Abstract: Vortices can develop in intakes of turbojet and turbo
fan aero engines during high power operation in the vicinity of solid
surfaces. These vortices can cause catastrophic damage to the engine.
The factors determining the formation of the vortex include both
geometric dimensions as well as flow parameters. It was shown that
the threshold at which the vortex forms or disappears is also
dependent on the initial flow condition (i.e. whether a vortex forms
after stabilised non vortex flow or vice-versa). A computational fluid
dynamics study was conducted to determine the difference in
thresholds between the two conditions. This is the first reported
numerical investigation of the “memory effect". The numerical
results reproduce the phenomenon reported in previous experimental
studies and additional factors, which had not been previously studied,
were investigated. They are the rate at which ambient velocity
changes and the initial value of ambient velocity. The former was
found to cause a shift in the threshold but not the later. It was also
found that the varying condition thresholds are not symmetrical about
the neutral threshold. The vortex to no vortex threshold lie slightly
further away from the neutral threshold compared to the no vortex to
vortex threshold. The results suggests that experimental investigation
of vortex formation threshold performed either in vortex to no vortex
conditions, or vice versa, solely may introduce mis-predictions
greater than 10%.
Abstract: The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.
Abstract: L-asparaginase was extracted from pathogenic
Escherichia coli which was isolated from urinary tract infection
patients. L-asparaginase was purified 96-fold by ultrafiltration, ion
exchange and gel filtration giving 39.19% yield with final specific
activity of 178.57 IU/mg. L-asparaginase showed 138,356±1,000
Dalton molecular weight with 31024±100 Dalton molecular mass.
Kinetic properties of enzyme resulting 1.25×10-5 mM Km and
2.5×10-3 M/min Vmax. L-asparaginase showed a maximum activity
at pH 7.5 when incubated at 37 ºC for 30 min and illustrated its full
activity (100%) after 15 min incubation at 20-37 ºC, while 70% of its
activity was lost when incubated at 60 ºC. L-asparaginase showed
cytotoxicity to U937 cell line with IC50 0.5±0.19 IU/ml, and
selectivity index (SI=7.6) about 8 time higher selectivity over the
lymphocyte cells. Therefore, the local pathogenic E. coli strains may
be used as a source of high yield of L-asparaginase to produce anti
cancer agent with high selectivity.
Abstract: Vehicular Ad-hoc Network (VANET) is taking more
attention in automotive industry due to the safety concern of human
lives on roads. Security is one of the safety aspects in VANET. To be
secure, network availability must be obtained at all times since
availability of the network is critically needed when a node sends any
life critical information to other nodes. However, it can be expected
that security attacks are likely to increase in the coming future due to
more and more wireless applications being developed and deployed
onto the well-known expose nature of the wireless medium. In this
respect, the network availability is exposed to many types of attacks.
In this paper, Denial of Service (DOS) attack on network availability
is presented and its severity level in VANET environment is
elaborated. A model to secure the VANET from the DOS attacks has
been developed and some possible solutions to overcome the attacks
have been discussed.
Abstract: In the 1980s, companies began to feel the effect of three major influences on their product development: newer and innovative technologies, increasing product complexity and larger organizations. And therefore companies were forced to look for new product development methods. This paper tries to focus on the two of new product development methods (DFM and CE). The aim of this paper is to see and analyze different product development methods specifically on Design for Manufacturability and Concurrent Engineering. Companies can achieve and be benefited by minimizing product life cycle, cost and meeting delivery schedule. This paper also presents simplified models that can be modified and used by different companies based on the companies- objective and requirements. Methodologies that are followed to do this research are case studies. Two companies were taken and analysed on the product development process. Historical data, interview were conducted on these companies in addition to that, Survey of literatures and previous research works on similar topics has been done during this research. This paper also tries to show the implementation cost benefit analysis and tries to calculate the implementation time. From this research, it has been found that the two companies did not achieve the delivery time to the customer. Some of most frequently coming products are analyzed and 50% to 80 % of their products are not delivered on time to the customers. The companies are following the traditional way of product development that is sequentially design and production method, which highly affect time to market. In the case study it is found that by implementing these new methods and by forming multi disciplinary team in designing and quality inspection; the company can reduce the workflow steps from 40 to 30.
