Abstract: This paper provides a framework in order to
incorporate reliability issue as a sign of disruption in distribution
systems and partial covering theory as a response to limitation in
coverage radios and economical preferences, simultaneously into the
traditional literatures of capacitated facility location problems. As a
result we develop a bi-objective model based on the discrete
scenarios for expected cost minimization and demands coverage
maximization through a three echelon supply chain network by
facilitating multi-capacity levels for provider side layers and
imposing gradual coverage function for distribution centers (DCs).
Additionally, in spite of objectives aggregation for solving the model
through LINGO software, a branch of LP-Metric method called Min-
Max approach is proposed and different aspects of corresponds
model will be explored.
Abstract: This research simulates one of the natural phenomena,
the ocean wave. Our goal is to be able to simulate the ocean wave at
real-time rate with the water surface interacting with objects. The
wave in this research is calm and smooth caused by the force of the
wind above the ocean surface. In order to make the simulation of the
wave real-time, the implementation of the GPU and the
multithreading techniques are used here. Based on the fact that the
new generation CPUs, for personal computers, have multi cores, they
are useful for the multithread. This technique utilizes more than one
core at a time. This simulation is programmed by C language with
OpenGL. To make the simulation of the wave look more realistic, we
applied an OpenGL technique called cube mapping (environmental
mapping) to make water surface reflective and more realistic.
Abstract: The paper contains a review of the literature in terms of the critical analysis of methodologies of university ranking systems. Furthermore, the initiatives supported by the European Commission (U-Map, U-Multirank) and CHE Ranking are described. Special attention is paid to the tendencies in the development of ranking systems. According to the author, the ranking organizations should abandon the classic form of ranking, namely a hierarchical ordering of universities from “the best" to “the worse". In the empirical part of this paper, using one of the method of cluster analysis called k-means clustering, the author presents university classifications of the top universities from the Shanghai Jiao Tong University-s (SJTU) Academic Ranking of World Universities (ARWU).
Abstract: This paper proposes a method that discovers time series event patterns from textual data with time information. The patterns are composed of sequences of events and each event is extracted from the textual data, where an event is characteristic content included in the textual data such as a company name, an action, and an impression of a customer. The method introduces 7 types of time constraints based on the analysis of the textual data. The method also evaluates these constraints when the frequency of a time series event pattern is calculated. We can flexibly define the time constraints for interesting combinations of events and can discover valid time series event patterns which satisfy these conditions. The paper applies the method to daily business reports collected by a sales force automation system and verifies its effectiveness through numerical experiments.
Abstract: In this paper, we use an M/G/C/C state dependent
queuing model within a complex network topology to determine the
different performance measures for pedestrian traffic flow. The
occupants in this network topology need to go through some source
corridors, from which they can choose their suitable exiting
corridors. The performance measures were calculated using arrival
rates that maximize the throughputs of source corridors. In order to
increase the throughput of the network, the result indicates that the
flow direction of pedestrian through the corridors has to be restricted
and the arrival rates to the source corridor need to be controlled.
Abstract: This study proposes a novel recommender system to
provide the advertisements of context-aware services. Our proposed
model is designed to apply a modified collaborative filtering (CF)
algorithm with regard to the several dimensions for the personalization
of mobile devices – location, time and the user-s needs type. In
particular, we employ a classification rule to understand user-s needs
type using a decision tree algorithm. In addition, we collect primary
data from the mobile phone users and apply them to the proposed
model to validate its effectiveness. Experimental results show that the
proposed system makes more accurate and satisfactory advertisements
than comparative systems.
Abstract: Service quality has become a centerpiece for airline companies in vying with one another and keeps their image in the minds of passengers. Many airlines have pushed service quality through service personalization which includes both ground and on board especially from the viewpoint of retaining satisfied passengers and attracting new ones. Besides those, in-flight meals/food service is another important aspect of the airline operation. The in flight meals/food services now are seen as part of marketing strategies in attracting business or leisure travelers. This study reports the outcomes of the investigation on in-flight meals/food attributes toward passengers- level of satisfaction and re-flying intention. Taste, freshness, appearance of in-flight meals/food served and menu choices are important to the airlines passengers especially for the long haul flight. Food not only contributes to the prediction of the airline passengers- levels of satisfaction but besides other factors slightly influence passengers- re- flying intention. Airline companies therefore should not ignore this element but take the opportunity to create more attractive and acceptable in-flight meals/food along with other matter as marketing tools in attracting passengers to re-flying with them.
Abstract: High employee turnover rate in Malaysia-s retail industry has become a major issue that needs to be addressed. This study determines the levels of job satisfaction, organizational commitment, and turnover intention of employees in a retail company in Malaysia. The relationships between job satisfaction and organizational commitment on turnover intention are also investigated. A questionnaire was developed using Job Descriptive Index, Organizational Commitment Questionnaire, and Lee and Mowday-s turnover intention items and data were collected from 62 respondents. The findings suggested that the respondents were moderately satisfied with job satisfaction facets such as promotion, work itself, co-workers, and supervisors but were unsatisfied with salary. They also had moderate commitment level with considerably high intention to leave the organization. All satisfaction facets (except for co-workers) and organizational commitment were significantly and negatively related to turnover intention. Based on the findings, retention strategies of retail employees were proposed.
