Abstract: Composting is the process in which municipal solid
waste (MSW) and other organic waste materials such as biosolids
and manures are decomposed through the action of bacteria and other
microorganisms into a stable granular material which, applied to
land, as soil conditioner. Microorganisms, especially those that are
able to degrade polymeric organic material have a key role in speed
up this process. The aim of this study has been established to
isolation of microorganisms with high ability to production
extracellular enzymes for degradation of natural polymers that are
exists in MSW for decreasing time of degradation phase. Our
experimental study for isolation designed in two phases: in first
phase we isolated degrading microorganism with selected media that
consist a special natural polymer such as cellulose, starch, lipids and
etc as sole source of carbon. In second phase we selected
microorganism that had high degrading enzyme production with
enzymatic assay for seed production. However, our findings in pilot
scale have indicated that usage of this microbial consortium had high
efficiency for decreasing degradation phase.
Abstract: Multicast transmissions allow an host (the source) to send only one flow bound for a group of hosts (the receivers). Any equipment eager to belong to the group may explicitly register itself to that group via its multicast router. This router will be given the responsibility to convey all information relating to the group to all registered hosts. However in an environment in which the final receiver or the source frequently moves, the multicast flows need particular treatment. This constitutes one of the multicast transmissions problems around which several proposals were made in the Mobile IPv6 case in general. In this article, we describe the problems involved in this IPv6 multicast mobility and the existing proposals for their resolution. Then architecture will be proposed aiming to satisfy and optimize these transmissions in the specific case of a mobile multicast receiver in NC-HMIPv6 environment.
Abstract: If science is supposed to gain greater social
relevance and acceptance, researchers must not only relate to
the broader public, but also promote intercourse within the
ivory tower itself. The latter process has been under way
successfully for a number of years in the form of
transdisciplinary research initiatives. What is still lacking is a
broad debate about the necessity to look around properly and
face up to opposing views on one and the same topic within
our own discipline.
Abstract: all of religions free towards society in Kazakhstan. Considering that Islam is more widespread religion in the region, Islamic industry is developing sector of Economy. There are some new sectors of Halal (Islamic) industry, which have importance for state developing on the whole. One of the youngest sectors of Halal industry is Islamic tourism, which became an object of disputes and led to dilemma, such as Islamic tourism is a result of a Religious revival and Islamic tourism is a new trend of Tourism. The paper was written under the research project “Islam in modern Kazakhstan: the nature and outcome of the religious revival".
Abstract: In this paper, we propose a texture feature-based
language identification using wavelet-domain BDIP (block difference
of inverse probabilities) and BVLC (block variance of local
correlation coefficients) features and FFT (fast Fourier transform)
feature. In the proposed method, wavelet subbands are first obtained
by wavelet transform from a test image and denoised by Donoho-s
soft-thresholding. BDIP and BVLC operators are next applied to the
wavelet subbands. FFT blocks are also obtained by 2D (twodimensional)
FFT from the blocks into which the test image is
partitioned. Some significant FFT coefficients in each block are
selected and magnitude operator is applied to them. Moments for each
subband of BDIP and BVLC and for each magnitude of significant
FFT coefficients are then computed and fused into a feature vector. In
classification, a stabilized Bayesian classifier, which adopts variance
thresholding, searches the training feature vector most similar to the
test feature vector. Experimental results show that the proposed
method with the three operations yields excellent language
identification even with rather low feature dimension.
Abstract: In this paper, 3X3 routing nodes are proposed to
provide speedup and parallel processing capability in Data Vortex
network architectures. The new design not only significantly
improves network throughput and latency, but also eliminates the
need for distributive traffic control mechanism originally embedded
among nodes and the need for nodal buffering. The cost effectiveness
is studied by a comparison study with the previously proposed 2-
input buffered networks, and considerable performance enhancement
can be achieved with similar or lower cost of hardware. Unlike
previous implementation, the network leaves small probability of
contention, therefore, the packet drop rate must be kept low for such
implementation to be feasible and attractive, and it can be achieved
with proper choice of operation conditions.
Abstract: Today-s Voltage Regulator Modules (VRMs) face increasing design challenges as the number of transistors in microprocessors increases per Moore-s Law. These challenges have recently become even more demanding as microprocessors operate at sub voltage range at significantly high current. This paper presents a new multiphase topology with cell configuration for improved performance in low voltage and high current applications. A lab scale hardware prototype of the new topology was design and constructed. Laboratory tests were performed on the proposed converter and compared with a commercially available VRM. Results from the proposed topology exhibit improved performance compared to the commercially available counterpart.
Abstract: This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.
Abstract: The main issue in sweetening natural gas is H2S
dissociation. The present study is concerned with simulating thermal
dissociation of H2S in industrial natural gas carbon black furnace.
The comparison of calculated results against experimental
measurements shows good agreement. The results show that sulfur
derived from H2S thermal dissociation peaked at φ=0.95. H2S
thermal dissociation is enhanced in equivalence ratio upper than 1
and H2S oxidization is increased in equivalence ratio lower than 1.
H2 concentration of H2S thermal dissociation is increased with
increase of equivalence ratio up to 1. Also, H2S concentration
decreased in outlet as equivalence ratio increases. H2S thermal
dissociation to hydrogen and Sulfur reduces its toxic characteristics
and make economical benefits.