Abstract: Contact stress is an important problem in industry.
This is a problem that in the first attention may be don-t appears, but
disregard of these stresses cause a lot of damages in machines. These
stresses occur at locations such as gear teeth, bearings, cams and
between a locomotive wheel and the railroad rail. These stresses
cause failure by excessive elastic deformation, yielding and fracture.
In this paper we intend show the effective parameters in contact
stress and ponder effect of curvature. In this paper we study contact
stresses on the surface of gear teeth and compare these stresses for
four popular profiles of gear teeth (involute, cycloid, epicycloids, and
hypocycloid). We study this problem with mathematical and finite
element methods and compare these two methods on different profile
surfaces.
Abstract: The goal of a network-based intrusion detection
system is to classify activities of network traffics into two major
categories: normal and attack (intrusive) activities. Nowadays, data
mining and machine learning plays an important role in many
sciences; including intrusion detection system (IDS) using both
supervised and unsupervised techniques. However, one of the
essential steps of data mining is feature selection that helps in
improving the efficiency, performance and prediction rate of
proposed approach. This paper applies unsupervised K-means
clustering algorithm with information gain (IG) for feature selection
and reduction to build a network intrusion detection system. For our
experimental analysis, we have used the new NSL-KDD dataset,
which is a modified dataset for KDDCup 1999 intrusion detection
benchmark dataset. With a split of 60.0% for the training set and the
remainder for the testing set, a 2 class classifications have been
implemented (Normal, Attack). Weka framework which is a java
based open source software consists of a collection of machine
learning algorithms for data mining tasks has been used in the testing
process. The experimental results show that the proposed approach is
very accurate with low false positive rate and high true positive rate
and it takes less learning time in comparison with using the full
features of the dataset with the same algorithm.
Abstract: By the end of XX century in the structure of humanity some changes have been provoked: a new ethnos - Ethnos of Intellect is formed and is still being formed, beside the historical types of ethnoses: open ethnos, closed ethnos, wandering ethnos, dead ethnos, - and this event was caused by the technical progress, development of informational and transport communications, especially - by creation of Internet. The Ethnos of Intellect is something very close to the ÔÇ×Information Society“ described by J. Ellule and Y. Masuda that was regarded as the culture of XXI century, being an antithesis for technical and technicistical civilizations, but it-s necessary to indicate also the essential difference between these concepts: the Ethnos of Intellect is the antithesis of Socium. The existence of such an ethnos within human society that has already become an Information Society itself is extremely important in observing legally and informatically a new kind of reins in the hands of the political power, revealing every attempt to violate the human rights of simple citizens. A concrete example of some conjunction points of legal informatics and informatical law in a certain kind of ambiental studies of the project ''State Registre of Population'' in Russia is very eloquent.
Abstract: Information systems practitioners are frequently
required to master new technology, often without the aid of formal
training. They require the skill to manage their own learning and,
when this skill is developed in their formal training, their adaptability
to new technology may be improved. Self- directed learning is the
ability of the learner to manage his or her own learning experience
with some guidance from a facilitator. Self-directed learning skills
are best improved when practiced. This paper reflects on a critical
social research project to improve the self-directed learning skills of
fourth year Information Systems students. Critical social research
differs from other research paradigms in that the researcher is viewed
as the agent of change to achieve the desired outcome in the problem
situation.
Abstract: Mostly transforms are used for speech data
compressions which are lossy algorithms. Such algorithms are
tolerable for speech data compression since the loss in quality is not
perceived by the human ear. However the vector quantization (VQ)
has a potential to give more data compression maintaining the same
quality. In this paper we propose speech data compression algorithm
using vector quantization technique. We have used VQ algorithms
LBG, KPE and FCG. The results table shows computational
complexity of these three algorithms. Here we have introduced a new
performance parameter Average Fractional Change in Speech
Sample (AFCSS). Our FCG algorithm gives far better performance
considering mean absolute error, AFCSS and complexity as
compared to others.
