Abstract: The purpose of the research is to investigate the energetic feature of the backpack load on soldier’s gait with variation of the trunk flexion angle. It is believed that the trunk flexion variation of the loaded gait may cause a significant difference in the energy cost which is often in practice in daily life. To this end, seven healthy Korea military personnel participated in the experiment and are tested under three different walking postures comprised of the small, natural and large trunk flexion. There are around 5 degree differences of waist angle between each trunk flexion. The ground reaction forces were collected from the force plates and motion kinematic data are measured by the motion capture system. Based on these data, the impulses, momentums and mechanical works done on the center of body mass (COM) during the double support phase were computed. The result shows that the push-off and heel strike impulse are not relevant to the trunk flexion change, however the mechanical work by the push-off and heel strike were changed by the trunk flexion variation. It is because the vertical velocity of the COM during the double support phase is increased significantly with an increase in the trunk flexion. Therefore, we can know that the gait efficiency of the loaded gait depends on the trunk flexion angle. Also, even though the gravitational impulse and pre-collision momentum are changed by the trunk flexion variation, the after-collision momentum is almost constant regardless of the trunk flexion variation.
Abstract: Microorganisms can be removed, inhibited or killed by physical agents, physical processes or chemical agents but they have their inherent disadvantages such as increased resistance against antibiotics etc. Since, plants have endless ability to synthesize aromatic substances which act as the master agents for plant defense mechanisms against microorganisms, insects and herbivores. Thus, secondary metabolites or phytochemicals obtained from plants can be used as agents of disease control nowadays. In the present study effect of different concentrations of acetone fraction of leaves and alcohol fraction of inflorescence of Euphorbia pulcherrima on various cytomorphological parameters i.e. cell number, mycelium width, conidial size, conidiophore size etc. of Aspergillus fumigatus has been studied. Change in mycelium/ hyphal cell width, conidium size, conidiophore size etc. was measured with the help of a previously calibrated oculometer. To study effect on morphology, fungal mycelium along with conidiophore and conidia were stained with cotton blue and mounted in lactophenol and observed microscopically. Inhibitory action of the acetone extract of Euphorbia pulcherrima leaf on growth of Aspergillus fumigatus was investigated. Control containing extract free medium supported profuse growth of the fungus. Although decrease in growth was observed even at 3.95μg/ml but significant inhibition of growth was started at7.81μg/ml concentration of the extract. Complete inhibition was observed at 15.62μg/ml and above. Microscopic examination revealed that at 3.95, 7.81 and 15.62μg/ml extract concentration hyphal cell width was found to be increased from 1.44μm in control to 3.86, 5.24 and 8.98 μm respectively giving a beaded appearance to the mycelium. Vesicle size was reduced from 24.78x20.08μm (control) to 11.34x10.06μm at 3.95μg/ml concentration. At 7.81 and 15.62μg/ml concentration no phialides and sterigmata were observed. Inhibitory action of the alcohol extract of inflorescence on the growth of Aspergillus fumigatus was also studied. Control containing extract free medium supported profuse growth of the fungus. Although decrease in growth was observed even at 3.95μg/ml but complete inhibition was observed at 62.5μg/ml and above. Microscopic examination revealed that hyphal cell width of Aspergillus fumigatus was found to be increased from 1.67μm in control to 5.84μm at MIC i.e. at 62.5μg/ml. Vesicle size was reduced from 44.76x 24.22μm (control) to 11.36x 6.80μm at 15.62μg/ml concentrations. At 31.25 μg/ml and 62.5μg/ml concentration no phialides and sterigmata was found. Spore germination was completely found to be inhibited at 3.95μg/ml concentration. Similarly 92.87% reduction in vesicle size was observed at 15.62μg/ml concentration. It is evident from the results that plant extracts inhibit fungal growth and this inhibition is concentration dependent.
