Abstract: Supply chain networks are frequently hit by
unplanned events which lead to disruptions and cause operational and
financial consequences. It is neither possible to avoid disruption risk
entirely, nor are network members able to prepare for every possible
disruptive event. Therefore a continuity planning should be set up
which supports effective operational responses in supply chain
networks in times of emergencies. In this research network related
degrees of freedom which determine the options for responsive
actions are derived from interview data. The findings are further
embedded into a common risk management process. The paper
provides support for researchers and practitioners to identify the
network related options for responsive actions and to determine the
need for improving the reaction capabilities.
Abstract: In most of the cases, natural disasters lead to the
necessity of evacuating people. The quality of evacuation
management is dramatically improved by the use of information
provided by decision support systems, which become indispensable
in case of large scale evacuation operations. This paper presents a
best practice case study. In November 2007, officers from the
Emergency Situations Inspectorate “Crisana" of Bihor County from
Romania participated to a cross-border evacuation exercise, when
700 people have been evacuated from Netherlands to Belgium. One
of the main objectives of the exercise was the test of four different
decision support systems. Afterwards, based on that experience,
software system called TEVAC (Trans Border Evacuation) has been
developed “in house" by the experts of this institution. This original
software system was successfully tested in September 2008, during
the deployment of the international exercise EU-HUROMEX 2008,
the scenario involving real evacuation of 200 persons from Hungary
to Romania. Based on the lessons learned and results, starting from
April 2009, the TEVAC software is used by all Emergency
Situations Inspectorates all over Romania.
Abstract: A transient finite element model has been developed
to study the heat transfer and fluid flow during spot Gas Tungsten
Arc Welding (GTAW) on stainless steel. Temperature field, fluid
velocity and electromagnetic fields are computed inside the cathode,
arc-plasma and anode using a unified MHD formulation. The
developed model is then used to study the influence of different
helium-argon gas mixtures on both the energy transferred to the
workpiece and the time evolution of the weld pool dimensions. It is
found that the addition of helium to argon increases the heat flux
density on the weld axis by a factor that can reach 6.5. This induces
an increase in the weld pool depth by a factor of 3. It is also found
that the addition of only 10% of argon to helium decreases
considerably the weld pool depth, which is due to the electrical
conductivity of the mixture that increases significantly when argon is
added to helium.
Abstract: TUSAT is a prospective Turkish
Communication Satellite designed for providing mainly data
communication and broadcasting services through Ku-Band
and C-Band channels. Thermal control is a vital issue in
satellite design process. Therefore, all satellite subsystems and
equipments should be maintained in the desired temperature
range from launch to end of maneuvering life. The main
function of the thermal control is to keep the equipments and
the satellite structures in a given temperature range for various
phases and operating modes of spacecraft during its lifetime.
This paper describes the thermal control design which uses
passive and active thermal control concepts. The active
thermal control is based on heaters regulated by software via
thermistors. Alternatively passive thermal control composes of
heat pipes, multilayer insulation (MLI) blankets, radiators,
paints and surface finishes maintaining temperature level of
the overall carrier components within an acceptable value.
Thermal control design is supported by thermal analysis using
thermal mathematical models (TMM).
Abstract: Chemical detection is still a continuous challenge when
it comes to designing single-walled carbon nanotube (SWCNT)
sensors with high selectivity, especially in complex chemical
environments. A perfect example of such an environment would be in
thermally oxidized soybean oil. At elevated temperatures, oil oxidizes
through a series of chemical reactions which results in the formation of
monoacylglycerols, diacylglycerols, oxidized triacylglycerols, dimers,
trimers, polymers, free fatty acids, ketones, aldehydes, alcohols,
esters, and other minor products. In order to detect the rancidity of
oxidized soybean oil, carbon nanotube chemiresistor sensors have
been coated with polyethylenimine (PEI) to enhance the sensitivity
and selectivity. PEI functionalized SWCNTs are known to have a high
selectivity towards strong electron withdrawing molecules. The
sensors were very responsive to different oil oxidation levels and
furthermore, displayed a rapid recovery in ambient air without the
need of heating or UV exposure.
Abstract: The spores of entomopathogenic fungi, Beauveria bassiana was evaluated for their compatibility with four surfactants; SDS (sodium dodyl sulphate) and CABS-65 (calcium alkyl benzene sulphonate), Tween 20 (polyethylene sorbitan monolaureate) and Tween 80 (polyoxyethylene sorbitan monoleate) at six different concentrations (0.1%, 0.5%, 1%, 2.5%, 5% and 10%). Incubated spores showed decrease in concentrations due to conversion of spores to hyphae. The maximum germination recorded in 72 h incubated spores varied with surfactant concentration at 49-68% (SDS), 39- 53% (CABS), 78-92% (Tween 80) and 80-92% (Tween 20), while the optimal surfactant concentration for spore germination was found to be 2.5-5%. The surfactant effect on spores was more pronounced with SDS and CABS-65, where significant deterioration and loss in viability of the incubated spores was observed. The effect of Tween 20 and Tween 80 were comparatively less inhibiting. The results of the study would help in surfactant selection for B. bassiana emulsion preparation.