Abstract: The most important subtype of non-Hodgkin-s
lymphoma is the Diffuse Large B-Cell Lymphoma. Approximately
40% of the patients suffering from it respond well to therapy,
whereas the remainder needs a more aggressive treatment, in order to
better their chances of survival. Data Mining techniques have helped
to identify the class of the lymphoma in an efficient manner. Despite
that, thousands of genes should be processed to obtain the results.
This paper presents a comparison of the use of various attribute
selection methods aiming to reduce the number of genes to be
searched, looking for a more effective procedure as a whole.
Abstract: The service industry accounts for about 70% of GDP of
Japan, and the importance of the service innovation is pointed out. The
importance of the system use and the support service increases in the
information system that is one of the service industries. However,
because the system is not used enough, the purpose for which it was
originally intended cannot often be achieved in the CRM system. To
promote the use of the system, the effective service method is needed.
It is thought that the service model's making and the clarification of the
success factors are necessary to improve the operation service of the
CRM system. In this research the model of the operation service in the
CRM system is made.
Abstract: In this paper, several improvements are proposed to
previous work of automated classification of alcoholics and nonalcoholics.
In the previous paper, multiplayer-perceptron neural
network classifying energy of gamma band Visual Evoked Potential
(VEP) signals gave the best classification performance using 800
VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the
dataset is extended to include 3560 VEP signals from 102 subjects:
62 alcoholics and 40 non-alcoholics. Three modifications are
introduced to improve the classification performance: i) increasing
the gamma band spectral range by increasing the pass-band width of
the used filter ii) the use of Multiple Signal Classification algorithm
to obtain the power of the dominant frequency in gamma band VEP
signals as features and iii) the use of the simple but effective knearest
neighbour classifier. To validate that these two modifications
do give improved performance, a 10-fold cross validation
classification (CVC) scheme is used. Repeat experiments of the
previously used methodology for the extended dataset are performed
here and improvement from 94.49% to 98.71% in maximum
averaged CVC accuracy is obtained using the modifications. This
latest results show that VEP based classification of alcoholics is
worth exploring further for system development.
Abstract: The move from cash accounting to accrual accounting, or rule-based to principle-based accounting, by many governments is part of an ongoing efforts in promoting a more business-like and performance-focused public sector. Using questionnaire responses from preparers of financial statements of public universities in Malaysia, this study examines the implementation challenges and benefits of principle-based accounting. Results from these responses suggest that most respondents perceived significant costs would be incurred in relation to staff training and recruitment of staffs with relevant technical knowledge. In addition, most respondents also perceived that there will be significant changes in the current accounting system and structure in order to comply with the principle-based accounting requirements. However, most respondents perceived that these changes might not result in significant benefits for management purposes, for example, financial management, budgeting and allocation of resources. Nevertheless, most respondents perceived that principle-based accounting information would facilitate the monitoring function of the board. The general perception is that adoption of principle-based accounting information is not significantly useful than rule-based accounting information is expected to change over time as preparers of the financial statements gradually understand and appreciate the benefits of principle-based accounting information. This infers that the perceived usefulness of different accounting system is a function of familiarity by the preparers.
Abstract: In this paper we propose a simple adaptive algorithm
iteratively solving the unit-norm constrained optimization problem.
Instead of conventional parameter norm based normalization,
the proposed algorithm incorporates scalar normalization which is
computationally much simpler. The analysis of stationary point is
presented to show that the proposed algorithm indeed solves the
constrained optimization problem. The simulation results illustrate
that the proposed algorithm performs as good as conventional ones
while being computationally simpler.