Abstract: Elastic boundary eigensolution problems are converted
into boundary integral equations by potential theory. The kernels of
the boundary integral equations have both the logarithmic and Hilbert
singularity simultaneously. We present the mechanical quadrature
methods for solving eigensolutions of the boundary integral equations
by dealing with two kinds of singularities at the same time. The methods
possess high accuracy O(h3) and low computing complexity. The
convergence and stability are proved based on Anselone-s collective
compact theory. Bases on the asymptotic error expansion with odd
powers, we can greatly improve the accuracy of the approximation,
and also derive a posteriori error estimate which can be used for
constructing self-adaptive algorithms. The efficiency of the algorithms
are illustrated by numerical examples.
Abstract: This paper proposes a new of cloud computing for individual computer users to share applications in distributed communities, called community-based personal cloud computing (CPCC). The paper also presents a prototype design and implementation of CPCC. The users of CPCC are able to share their computing applications with other users of the community. Any member of the community is able to execute remote applications shared by other members. The remote applications behave in the same way as their local counterparts, allowing the user to enter input, receive output as well as providing the access to the local data of the user. CPCC provides a peer-to-peer (P2P) environment where each peer provides applications which can be used by the other peers that are connected CPCC.
Abstract: In this paper we introduce a novel method for
the characterization of synchronziation and coupling effects
in multivariate time series that can be used for the analysis
of EEG or ECoG signals recorded during epileptic seizures.
The method allows to visualize the spatio-temporal evolution
of synchronization and coupling effects that are characteristic
for epileptic seizures. Similar to other methods proposed for
this purpose our method is based on a regression analysis.
However, a more general definition of the regression together
with an effective channel selection procedure allows to use the
method even for time series that are highly correlated, which
is commonly the case in EEG/ECoG recordings with large
numbers of electrodes. The method was experimentally tested
on ECoG recordings of epileptic seizures from patients with
temporal lobe epilepsies. A comparision with the results from
a independent visual inspection by clinical experts showed
an excellent agreement with the patterns obtained with the
proposed method.
Abstract: A sequential decision problem, based on the task ofidentifying the species of trees given acoustic echo data collectedfrom them, is considered with well-known stochastic classifiers,including single and mixture Gaussian models. Echoes are processedwith a preprocessing stage based on a model of mammalian cochlearfiltering, using a new discrete low-pass filter characteristic. Stoppingtime performance of the sequential decision process is evaluated andcompared. It is observed that the new low pass filter processingresults in faster sequential decisions.
Abstract: Vernonia divergens Benth., commonly known as
“Insulin Plant” (Fam: Asteraceae) is a potent sugar killer. Locally the
leaves of the plant, boiled in water are successfully administered to a
large number of diabetic patients. The present study evaluates the
putative anti-diabetic ingredients, isolated from the in vivo and in
vitro grown plantlets of V. divergens for their antimicrobial and
anticancer activities. Sterilized explants of nodal segments were
cultured on MS (Musashige and Skoog, 1962) medium in presence of
different combinations of hormones. Multiple shoots along with
bunch of roots were regenerated at 1mg l-1 BAP and 0.5 mg l-1 NAA.
Micro-plantlets were separated and sub-cultured on the double
strength (2X) of the above combination of hormones leading to
increased length of roots and shoots. These plantlets were
successfully transferred to soil and survived well in nature. The
ethanol extract of plantlets from both in vivo & in vitro sources were
prepared in soxhlet extractor and then concentrated to dryness under
reduced pressure in rotary evaporator. Thus obtainedconcentrated
extracts showed significant inhibitory activity against gram
negative bacteria like Escherichia coli and Pseudomonas
aeruginosa but no inhibition was found against gram positive
bacteria. Further, these ethanol extracts were screened for in vitro
percentage cytotoxicity at different time periods (24 h, 48 h and 72 h)
of different dilutions. The in vivo plant extract inhibited the growth of
EAC mouse cell lines in the range of 65, 66, 78, and 88% at 100, 50,
25 & 12.5μg mL-1 but at 72 h of treatment. In case of the extract of in
vitro origin, the inhibition was found against EAC cell lines even at
48h. During spectrophotometric scanning, the extracts exhibited
different maxima (ʎ) - four peaks in in vitro extracts as against single
in in vivo preparation suggesting the possible change in the nature of
ingredients during micropropagation through tissue culture
techniques.
Abstract: In order to make conventional implicit algorithm to be applicable in large scale parallel computers , an interface prediction and correction of discontinuous finite element method is presented to solve time-dependent neutron transport equations under 2-D cylindrical geometry. Domain decomposition is adopted in the computational domain.The numerical experiments show that our parallel algorithm with explicit prediction and implicit correction has good precision, parallelism and simplicity. Especially, it can reach perfect speedup even on hundreds of processors for large-scale problems.