Abstract: Knowledge discovery from text and ontology learning
are relatively new fields. However their usage is extended in many
fields like Information Retrieval (IR) and its related domains. Human
Plausible Reasoning based (HPR) IR systems for example need a
knowledge base as their underlying system which is currently made
by hand. In this paper we propose an architecture based on ontology
learning methods to automatically generate the needed HPR
knowledge base.
Abstract: Hypernetworks are a generalized graph structure
representing higher-order interactions between variables. We present a
method for self-organizing hypernetworks to learn an associative
memory of sentences and to recall the sentences from this memory.
This learning method is inspired by the “mental chemistry" model of
cognition and the “molecular self-assembly" technology in
biochemistry. Simulation experiments are performed on a corpus of
natural-language dialogues of approximately 300K sentences
collected from TV drama captions. We report on the sentence
completion performance as a function of the order of word-interaction
and the size of the learning corpus, and discuss the plausibility of this
architecture as a cognitive model of language learning and memory.
Abstract: This is the second part of the paper. It, aside from the
core subroutine test reported previously, focuses on the simulation of
turbulence governed by the full STF Navier-Stokes equations on a
large scale. Law of the wall is found plausible in this study as a model
of the boundary layer dynamics. Model validations proceed to
include velocity profiles of a stationary turbulent Couette flow, pure
sloshing flow simulations, and the identification of water-surface
inclination due to fluid accelerations. Errors resulting from the
irrotational and hydrostatic assumptions are explored when studying
a wind-driven water circulation with no shakings. Illustrative
examples show that this numerical strategy works for the simulation
of sloshing-shear mixed flow in a 3-D rigid rectangular base tank.
Abstract: Oral health is particular important to the hospitalized
patients with chronic schizophrenia for an extreme high potential of the respiratory infections. Due to the degeneration of physical capability, patients of this kind typically fall dependent in the activity of daily living (ADL). A very high percentage of patients had dental
problems of which mostly could be easily avoid by easy regular tooth brushing. Purpose of the project is to develop a mechanism in helping the schizophrenia patients in rebuilding a tooth-cleaning habit. The
project observed and evaluated the tooth-cleaning behavior of 100
male patients in a psychiatric hospital, and found the majority of them
ignored such an activity in a three-month period of time. In the meantime, the primary care-givers were not aware or not convinced
the importance of such a need of dental hygiene, and thus few if any
tooth cleaning training or knowledge on dental hygiene were given to
the patients. The project then developed a program based on the numerous observations and discussions. The improvement program
included patients- group education, care-givers- training, and a
tool-kit for tooth-brush holding was erected. The project launched
with some incentive package. The outcomes were encouraging with
87% of the patients had rebuilt their tooth-brushing habits against
previous 22%, and the tooth cleaning kits were 100% kept against 22%
in the past. This project had significantly improved the oral health of
the patients. The project, included the procedure and the tool-kit
holder specific for this purpose, was a good examples for psychiatric
hospitals.
Abstract: Money laundering has been described by many as the lifeblood of crime and is a major threat to the economic and social well-being of societies. It has been recognized that the banking system has long been the central element of money laundering. This is in part due to the complexity and confidentiality of the banking system itself. It is generally accepted that effective anti-money laundering (AML) measures adopted by banks will make it tougher for criminals to get their "dirty money" into the financial system. In fact, for law enforcement agencies, banks are considered to be an important source of valuable information for the detection of money laundering. However, from the banks- perspective, the main reason for their existence is to make as much profits as possible. Hence their cultural and commercial interests are totally distinct from that of the law enforcement authorities. Undoubtedly, AML laws create a major dilemma for banks as they produce a significant shift in the way banks interact with their customers. Furthermore, the implementation of the laws not only creates significant compliance problems for banks, but also has the potential to adversely affect the operations of banks. As such, it is legitimate to ask whether these laws are effective in preventing money launderers from using banks, or whether they simply put an unreasonable burden on banks and their customers. This paper attempts to address these issues and analyze them against the background of the Malaysian AML laws. It must be said that effective coordination between AML regulator and the banking industry is vital to minimize problems faced by the banks and thereby to ensure effective implementation of the laws in combating money laundering.
Abstract: Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During
the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared
to public schools. This study investigated the environments of gifted
students compared with other non-gifted, using a survey instrument
that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total
number of 109 were selected from excellence schools for
academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students
reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and
32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%,
“Seldom" support with 15.4%, “Often" support with 26.6%,
“Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly,
statistical differences were found between the two groups favoring
non-gifted students in perception of their surrounding environments
in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions
of the survey, namely, family, peers, and resources. As the
differences were found in teachers, school- support, and society, the
nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and
infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful
identification models. Thus, families, schools, and society should
increase their cooperation, communication, and awareness of the
gifted supportive environments. However, more studies to investigate
other aspects of promoting academic giftedness and excellence are recommended.