Abstract: This study aims to discuss the effect of illumination and the color temperature of the lighting source under the office lighting environment on human psychological and physiological responses. In this study, 21 healthy participants were selected, and the Ryodoraku measurement system was utilized to measure their skin resistance change.The findings indicated that the effect of the color temperature of the lighting source on human physiological responses is significant within 90 min after turning the lights on; while after 90 min the effect of illumination on human physiological responses is higher than that of the color temperature. Moreover, the cardiovascular, digestive and endocrine systems are prone to be affected by the indoor lighting environment. During the long-term exposure to high intensity of illumination and high color temperature (2000Lux -6500K), the effect on the psychological responses turned moderate after the human visual system adopted to the lighting environment. However, the effect of the Ryodoraku value on human physiological responses was more significant with the increase of perceptive time. The effect of long time exposure to a lighting environment on the physiological responses is greater than its effect on the psychological responses. This conclusion is different from the traditional public viewpoint that the effect on the psychological responses is greater.
Abstract: In Content-Based Image Retrieval systems it is
important to use an efficient indexing technique in order to perform
and accelerate the search in huge databases. The used indexing
technique should also support the high dimensions of image features.
In this paper we present the hierarchical index NOHIS-tree (Non
Overlapping Hierarchical Index Structure) when we scale up to very
large databases. We also present a study of the influence of clustering
on search time. The performance test results show that NOHIS-tree
performs better than SR-tree. Tests also show that NOHIS-tree keeps
its performances in high dimensional spaces. We include the
performance test that try to determine the number of clusters in
NOHIS-tree to have the best search time.
Abstract: The Mobile IP Standard has been developed to support mobility over the Internet. This standard contains several drawbacks as in the cases where packets are routed via sub-optimal paths and significant amount of signaling messages is generated due to the home registration procedure which keeps the network aware of the current location of the mobile nodes. Recently, a dynamic hierarchical mobility management strategy for mobile IP networks (DHMIP) has been proposed to reduce home registrations costs. However, this strategy induces a packet delivery delay and increases the risk of packet loss. In this paper, we propose an enhanced version of the dynamic hierarchical strategy that reduces the packet delivery delay and minimizes the risk of packet loss. Preliminary results obtained from simulations are promising. They show that the enhanced version outperforms the original dynamic hierarchical mobility management strategy version.
Abstract: The protection of groundwater resources is the great
important many semiarid and arid environments. Baghan watershed
is located in the north of Kangan in the Boshehr province in Iran. The
groundwater resources have a vital role in supplying agricultural,
drinking, domestic and industrial water demand in Baghan
watershed. For our investigation into the water quality we collected
30 samples to chemical and physical analysis. The result showed the
marl and evaporation deposits that contain anhydrite and gypsum is
the main source of groundwater pollution, and one part of the
groundwater was polluted by oil and gas industrial. Another part of
the groundwater was contaminated by urban waste water. The
electrical conductivity and captions and anions increased around of
towns and gas refinery. Although the negative impact of untreated
domestic wastewater is relatively low but the results showed strongly
the negative impact of wastewater refinery is very considerable. This
negative impact increased in downstream due to shallow aquifer.
Additionally, the agents that adversely affect the quality of
groundwater come from a variety of sources, including geology,
domestic wastewater and the Jam refinery in Baghan watershed.
Abstract: Keys to high-quality face-to-face education are ensuring flexibility in the way lectures are given, and providing care and responsiveness to learners. This paper describes a face-to-face education support system that is designed to raise the satisfaction of learners and reduce the workload on instructors. This system consists of a lecture adaptation assistance part, which assists instructors in adapting teaching content and strategy, and a Q&A assistance part, which provides learners with answers to their questions. The core component of the former part is a “learning achievement map", which is composed of a Bayesian network (BN). From learners- performance in exercises on relevant past lectures, the lecture adaptation assistance part obtains information required to adapt appropriately the presentation of the next lecture. The core component of the Q&A assistance part is a case base, which accumulates cases consisting of questions expected from learners and answers to them. The Q&A assistance part is a case-based search system equipped with a search index which performs probabilistic inference. A prototype face-to-face education support system has been built, which is intended for the teaching of Java programming, and this approach was evaluated using this system. The expected degree of understanding of each learner for a future lecture was derived from his or her performance in exercises on past lectures, and this expected degree of understanding was used to select one of three adaptation levels. A model for determining the adaptation level most suitable for the individual learner has been identified. An experimental case base was built to examine the search performance of the Q&A assistance part, and it was found that the rate of successfully finding an appropriate case was 56%.