using the SHARC software on the other. For this reason, the paper focuses on the comparative analysis of the hydraulic behaviors of the Sabilli main canal that feeds the pumping station with that of the Western canal in the Greater Dezful region to identify effective factors in sedimentation and ways of mitigating their impact on water abstraction in the canal systems. The method involved use of observational data available in the Dezful Dastmashoon hydrometric station along a 6 km waterway of the Sabilli main canal using the SHARC software to estimate the suspended load concentration and bed load materials. Results showed the transport of a significant volume of sediment loads from the waterways into the canal system which is assumed to have arisen from the absence of stilling basin on one hand and the gravity flow on the other has caused serious challenges. This is contrary to what occurs in the Sabilli canal, where the design feature which incorporates a settling basin just before the pumping station is the major cause of reduced sediment load transport into the canal system.Results showed that modification of the present design features by constructing a settling basin just upstream of the western intake structure can considerably reduce the entry of sediment materials into the canal system. Not only this can result in the sustainability of the hydraulic structures but can also improve operational performance of water conveyance and distribution system, all of which are the pre-requisite to secure reliable and equitable water delivery regime for the command area.
Abstract: Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.
Abstract: When choosing marketing strategies for international markets, one of the factors that should be considered is the cultural differences that exist among consumers in different countries. If the branding strategy has to be contextual and in tune with the culture, then the brand positioning variables has to interact, adapt and respond to the cultural variables in which the brand is operating. This study provides an overview of the relevance of culture in the development of an effective branding strategy in the international business environment. Hence, the main objective of this study is to provide a managerial framework for developing strategies for cross cultural brand management. The framework is useful because it incorporates the variables that are important in the competitiveness of fast food enterprises irrespective of their size. It provides practical, proactive and result oriented analysis that will help fast food firms augment their strategies in the international fast food markets. The proposed framework will enable managers understand the intricacies involved in branding in the global fast food industry and decrease the use of 'trial and error' when entering into unfamiliar markets.
Abstract: Intelligent systems based on machine learning
techniques, such as classification, clustering, are gaining wide spread
popularity in real world applications. This paper presents work on
developing a software system for predicting crop yield, for example
oil-palm yield, from climate and plantation data. At the core of our
system is a method for unsupervised partitioning of data for finding
spatio-temporal patterns in climate data using kernel methods which
offer strength to deal with complex data. This work gets inspiration
from the notion that a non-linear data transformation into some high
dimensional feature space increases the possibility of linear
separability of the patterns in the transformed space. Therefore, it
simplifies exploration of the associated structure in the data. Kernel
methods implicitly perform a non-linear mapping of the input data
into a high dimensional feature space by replacing the inner products
with an appropriate positive definite function. In this paper we
present a robust weighted kernel k-means algorithm incorporating
spatial constraints for clustering the data. The proposed algorithm
can effectively handle noise, outliers and auto-correlation in the
spatial data, for effective and efficient data analysis by exploring
patterns and structures in the data, and thus can be used for
predicting oil-palm yield by analyzing various factors affecting the
yield.
Abstract: Possible advantages of technology in educational
context required the defining boundaries of formal and informal
learning. Increasing opportunity to ubiquitous learning by
technological support has revealed a question of how to discover
the potential of individuals in the spontaneous environments such as
social networks. This seems to be related with the question of what
purposes in social networks have been being used? Social networks
provide various advantages in educational context as collaboration,
knowledge sharing, common interests, active participation and
reflective thinking. As a consequence of these, the purpose of this
study is composed of proposing a new model that could determine
factors which effect adoption of social network applications for usage
in educational context. While developing a model proposal, the
existing adoption and diffusion models have been reviewed and they
are thought to be suitable on handling an original perspective instead
of using completely other diffusion or acceptance models because of
different natures of education from other organizations. In the
proposed model; social factors, perceived ease of use, perceived
usefulness and innovativeness are determined four direct constructs
that effect adoption process. Facilitating conditions, image,
subjective norms and community identity are incorporated to model
as antecedents of these direct four constructs.
Abstract: pH-sensitive drug targeting using nanoparticles for
cancer chemotherapy have been spotlighted in recent decades. Graft
copolymer composed of poly (L-histidine) (PHS) and dextran
(DexPHS) was synthesized and pH-sensitive nanoparticles were
fabricated for pH-responsive drug delivery of doxorubicin (DOX).
Nanoparticles of DexPHS showed pH-sensitive changes in particle
sizes and drug release behavior, i.e. particle sizes and drug release rate
were increased at acidic pH, indicating that DexPHS nanoparticles
have pH-sensitive drug delivery potentials. Antitumor activity of
DOX-incorporated DexPHS nanoparticles were studied using CT26
colorectal carcinoma cells. Results indicated that fluorescence
intensity was higher at acidic pH than basic pH. These results
indicated that DexPHS nanoparticles have pH-responsive drug
targeting.
Abstract: Cognizant of the fact that enterprise systems involve
organizational change and their implementation is over shadowed by a
high failure rate, it is argued that there is the need to focus attention on
employees- perceptions of such organizational change when
explaining adoption behavior of enterprise systems. For this purpose,
the research incorporates a conceptual constructo fattitude toward
change that captures views about the need for organizational change.
Centered on this conceptual construct, the research model includes
beliefs regarding the system and behavioral intention as its
consequences, and the personal characteristics of organizational
commitment and perceived personal competence as its antecedents.
Structural equation analysis using LISREL provides significant
support for the proposed relationships. Theoretical and practical
implications are discussed along with limitations.
Abstract: Considering toxicity of heavy metals and their
accumulation in domestic wastes, immobilization of lead and
cadmium is envisaged inside glass-ceramics. We particularly
focused this work on calcium-rich phases embedded in a
glassy matrix.
Glass-ceramics were synthesized from glasses doped with
12 wt% and 16 wt% of PbO or CdO. They were observed and
analyzed by Electron MicroProbe Analysis (EMPA) and
Analytical Scanning Electron Microscopy (ASEM). Structural
characterization of the samples was performed by powder XRay
Diffraction.
Diopside crystals of CaMgSi2O6 composition are shown to
incorporate significant amounts of cadmium (up to 9 wt% of
CdO). Two new crystalline phases are observed with very
high Cd or Pb contents: about 40 wt% CdO for the cadmiumrich
phase and near 60 wt% PbO for the lead-rich phase. We
present complete chemical and structural characterization of
these phases. They represent a promising way for the
immobilization of toxic elements like Cd or Pb since glass
ceramics are known to propose a “double barrier" protection
(metal-rich crystals embedded in a glass matrix) against metal
release in the environment.
Abstract: While the form of crises may change, their essence
remains the same (such as a cycle of abundant liquidity, rapid credit
growth, and a low-inflation environment followed by an asset-price
bubble). The current market turbulence began in mid-2000s when the
US economy shifted to imbalanced both internal and external
macroeconomic positions. We see two key causes of these problems
– loose US monetary policy in early 2000s and US government
guarantees issued on the securities by government-sponsored
enterprises what was further fueled by financial innovations such as
structured credit products. We have discovered both negative and
positive lessons deriving from this crisis and divided the negative
lessons into three groups: financial products and valuation, processes
and business models, and strategic issues. Moreover, we address key
risk management lessons and exit strategies derived from the current
crisis and recommend policies that should help diminish the negative
impact of future potential crises.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.