Abstract: This paper presents a boarding on biometric
authentication through the Keystrokes Dynamics that it intends to
identify a person from its habitual rhythm to type in conventional
keyboard. Seven done experiments: verifying amount of prototypes,
threshold, features and the variation of the choice of the times of the
features vector. The results show that the use of the Keystroke
Dynamics is simple and efficient for personal authentication, getting
optimum resulted using 90% of the features with 4.44% FRR and 0%
FAR.
Abstract: This paper presents various classifiers results from a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The three classifiers considered are a naïve one and two based on the belief theory. The belief theory-based classifiers use either a classic or restricted plausibility criterion to make a decision after data fusion. The data come from the people 2D segmentation and from their face localization. Measurements consist in distances relative to a reference posture. The efficiency and the limits of the different classifiers on the recognition system are highlighted thanks to the analysis of a great number of results. This system allows real-time processing.
Abstract: The major goal in defining and examining game
scenarios is to find good strategies as solutions to the game. A
plausible solution is a recommendation to the players on how to play
the game, which is represented as strategies guided by the various
choices available to the players. These choices invariably compel the
players (decision makers) to execute an action following some
conscious tactics. In this paper, we proposed a refinement-based
heuristic as a machine learning technique for human-like decision
making in playing Ayo game. The result showed that our machine
learning technique is more adaptable and more responsive in making
decision than human intelligence. The technique has the advantage
that a search is astutely conducted in a shallow horizon game tree.
Our simulation was tested against Awale shareware and an appealing
result was obtained.
Abstract: This paper describes studies carried out to investigate
the viability of using wireless cameras as a tool in monitoring
changes in air quality. A camera is used to monitor the change in
colour of a chemically responsive polymer within view of the camera
as it is exposed to varying chemical species concentration levels. The
camera captures this image and the colour change is analyzed by
averaging the RGB values present. This novel chemical sensing
approach is compared with an established chemical sensing method
using the same chemically responsive polymer coated onto LEDs. In
this way, the concentration levels of acetic acid in the air can be
tracked using both approaches. These approaches to chemical plume
tracking have many applications for air quality monitoring.
Abstract: Emergence of smartphones brings to live the concept
of converged devices with the availability of web amenities. Such
trend also challenges the mobile devices manufactures and service
providers in many aspects, such as security on mobile phones,
complex and long time design flow, as well as higher development
cost. Among these aspects, security on mobile phones is getting more
and more attention. Microkernel based virtualization technology will
play a critical role in addressing these challenges and meeting mobile
market needs and preferences, since virtualization provides essential
isolation for security reasons and it allows multiple operating systems
to run on one processor accelerating development and cutting development
cost. However, virtualization benefits do not come for free.
As an additional software layer, it adds some inevitable virtualization
overhead to the system, which may decrease the system performance.
In this paper we evaluate and analyze the virtualization performance
cost of L4 microkernel based virtualization on a competitive mobile
phone by comparing the L4Linux, a para-virtualized Linux on top of
L4 microkernel, with the native Linux performance using lmbench
and a set of typical mobile phone applications.
Abstract: In this paper is presented a Geographic Information System (GIS) approach in order to qualify and monitor the broadband lines in efficient way. The methodology used for interpolation is the Delaunay Triangular Irregular Network (TIN). This method is applied for a case study in ISP Greece monitoring 120,000 broadband lines.
Abstract: The response surface methodology (RSM) is a
collection of mathematical and statistical techniques useful in the
modeling and analysis of problems in which the dependent variable
receives the influence of several independent variables, in order to
determine which are the conditions under which should operate these
variables to optimize a production process. The RSM estimated a
regression model of first order, and sets the search direction using the
method of maximum / minimum slope up / down MMS U/D.
However, this method selects the step size intuitively, which can
affect the efficiency of the RSM. This paper assesses how the step
size affects the efficiency of this methodology. The numerical
examples are carried out through Monte Carlo experiments,
evaluating three response variables: efficiency gain function, the
optimum distance and the number of iterations. The results in the
simulation experiments showed that in response variables efficiency
and gain function at the optimum distance were not affected by the
step size, while the number of iterations is found that the efficiency if
it is affected by the size of the step and function type of test used.
Abstract: Directional over current relays (DOCR) are commonly used in power system protection as a primary protection in distribution and sub-transmission electrical systems and as a secondary protection in transmission systems. Coordination of protective relays is necessary to obtain selective tripping. In this paper, an approach for efficiency reduction of DOCRs nonlinear optimum coordination (OC) is proposed. This was achieved by modifying the objective function and relaxing several constraints depending on the four constraints classification, non-valid, redundant, pre-obtained and valid constraints. According to this classification, the far end fault effect on the objective function and constraints, and in consequently on relay operating time, was studied. The study was carried out, firstly by taking into account the near-end and far-end faults in DOCRs coordination problem formulation; and then faults very close to the primary relays (nearend faults). The optimal coordination (OC) was achieved by simultaneously optimizing all variables (TDS and Ip) in nonlinear environment by using of Genetic algorithm nonlinear programming techniques. The results application of the above two approaches on 6-bus and 26-bus system verify that the far-end faults consideration on OC problem formulation don-t lose the optimality.