Abstract: In this paper, we present an analytical framework for the evaluation of the uplink performance of multihop cellular networks based on dynamic time division duplex (TDD). New wireless broadband protocols, such as WiMAX, WiBro, and 3G-LTE apply TDD, and mobile communication protocols under standardization (e.g., IEEE802.16j) are investigating mobile multihop relay (MMR) as a future technology. In this paper a novel MMR TDD scheme is presented, where the dynamic range of the frame is shared to traffic resources of asymmetric nature and multihop relaying. The mobile communication channel interference model comprises of inner and co-channel interference (CCI). The performance analysis focuses on the uplink due to the fact that the effects of dynamic resource allocation show significant performance degradation only in the uplink compared to time division multiple access (TDMA) schemes due to CCI [1-3], where the downlink results to be the same or better.The analysis was based on the signal to interference power ratio (SIR) outage probability of dynamic TDD (D-TDD) and TDMA systems,which are the most widespread mobile communication multi-user control techniques. This paper presents the uplink SIR outage probability with multihop results and shows that the dynamic TDD scheme applying MMR can provide a performance improvement compared to single hop applications if executed properly.
Abstract: The scenario of bypass transition is generally described
as follows: the low-frequency disturbances in the free-stream may
generate long stream-wise streaks in the boundary layer, which later
may trigger secondary instability, leading to rapid increase of
high-frequency disturbances. Then possibly turbulent spots emerge,
and through their merging, lead to fully developed turbulence. This
description, however, is insufficient in the sense that it does not
provide the inherent mechanism of transition that during the transition,
a large number of waves with different frequencies and wave numbers
appear almost simultaneously, producing sufficiently large Reynolds
stress, so the mean flow profile can change rapidly from laminar to
turbulent. In this paper, such a mechanism will be figured out from
analyzing DNS data of transition.
Abstract: Images are important in disease research, education,
and clinical medicine. This paper presents a Web Service Platform
(WSP) for support multiple programming languages to access image
from biomedical databases. The main function WSP is to allow web
users access image from biomedical databases. The WSP will
receive web user-s queries. After that, it will send to Querying
Server (QS) and the QS will search and retrieve data from
biomedical databases. Finally, the information will display to the
web users. Simple application is developed and tested for
experiment purpose. Result from experiment indicated WSP can be
used in biomedical environment.
Abstract: As new challenges emerge in power electrical
workplace safety, it is the responsibility of the systems designer to
seek out new approaches and solutions that address them. Design
decisions made today will impact cost, safety and serviceability of
the installed systems for 40 or 50 years during the useful life for the
owner. Studies have shown that this cost is an order of magnitude of
7 to 10 times the installed cost of the power distribution equipment.
This paper reviews some aspects of earthing system design in power
substation surrounded by residential houses. The electrical potential
rise and split factors are discussed and a few recommendations are
provided to achieve a safety voltage in the area beyond the boundary
of the substation.
Abstract: Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: This paper critiques several exiting strategic
international human resource management (SIHRM) frameworks and
discusses their limitations to apply directly to emerging multinational
enterprises (EMNEs), especially those generated from China and
other BRICS nations. To complement the existing SIHRM
frameworks, key variables relevant to emerging economies are
identified and the extended model with particular reference to
EMNEs is developed with several research propositions. It is
believed that the extended model would better capture the recent
development of MNEs in transition, and alert emerging international
managers to address several human resource management challenges
in the global context
Abstract: The article deals with technical support of intracranial single unit activity measurement. The parameters of the whole measuring set were tested in order to assure the optimal conditions of extracellular single-unit recording. Metal microelectrodes for measuring the single-unit were tested during animal experiments. From signals recorded during these experiments, requirements for the measuring set parameters were defined. The impedance parameters of the metal microelectrodes were measured. The frequency-gain and autonomous noise properties of preamplifier and amplifier were verified. The measurement and the description of the extracellular single unit activity could help in prognoses of brain tissue damage recovery.
