Abstract: In this paper a comprehensive review on various
factory layouts has been carried out for designing a lucrative process
layout for medium scale industries. Industry data base reveals that the
end product rejection rate is on the order of 10% amounting large
profit loss. In order to avoid these rejection rates and to increase the
quality product production an intermediate non-destructive testing
facility (INDTF) has been recommended for increasing the overall
profit. We observed through detailed case studies that while
introducing INDTF to medium scale industries the expensive
production process can be avoided to the defective products well
before its final shape. Additionally, the defective products identified
during the intermediate stage can be effectively utilized for other
applications or recycling; thereby the overall wastage of the raw
materials can be reduced and profit can be increased. We concluded
that the prudent design of a factory layout through critical path
method facilitating with INDTF will warrant profitable outcome.
Abstract: Adapting quickly to environmental dynamism is
essential for an organization to develop outsourcing strategic and
management in order to sustain competitive advantage. This research
used the Partial Least Squares Structural Equation Modeling (PLSSEM)
tool to investigate the factors of environmental dynamism
impact on the strategic outsourcing success among electrical and
electronic manufacturing industries in outsourcing management.
Statistical results confirm that the inclusion of customer demand,
technological change, and competition level as a new combination
concept of environmental dynamism, has positive effects on
outsourcing success. Additionally, this research demonstrates the
acceptability of PLS-SEM as a statistical analysis to furnish a better
understanding of environmental dynamism in outsourcing
management in Malaysia. A practical finding contributes to
academics and practitioners in the field of outsourcing management.
Abstract: In this paper, Least Mean Square (LMS) adaptive
noise reduction algorithm is proposed to enhance the speech signal
from the noisy speech. In this, the speech signal is enhanced by
varying the step size as the function of the input signal. Objective and
subjective measures are made under various noises for the proposed
and existing algorithms. From the experimental results, it is seen that
the proposed LMS adaptive noise reduction algorithm reduces Mean
square Error (MSE) and Log Spectral Distance (LSD) as compared to
that of the earlier methods under various noise conditions with
different input SNR levels. In addition, the proposed algorithm
increases the Peak Signal to Noise Ratio (PSNR) and Segmental SNR
improvement (ΔSNRseg) values; improves the Mean Opinion Score
(MOS) as compared to that of the various existing LMS adaptive
noise reduction algorithms. From these experimental results, it is
observed that the proposed LMS adaptive noise reduction algorithm
reduces the speech distortion and residual noise as compared to that
of the existing methods.
Abstract: Enterprise Architecture (EA) is a strategy that is
employed by enterprises in order to align their business and
Information Technology (IT). EA is managed, developed, and
maintained through Enterprise Architecture Implementation
Methodology (EAIM). Effectiveness of EA implementation is the
degree in which EA helps to achieve the collective goals of the
organization. This paper analyzes the results of a survey that aims to
explore the factors that affect the effectiveness of EAIM and
specifically the relationship between factors and effectiveness of the
output and functionality of EA project. The exploratory factor
analysis highlights a specific set of five factors: alignment,
adaptiveness, support, binding, and innovation. The regression
analysis shows that there is a statistically significant and positive
relationship between each of the five factors and the effectiveness of
EAIM. Consistent with theory and practice, the most prominent
factor for developing an effective EAIM is innovation. The findings
contribute to the measuring the effectiveness of EA implementation
project by providing an indication of the measurement
implementation approaches which is used by the Enterprise
Architects, and developing an effective EAIM.
Abstract: Sports games conducted as a group are a form of
therapeutic exercise for aged people with decreased strength and for
people suffering from permanent damage of stroke and other
conditions. However, it is difficult for patients with different athletic
abilities to play a game on an equal footing. This study specifically
examines a computer video game designed for therapeutic exercise,
and a game system with support given depending on athletic ability.
Thereby, anyone playing the game can participate equally. This
video-game, to be specific, is a popular variant of balloon volleyball,
in which players hit a balloon by hand before it falls to the floor. In this
game system, each player plays the game watching a monitor on which
the system displays tailor-made video-game images adjusted to the
person’s athletic ability, providing players with player-adaptive assist
support. We have developed a multiplayer game system with an image
generation technique for the tailor-made video-game and conducted
tests to evaluate it.
Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: The Lean Environmental Management Integration
System (LEMIS) framework development is integration between lean
core element and ISO 14001. The curiosity on the relationship
between continuous improvement and sustainability of lean
implementation has influenced this study toward LEMIS.
Characteristic of ISO 14001 standard clauses and core elements of
lean principles are explored from past studies and literature reviews.
Survey was carried out on ISO 14001 certified companies to examine
continual improvement by implementing the ISO 14001 standard.
The study found that there is a significant and positive relationship
between Lean Principles: value, value stream, flow, pull and
perfection with the ISO 14001 requirements. LEMIS is significant to
support the continuous improvement and sustainability. The
integration system can be implemented to any manufacturing
company. It gives awareness on the importance on why organizations
need to sustain its environmental management system. In the
meantime, the lean principle can be adapted in order to streamline
daily activities of the company. Throughout the study, it had proven
that there is no sacrifice or trade-off between lean principles with ISO
14001 requirements. The framework developed in the study can be
further simplified in the future, especially the method of crossing
each sub requirements of ISO 14001 standard with the core elements
of Lean principles in this study.
Abstract: This paper proposes the designing direct adaptive
neural controller to apply for a class of a nonlinear pendulum
dynamic system. The radial basis function (RBF) neural adaptive
controller is robust in presence of external and internal uncertainties.
Both the effectiveness of the controller and robustness against
disturbances are importance of this paper. The simulation results
show the promising performance of the proposed controller.
Abstract: Artificial Immune Systems (AIS), inspired by the
human immune system, are algorithms and mechanisms which are
self-adaptive and self-learning classifiers capable of recognizing and
classifying by learning, long-term memory and association. Unlike
other human system inspired techniques like genetic algorithms and
neural networks, AIS includes a range of algorithms modeling on
different immune mechanism of the body. In this paper, a mechanism
of a human immune system based on apoptosis is adopted to build an
Intrusion Detection System (IDS) to protect computer networks.
Features are selected from network traffic using Fisher Score. Based
on the selected features, the record/connection is classified as either
an attack or normal traffic by the proposed methodology. Simulation
results demonstrates that the proposed AIS based on apoptosis
performs better than existing AIS for intrusion detection.
Abstract: In today’s era, it is no news that organizations should
demonstrate honest conduct as well as ethical administration.
Therefore, the concept of corporate social responsibility
(subsequently CSR) has created its tag upon the company’s focal
point as well as marketing communications, and will continue in the
future. The importance of CSR has increased in the last decade, and
this concept has attracted global attention. The notion of CSR has
strategic significance for many organizations. However, businesses
are not adapting the activities of CSR that benefit to all of its
stakeholders (including society). The main reason is the practitioners
are unfortunately unable to comprehend its importance; and
therefore, the activities of the CSR are so detached from the business
activities. Hence, it is required to develop an understanding that the
activities of CSR are not only beneficial for the society but it also
benefit to business. This paper focuses on the concept of strategic
CSR, and develops a theoretical framework that will help
practitioners to filter and chose the activities of CSR that are strategic
in nature.
Abstract: The objective of this study was to determine effect of
dietary essential oil (EO) compounds, which contained
cinnamaldehyde, eugenol, peppermint, coriander, cumin, lemongrass,
and an organic carrier on feed intake, milk composition, and rumen
fermentation of dairy cows during heat exposure. Thirty-two Holstein
cows (days in milk= 60 ± 5) were assigned to one of two treatment
groups: a Control and EO fed. The experiment lasted 28 days. Dry
matter intake (DMI) was measured daily while and milk production
was measured weekly. Our result showed that DMI and milk yield
was decreased (P < 0.01) in control cows relative to EO cows.
Furthermore, supplementation with EO was associated with a
decrease in the molar proportion of propionate (P < 0.05) and
increase (P < 0.05) in acetate to propionate ratio. In conclusion, EO
supplementations in diets can be useful nutritional modification to
alleviate for the decrease DMI and milk production during heat
exposure in lactating dairy cows.
Abstract: The purpose of this study was to investigate
perceptions of climate change risk to forest ecosystems and forestbased
communities as well as perceived effectiveness of adaptation
strategies for climate change as well as challenges for adaptation.