Abstract: Cooperative organizations in Malaysia are going
through a phase of rapid growth. They are seen by the government as
another crucial vehicle to drive and boost up the country-s
economical development and growth. Hence, the issue of cooperative
governance is of great importance. Unlike literatures on corporate
governance for public listed companies-, literatures on governance
for social enterprises, in particular the cooperative organizations are
still at the early stage in Malaysia and very scant in number. This
paper will look into current practices as well as issues and challenges
related to cooperative governance. The need for a better solution
towards forming best practices of cooperative governance framework
appears imperative in deterring cases of mismanagement and fraud.
Abstract: Energy dissipation in drops has been investigated by
physical models. After determination of effective parameters on the
phenomenon, three drops with different heights have been
constructed from Plexiglas. They have been installed in two existing
flumes in the hydraulic laboratory. Several runs of physical models
have been undertaken to measured required parameters for
determination of the energy dissipation. Results showed that the
energy dissipation in drops depend on the drop height and discharge.
Predicted relative energy dissipations varied from 10.0% to 94.3%.
This work has also indicated that the energy loss at drop is mainly
due to the mixing of the jet with the pool behind the jet that causes
air bubble entrainment in the flow. Statistical model has been
developed to predict the energy dissipation in vertical drops denotes
nonlinear correlation between effective parameters. Further an
artificial neural networks (ANNs) approach was used in this paper to
develop an explicit procedure for calculating energy loss at drops
using NeuroSolutions. Trained network was able to predict the
response with R2 and RMSE 0.977 and 0.0085 respectively. The
performance of ANN was found effective when compared to
regression equations in predicting the energy loss.
Abstract: This paper analyses the unsteady, two-dimensional
stagnation point flow of an incompressible viscous fluid over a flat
sheet when the flow is started impulsively from rest and at the same
time, the sheet is suddenly stretched in its own plane with a velocity
proportional to the distance from the stagnation point. The partial
differential equations governing the laminar boundary layer forced
convection flow are non-dimensionalised using semi-similar
transformations and then solved numerically using an implicit finitedifference
scheme known as the Keller-box method. Results
pertaining to the flow and heat transfer characteristics are computed
for all dimensionless time, uniformly valid in the whole spatial region
without any numerical difficulties. Analytical solutions are also
obtained for both small and large times, respectively representing the
initial unsteady and final steady state flow and heat transfer.
Numerical results indicate that the velocity ratio parameter is found
to have a significant effect on skin friction and heat transfer rate at
the surface. Furthermore, it is exposed that there is a smooth
transition from the initial unsteady state flow (small time solution) to
the final steady state (large time solution).
Abstract: In this article, we present a web server based solution
for implementing a system for intelligent navigation. In this solution
we use real time collected data and traffic history to establish the best
route for navigation. This is a low cost solution that is easily to
implement and extend. There is no need any infrastructure at road
network level except only a device that collect data about traffic in
key road crossing. The presented solution creates a strong base for
traffic pursuit and offers an infrastructure for navigation applications.
Abstract: In this work, I present a review on Sparse Distributed
Memory for Small Cues (SDMSCue), a variant of Sparse Distributed
Memory (SDM) that is capable of handling small cues. I then conduct
and show some cognitive experiments on SDMSCue to test its
cognitive soundness compared to SDM. Small cues refer to input
cues that are presented to memory for reading associations; but have
many missing parts or fields from them. The original SDM failed to
handle such a problem. SDMSCue handles and overcomes this
pitfall. The main idea in SDMSCue; is the repeated projection of the
semantic space on smaller subspaces; that are selected based on the
input cue length and pattern. This process allows for Read/Write
operations using an input cue that is missing a large portion.
SDMSCue is augmented with the use of genetic algorithms for
memory allocation and initialization. I claim that SDM functionality
is a subset of SDMSCue functionality.
Abstract: In a none-super-competitive environment the concepts
of closed system, management control remains to be the dominant
guiding concept to management. The merits of closed loop have been
the sources of most of the management literature and culture for
many decades. It is a useful exercise to investigate and poke into the
dynamics of the control loop phenomenon and draws some lessons to
use for refining the practice of management. This paper examines the
multitude of lessons abstracted from the behavior of the Input /output
/feedback control loop model, which is the core of control theory.
There are numerous lessons that can be learned from the insights this
model would provide and how it parallels the management dynamics
of the organization. It is assumed that an organization is basically a
living system that interacts with the internal and external variables. A
viable control loop is the one that reacts to the variation in the
environment and provide or exert a corrective action. In managing
organizations this is reflected in organizational structure and
management control practices. This paper will report findings that
were a result of examining several abstract scenarios that are
exhibited in the design, operation, and dynamics of the control loop
and how they are projected on the functioning of the organization.
Valuable lessons are drawn in trying to find parallels and new
paradigms, and how the control theory science is reflected in the
design of the organizational structure and management practices. The
paper is structured in a logical and perceptive format. Further
research is needed to extend these findings.