Abstract: An attractor neural network on the small-world topology
is studied. A learning pattern is presented to the network, then
a stimulus carrying local information is applied to the neurons and
the retrieval of block-like structure is investigated. A synaptic noise
decreases the memory capability. The change of stability from local
to global attractors is shown to depend on the long-range character
of the network connectivity.
Abstract: Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.
Abstract: Mathematical models can be used to describe the
transmission of disease. Dengue disease is the most significant
mosquito-borne viral disease of human. It now a leading cause of
childhood deaths and hospitalizations in many countries. Variations
in environmental conditions, especially seasonal climatic parameters,
effect to the transmission of dengue viruses the dengue viruses and
their principal mosquito vector, Aedes aegypti. A transmission model
for dengue disease is discussed in this paper. We assume that the
human and vector populations are constant. We showed that the local
stability is completely determined by the threshold parameter, 0 B . If
0 B is less than one, the disease free equilibrium state is stable. If
0 B is more than one, a unique endemic equilibrium state exists and
is stable. The numerical results are shown for the different values of
the transmission probability from vector to human populations.
Abstract: Weblog is an Internet tool that is believed to possess
great potential to facilitate learning in education. This study wants to
know if weblog can be used to promote students- critical thinking. It
used a group of secondary two students from a Singapore school to
write weblogs as a means of substitution for their traditional
handwritten assignments. The topics for the weblogging are taken
from History syllabus but modified to suit the purpose of this study.
Weblogs from the students were collected and analysed using a
known coding system for measuring critical thinking. Results show
that the topic for blogging is crucial in determining the types of
critical thinking employed by the students. Students are seen to
display critical thinking traits in the areas of information sourcing,
linking information to arguments and viewpoints justification.
Students- criticalness is more profound when the information for
writing a topic is readily available. Otherwise, they tend to be less
critical and subjective. The study also found that students lack the
ability to source for external information suggesting that students
may need to be taught information literacy in order to widen their use
of critical thinking skills.
Abstract: Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians.
Abstract: The objective of the present communication is to
develop new genuine exponentiated mean codeword lengths and to
study deeply the problem of correspondence between well known
measures of entropy and mean codeword lengths. With the help of
some standard measures of entropy, we have illustrated such a
correspondence. In literature, we usually come across many
inequalities which are frequently used in information theory.
Keeping this idea in mind, we have developed such inequalities via
coding theory approach.
Abstract: The counting and analysis of blood cells allows the
evaluation and diagnosis of a vast number of diseases. In particular,
the analysis of white blood cells (WBCs) is a topic of great interest to
hematologists. Nowadays the morphological analysis of blood cells is
performed manually by skilled operators. This involves numerous
drawbacks, such as slowness of the analysis and a nonstandard
accuracy, dependent on the operator skills. In literature there are only
few examples of automated systems in order to analyze the white
blood cells, most of which only partial. This paper presents a
complete and fully automatic method for white blood cells
identification from microscopic images. The proposed method firstly
individuates white blood cells from which, subsequently, nucleus and
cytoplasm are extracted. The whole work has been developed using
MATLAB environment, in particular the Image Processing Toolbox.
Abstract: Today, cancer remains one of the major diseases that
lead to death. The main obstacle in chemotherapy as a main cancer
treatment is the toxicity to normal cells due to Multidrug Resistance
(MDR) after the use of anticancer drugs. Proposed solution to
overcome this problem is the use of MDR efflux inhibitor of cinchona
alkaloids which is delivered together with anticancer drugs
encapsulated in the form of polymeric nanoparticles. The particles
were prepared by the hydration method. The characterization of
nanoparticles was particle size, zeta potential, entrapment efficiency
and in vitro drug release. Combination nanoparticle size ranged 29-45
nm with a neutral surface charge. Entrapment efficiency was above
87% for the use quinine, quinidine or cinchonidine in combination
with etoposide. The release test results exhibited that the cinchona
alkaloids release released faster than that of etoposide. Collectively,
cinchona alkaloids can be packaged along with etoposide in
nanomicelles for better cancer therapy.