Data was gathered using a pre-tested semi-structured questionnaire.
Simple random selection technique was applied. For the majority of
issues, the responses were obtained on multi-point likert scales, and
the scores provided were, in turn, used to estimate the means and
other useful estimates. A composite knowledge index developed
using correct responses to a set of self-rated statements were used to
evaluate the issues. The mean of the knowledge index was 0.64. Also
all respondents recorded values of the knowledge index above 0.25.
Increase forest fire was perceived by respondents as the greatest risk
to forest eco-system. Decrease access to water supplies was perceived
as the greatest risk to livelihoods of forest based communities. The
most effective adaptation strategy relevant to climate change risks to
forest eco-systems and forest based communities livelihoods in
Kathmandu valley in Nepal as perceived by the respondents was
reforestation and afforestation. As well, lack of public awareness was
perceived as the major limitation for climate change adaptation.
However, perceived risks as well as effective adaptation strategies
showed an inconsistent association with knowledge indicators and
social-cultural variables. The results provide useful information to
any party who involve with climate change issues in Nepal, since
such attempts would be more effective once the people’s perceptions
on these aspects are taken into account.
Abstract: Inland Waterway Transportation (IWT) is playing an
important role in national transport systems, water transportation is
considered to be safe, energy efficient and environmentally friendly
mode of transport, all benefits of IWT cause national awareness
increase, for instance the Colombian government is planning to
restore the navigability of the most important river of the country, the
Magdalena’s River navigability, embrace waterway transportation in
Colombia could strength competitiveness while reduce most of the
transport externalities. However, the current situation of the
Magdalena is deplorable, the most important river of Colombia has
been abandoned for decades and the solution is beyond of a single
administrative entity. This paper analyzes the outcomes of the
Navigation And Inland Waterway Action and Development in
Europe program (NAIADES) as a prospective to develop a similar
program in Colombia with similar objectives and guidelines,
considering sustainability, guarantying the long-term future results
and adaptability of the program. Identifying stakeholders and policy
experts, a set of individual interviews were carried out; findings
support the idea of lack of integration within governmental
institutions and lack of importance in marketing promotion as
possible drawbacks on the implementation of IWT projects.
Abstract: The bean (Phaseolus vulgaris L.) is one of the best
known of the legumes, and it has a long cultivation tradition in Italy.
The territory of “Subappennino Dauno” (southern Italy) is at around
700 m a.s.l. and is predominantly grown with cereals, olive trees and
grapevines. Ecotypes of white beans to eat dry (such as cannellini
beans) are also grown, which are sought for their palatability, high
digestibility, and ease of cooking. However, these are not easy to find
on the market due to their low production in relatively small areas
and on small family farms that use seeds handed down from
generation to generation. The introduction of these ecotypes in plain
areas of the Puglia region would provide an opportunity to promote
the diffusion of this type of bean. To investigate the adaptability of
these ecotypes in plain environments (Cerignola, in southern Italy) a
comparative trial was carried out between three ‘Monti Dauni’
ecotypes (E1, E2, E3) that are native to mountain areas and the
similar commercial variety, ‘Cannellini’. The data provide useful
information about the quantitative and qualitative characteristics of
these ecotypes when grown in lowland environments. Ecotype E3
provided the greatest bean production (2.34 t ha-1) compared to
‘Cannellini’ (1.28 t ha-1) and the other ecotypes (0.55 and 0.40 t ha-1,
for E1 and E2, respectively), due to its greater plant growth and the
larger size of the seed (and thickness, in particular). Finally, ecotype
E2 provided the greatest protein content (31.2%), although not
significantly different from the commercial cultivar ‘Cannellini’
(32.1%).
Abstract: This study is purposed to develop an efficient fault
detection method for Global Navigation Satellite Systems (GNSS)
applications based on adaptive noise covariance estimation. Due to the
dependence on radio frequency signals, GNSS measurements are
dominated by systematic errors in receiver’s operating environment.
In the proposed method, the pseudorange and carrier-phase
measurement noise covariances are obtained at time propagations and
measurement updates in process of Carrier-Smoothed Code (CSC)
filtering, respectively. The test statistics for fault detection are
generated by the estimated measurement noise covariances. To
evaluate the fault detection capability, intentional faults were added to
the filed-collected measurements. The experiment result shows that
the proposed method is efficient in detecting unhealthy measurements
and improves GNSS positioning accuracy against fault occurrences.