Abstract: The aim of this paper is to examine the relationship among CO2 per capita emissions, energy consumption, economic growth and bilateral trade between Singapore and Malaysia for the 1970-2011 period. ARDL model and Granger causality tests are employed for the analysis. Results of bound F-statistics suggest that long-run relationship exists between CO2 per capita (PCO2) and its determinants. The EKC hypothesis is not supported in Malaysia. Carbon emissions are mainly determined by energy consumption in the short and long run. While, exports to Singapore is a significant variable in explaining PCO2 emissions in Malaysia in long-run. Furthermore, we find a unidirectional causal relationship running from economic growth to PCO2 emissions.
Abstract: This study was conducted to evaluate the anti-diabetic
properties of ethanolic extract of two plants commonly used in folk
medicine, Mormodica charantia (bitter melon) and Trigonella
foenum-graecum (fenugreek). The study was performed on STZinduced
diabetic rats (DM type-I). Plant extracts of these two plants
were given to STZ diabetic rats at the concentration of 500 mg/kg
body weight ,50 mg/kg body weight respectively. Cidophage®
(metformin HCl) were administered to another group to support the
results at a dose of 500 mg/kg body weight, the ethanolic extracts and
Cidophage administered orally once a day for four weeks using a
stomach tube and; serum samples were obtained for biochemical
analysis. The extracts caused significant decreases in glucose levels
compared with diabetic control rats. Insulin secretions were increased
after 4 weeks of treatment with Cidophage® compared with the
control non-diabetic rats. Levels of AST and ALT liver enzymes were
normalized by all treatments. Decreases in liver cholesterol,
triglycerides, and LDL in diabetic rats were observed with all
treatments. HDL levels were increased by the treatments in the
following order: bitter melon, Cidophage®, and fenugreek. Creatinine
levels were reduced by all treatments. Serum nitric oxide and
malonaldehyde levels were reduced by all extracts. GSH levels were
increased by all extracts. Extravasation as measured by the Evans
Blue test increased significantly in STZ-induced diabetic animals.
This effect was reversed by ethanolic extracts of bitter melon or
fenugreek.
Abstract: Digital libraries become more and more necessary in
order to support users with powerful and easy-to-use tools for
searching, browsing and retrieving media information. The starting
point for these tasks is the segmentation of video content into shots.
To segment MPEG video streams into shots, a fully automatic
procedure to detect both abrupt and gradual transitions (dissolve and
fade-groups) with minimal decoding in real time is developed in this
study. Each was explored through two phases: macro-block type's
analysis in B-frames, and on-demand intensity information analysis.
The experimental results show remarkable performance in
detecting gradual transitions of some kinds of input data and
comparable results of the rest of the examined video streams. Almost
all abrupt transitions could be detected with very few false positive
alarms.
Abstract: Provision of optical devices without proper instruction
and training may cause frustration resulting in rejection or incorrect
use of the magnifiers. However training in the use of magnifiers
increases the cost of providing these devices. This study compared
the efficacy of providing instruction alone and instruction plus
training in the use of magnifiers. 24 participants randomly assigned
to two groups. 15 received instruction and training and 9 received
instruction only. Repeated measures of print size and reading speed
were performed at pre, post training and follow up. Print size
decreased in both groups between pre and post training maintained at
follow up. Reading speed increased in both groups over time with the
training group demonstrating more rapid improvement. Whilst
overall outcomes were similar, training decreased the time required
to increase reading speed supporting the use of training for increased
efficiency. A cost effective form of training is suggested.
Abstract: In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.
Abstract: In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment.
Abstract: One of the major features of hypermedia learning is its non-linear structure, allowing learners, the opportunity of flexible navigation to accommodate their own needs. Nevertheless, such flexibility can also cause problems such as insufficient navigation and disorientation for some learners, especially those with Field Dependent cognitive styles. As a result students learning performance can be deteriorated and in turn, they can have negative attitudes with hypermedia learning systems. It was suggested that visual elements can be used to compensate dilemmas. However, it is unclear whether these visual elements improve their learning or whether problems still exist. The aim of this study is to investigate the effect of students cognitive styles and visual elements on students learning performance and attitudes in hypermedia learning environment. Cognitive Style Analysis (CSA), Learning outcome in terms of pre and post-test, practical task, and Attitude Questionnaire (AQ) were administered to a sample of 60 university students. The findings revealed that FD students preformed equally to those of FI. Also, FD students experienced more disorientation in the hypermedia learning system where they depend a lot on the visual elements for navigation and orientation purposes. Furthermore, they had more positive attitudes towards the visual elements which escape them from experiencing navigation and disorientation dilemmas. In contrast, FI students were more comfortable, did not get disturbed or did not need some of the visual elements in the hypermedia learning system.