Abstract: Electrocardiogram (ECG) is considered to be the
backbone of cardiology. ECG is composed of P, QRS & T waves and
information related to cardiac diseases can be extracted from the
intervals and amplitudes of these waves. The first step in extracting
ECG features starts from the accurate detection of R peaks in the
QRS complex. We have developed a robust R wave detector using
wavelets. The wavelets used for detection are Daubechies and
Symmetric. The method does not require any preprocessing therefore,
only needs the ECG correct recordings while implementing the
detection. The database has been collected from MIT-BIH arrhythmia
database and the signals from Lead-II have been analyzed. MatLab
7.0 has been used to develop the algorithm. The ECG signal under
test has been decomposed to the required level using the selected
wavelet and the selection of detail coefficient d4 has been done based
on energy, frequency and cross-correlation analysis of decomposition
structure of ECG signal. The robustness of the method is apparent
from the obtained results.
Abstract: This paper explores the opportunity of using tri-axial
wireless accelerometers for supervised monitoring of sports
movements. A motion analysis system for the upper extremities of
lawn bowlers in particular is developed. Accelerometers are placed
on parts of human body such as the chest to represent the shoulder
movements, the back to capture the trunk motion, back of the hand,
the wrist and one above the elbow, to capture arm movements. These
sensors placement are carefully designed in order to avoid restricting
bowler-s movements. Data is acquired from these sensors in soft-real
time using virtual instrumentation; the acquired data is then
conditioned and converted into required parameters for motion
regeneration. A user interface was also created to facilitate in the
acquisition of data, and broadcasting of commands to the wireless
accelerometers. All motion regeneration in this paper deals with the
motion of the human body segment in the X and Y direction, looking
into the motion of the anterior/ posterior and lateral directions
respectively.
Abstract: In the context of global climate change, flooding and sea level rise is increasingly threatening coastal urban areas, in which large population is continuously concentrated. Dutch experiences in urban water system management provide high reference value for sustainable coastal urban development projects. Preliminary studies shows the urban water system in Almere, a typical Dutch polder city, have three kinds of operational modes, achieving functions as: (1) coastline control – strong multiple damming system prevents from storm surges and maintains sufficient capacity upon risks; (2) high flexibility – large area and widely scattered open water system greatly reduce local runoff and water level fluctuation; (3) internal water maintenance – weir and sluice system maintains relatively stable water level, providing excellent boating and landscaping service, coupling with water circulating model maintaining better water quality. Almere has provided plenty of hints and experiences for ongoing development of coastal cities in emerging economies.
Abstract: This study presents the performance of membrane
bioreactor in treating high phosphate wastewater. The laboratory
scale MBR was operated at permeate flux of 25 L/m2.h with a hollow
fiber membrane (polypropylene, approx. pore size 0.01 - 0.2 μm) at
hydraulic retention time (HRT) of 12 hrs. Scanning electron
microscopy (SEM) and energy diffusive X-ray (EDX) analyzer were
used to characterize the membrane foulants. Results showed that the
removal efficiencies of COD, TSS, NH3-N and PO4
3- were 93, 98, 80
and 30% respectively. On average 91% of influent soluble microbial
products (SMP) were eliminated, with the eliminations of
polysaccharides mostly above 80%. The main fouling resistance was
cake resistance. It should be noted that SMP were found in major
portions of mixed liquor that played a relatively significant role in
membrane fouling. SEM and EDX analyses indicated that the
foulants covering the membrane surfaces comprises not only organic
substances but also inorganic elements including Mg, Ca, Al, K and
P.
Abstract: It is well known that during the developments in the
economic sector and through the financial crises occur everywhere in
the whole world, volatility measurement is the most important
concept in financial time series. Therefore in this paper we discuss
the volatility for Amman stocks market (Jordan) for certain period of
time. Since wavelet transform is one of the most famous filtering
methods and grows up very quickly in the last decade, we compare
this method with the traditional technique, Fast Fourier transform to
decide the best method for analyzing the volatility. The comparison
will be done on some of the statistical properties by using Matlab
program.