Abstract: Apps are today the most important possibility to adapt
mobile phones and computers to fulfill the special needs of their
users. Location- and context-sensitive programs are hereby the key to
support the interaction of the user with his/her environment and also
to avoid an overload with a plenty of dispensable information. The
contribution shows, how a trusted, secure and really bi-directional
communication and interaction among users and their environment
can be established and used, e.g. in the field of home automation.
Abstract: The main goal of this paper was evaluate the effect of
diets containing different levels of probiotic on performance and milk
composition of lactating cows.
Eight Holstein cows were distributed in two 4x4 Latin square. The
diets were based on corn silage, concentrate and the treatment (0, 3, 6
or 9 grams of probiotic/animal/day). It was evaluated the dry matter
intake of nutrients, milk yield and composition.
The use of probiotics did not affect the nutrient intake (p>0.05)
neither the daily milk production or corrected to 4% fat (p>0.05).
However, it was observed that there was a significant fall in milk
composition with higher levels of probiotics supplementation.
These results emphasize the need of further studies with different
experimental designs or improve the number of Latin square with
longer periods of adaptation.
Abstract: The North-eastern part of India, which receives
heavier rainfall than other parts of the subcontinent, is of great
concern now-a-days with regard to climate change. High intensity
rainfall for short duration and longer dry spell, occurring due to
impact of climate change, affects river morphology too. In the present
study, an attempt is made to delineate the North-eastern region of
India into some homogeneous clusters based on the Fuzzy Clustering
concept and to compare the resulting clusters obtained by using
conventional methods and nonconventional methods of clustering.
The concept of clustering is adapted in view of the fact that, impact
of climate change can be studied in a homogeneous region without
much variation, which can be helpful in studies related to water
resources planning and management. 10 IMD (Indian Meteorological
Department) stations, situated in various regions of the North-east,
have been selected for making the clusters. The results of the Fuzzy
C-Means (FCM) analysis show different clustering patterns for
different conditions. From the analysis and comparison it can be
concluded that nonconventional method of using GCM data is
somehow giving better results than the others. However, further
analysis can be done by taking daily data instead of monthly means to
reduce the effect of standardization.
Abstract: This paper explores the effects of gamification on
lower secondary school students’ motivation and engagement in the
classroom. Two-group posttest-only experimental design were
employed to study the influence of gamification teaching method
(GTM) when compared with conventional teaching method (CTM)
on 60 lower secondary school students. The Student Engagement
Instrument (SEI) and Intrinsic Motivation Inventory (IMI) were used
to assess students’ intrinsic motivation and engagement level towards
the respective teaching method. Finding indicates that students who
completed the GTM lesson were significantly higher in intrinsic
motivation to learn than those from the CTM. Although the result
were insignificant and only marginal difference in the engagement
mean, GTM still show better potential in raising student’s
engagement in class when compared with CTM. This finding proves
that the GTM is likely to solve the current issue of low motivation to
learn and low engagement in class among lower secondary school
students in Malaysia. On the other hand, despite being not significant,
higher mean indicates that CTM positively contribute to higher peer
support for learning and better teacher and student relationship when
compared with GTM. As a conclusion, gamification approach is
flexible and can be adapted into many learning content to enhance the
intrinsic motivation to learn and to some extent, encourage better
student engagement in class.
Abstract: The systematic evaluation of manufacturing
technologies with regard to the potential for product designing
constitutes a major challenge. Until now, conventional evaluation
methods primarily consider the costs of manufacturing technologies.
Thus, the potential of manufacturing technologies for achieving
additional product design features is not completely captured. To
compensate this deficit, final evaluations of new technologies are
mainly intuitive in practice. Therefore, an additional evaluation
dimension is needed which takes the potential of manufacturing
technologies for specific realizable product designs into account. In
this paper, we present the approach of an evaluation method for
selecting manufacturing technologies with regard to their potential
for product designing. This research is done within the Fraunhofer
innovation cluster »AdaM« (Adaptive Manufacturing) which targets
the development of resource efficient and adaptive manufacturing
technology processes for complex turbomachinery components.