Abstract: Value-based group decision is very complicated since many parties involved. There are different concern caused by differing preferences, experiences, and background. Therefore, a support system is required to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. The support system is based on combination between value-based analysis, multi criteria group decision making based on satisfying options, and negotiation process based on coalition formation. This paper presents the group decision and negotiation on the selection of suitable material for a support bridge structure involving three decision makers, who are an estate manager, a project manager, and an engineer. There are three alternative solutions for the material of the support bridge structure, which are (a1) steel structure, (a2) reinforced concrete structure and (a3) wooden structure.
Abstract: In this paper a study on the vibration of thin
cylindrical shells with ring supports and made of functionally
graded materials (FGMs) composed of stainless steel and
nickel is presented. Material properties vary along the
thickness direction of the shell according to volume fraction
power law. The cylindrical shells have ring supports which are
arbitrarily placed along the shell and impose zero lateral
deflections. The study is carried out based on third order shear
deformation shell theory (T.S.D.T). The analysis is carried out
using Hamilton-s principle. The governing equations of motion of
FGM cylindrical shells are derived based on shear deformation
theory. Results are presented on the frequency characteristics,
influence of ring support position and the influence of boundary
conditions. The present analysis is validated by comparing results
with those available in the literature.
Abstract: In this paper we introduce an effective ECG compression algorithm based on two dimensional multiwavelet transform. Multiwavelets offer simultaneous orthogonality, symmetry and short support, which is not possible with scalar two-channel wavelet systems. These features are known to be important in signal processing. Thus multiwavelet offers the possibility of superior performance for image processing applications. The SPIHT algorithm has achieved notable success in still image coding. We suggested applying SPIHT algorithm to 2-D multiwavelet transform of2-D arranged ECG signals. Experiments on selected records of ECG from MIT-BIH arrhythmia database revealed that the proposed algorithm is significantly more efficient in comparison with previously proposed ECG compression schemes.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
we present three feature selection methods: Information Gain,
Support Vector Machine feature selection called (SVM_FS) and
Genetic Algorithm with SVM (called GA_SVM). We show that the
best results were obtained with GA_SVM method for a relatively
small dimension of the feature vector.
Abstract: We evaluate the average energy consumption per bit
in Optical Packet Switches equipped with BENES switching fabric
realized in Semiconductor Optical Amplifier (SOA) technology. We
also study the impact that the Amplifier Spontaneous Emission
(ASE) noise generated by a transmission system has on the power
consumption of the BENES switches due to the gain saturation of the
SOAs used to realize the switching fabric. As a matter of example for
32×32 switches supporting 64 wavelengths and offered traffic equal
to 0,8, the average energy consumption per bit is 2, 34 · 10-1 nJ/bit
and increases if ASE noise introduced by the transmission systems
is increased.
Abstract: Defect prevention is the most vital but habitually
neglected facet of software quality assurance in any project. If
functional at all stages of software development, it can condense the
time, overheads and wherewithal entailed to engineer a high quality
product. The key challenge of an IT industry is to engineer a
software product with minimum post deployment defects.
This effort is an analysis based on data obtained for five selected
projects from leading software companies of varying software
production competence. The main aim of this paper is to provide
information on various methods and practices supporting defect
detection and prevention leading to thriving software generation. The
defect prevention technique unearths 99% of defects. Inspection is
found to be an essential technique in generating ideal software
generation in factories through enhanced methodologies of abetted
and unaided inspection schedules. On an average 13 % to 15% of
inspection and 25% - 30% of testing out of whole project effort time
is required for 99% - 99.75% of defect elimination.
A comparison of the end results for the five selected projects
between the companies is also brought about throwing light on the
possibility of a particular company to position itself with an
appropriate complementary ratio of inspection testing.
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: 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 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: 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%.