Abstract: The majority of existing predictors for time series are
model-dependent and therefore require some prior knowledge for the
identification of complex systems, usually involving system
identification, extensive training, or online adaptation in the case of
time-varying systems. Additionally, since a time series is usually
generated by complex processes such as the stock market or other
chaotic systems, identification, modeling or the online updating of
parameters can be problematic. In this paper a model-free predictor
(MFP) for a time series produced by an unknown nonlinear system or
process is derived using tracking theory. An identical derivation of the
MFP using the property of the Newton form of the interpolating
polynomial is also presented. The MFP is able to accurately predict
future values of a time series, is stable, has few tuning parameters and
is desirable for engineering applications due to its simplicity, fast
prediction speed and extremely low computational load. The
performance of the proposed MFP is demonstrated using the
prediction of the Dow Jones Industrial Average stock index.
Abstract: Nanomaterials have attracted considerable attention
during the last two decades, due to their unusual electrical, mechanical
and other physical properties as compared with their bulky
counterparts. The mechanical properties of nanostructured materials
show strong size dependency, which has been explained within the
framework of continuum mechanics by including the effects of surface
stress. The size-dependent deformations of two-dimensional
nanosized structures with surface effects are investigated in the paper
by the finite element method. Truss element is used to evaluate the
contribution of surface stress to the total potential energy and the
Gurtin and Murdoch surface stress model is implemented with
ANSYS through its user programmable features. The proposed
approach is used to investigate size-dependent stress concentration
around a nanosized circular hole and the size-dependent effective
moduli of nanoporous materials. Numerical results are compared with
available analytical results to validate the proposed modeling
approach.
Abstract: Software crisis refers to the situation in which the developers are not able to complete the projects within time and budget constraints and moreover these overscheduled and over budget projects are of low quality as well. Several methodologies have been adopted form time to time to overcome this situation and now in the focus is component based software engineering. In this approach, emphasis is on reuse of already existing software artifacts. But the results can not be achieved just by preaching the principles; they need to be practiced as well. This paper highlights some of the very basic elements of this approach, which has to be in place to get the desired goals of high quality, low cost with shorter time-to-market software products.
Abstract: According to conjugate gradient algorithm, a new consensus protocol algorithm of discrete-time multi-agent systems is presented, which can achieve finite-time consensus. Finally, a numerical example is given to illustrate our theoretical result.
Abstract: The aim of this article is to narrate the utility of novel simulation approach i.e. convolution method to predict blood concentration of drug utilizing dissolution data of salbutamol sulphate microparticulate formulations with different release patterns (1:1, 1:2 and 1:3, drug:polymer). Dissolution apparatus II USP 2007 and 900 ml double distilled water stirrd at 50 rpm was employed for dissolution analysis. From dissolution data, blood drug concentration was determined, and in return predicted blood drug concentration data was used to calculate the pharmacokinetic parameters i.e. Cmax, Tmax, and AUC. Convolution is a good biwaiver technique; however its better utility needs it application in the conditions where biorelevant dissolution media are used.
Abstract: The world is moving rapidly toward the deployment
of information and communication systems. Nowadays, computing
systems with their fast growth are found everywhere and one of the main challenges for these systems is increasing attacks and security threats against them. Thus, capturing, analyzing and verifying security requirements becomes a very important activity in
development process of computing systems, specially in developing
systems such as banking, military and e-business systems. For
developing every system, a process model which includes a process,
methods and tools is chosen. The Rational Unified Process (RUP) is
one of the most popular and complete process models which is used
by developers in recent years. This process model should be extended to be used in developing secure software systems. In this
paper, the Requirement Discipline of RUP is extended to improve RUP for developing secure software systems. These proposed extensions are adding and integrating a number of Activities, Roles,
and Artifacts to RUP in order to capture, document and model threats
and security requirements of system. These extensions introduce a
group of clear and stepwise activities to developers. By following these activities, developers assure that security requirements are
captured and modeled. These models are used in design, implementation and test activitie
Abstract: This paper compares planning results of the electricity and water generation inventory up to year 2030 in the State of
Kuwait. Currently, the generation inventory consists of oil and gas fired technologies only. The planning study considers two main cases. The first case, Reference case, examines a generation inventory based on oil and gas fired generation technologies only.
The second case examines the inclusion of renewables as part of the generation inventory under two scenarios. In the first scenario, Ref-RE, renewable build-out is based on optimum economic performance
of overall generation system. Result shows that the optimum installed
renewable capacity with electric energy generation of 11% . In the second scenario, Ref-RE20, the renewable capacity build-out is
forced to provide 20% of electric energy by 2030. The respective energy systems costs of Reference, Ref-RE and Ref-RE20 case
scenarios reach US dollar 24, 10 and 14 billion annually in 2030.
Abstract: The need of high frame-rate imaging has been triggered by the new applications of ultrasound imaging to transient elastography and real-time 3D ultrasound. Using plane wave excitation (PWE) is one of the methods to achieve very high frame-rate imaging since an image can be formed with a single insonification. However, due to the lack of transmit focusing, the image quality with PWE is lower compared with those using conventional focused transmission. To solve this problem, we propose a filter-retrieved transmit focusing (FRF) technique combined with cross-correlation weighting (FRF+CC weighting) for high frame-rate imaging with PWE. A restrospective focusing filter is designed to simultaneously minimize the predefined sidelobe energy associated with single PWE and the filter energy related to the signal-to-noise-ratio (SNR). This filter attempts to maintain the mainlobe signals and to reduce the sidelobe ones, which gives similar mainlobe signals and different sidelobes between the original PWE and the FRF baseband data. Normalized cross-correlation coefficient at zero lag is calculated to quantify the degree of similarity at each imaging point and used as a weighting matrix to the FRF baseband data to further suppress sidelobes, thus improving the filter-retrieved focusing quality.
Abstract: Knowledge capabilities are increasingly important for
the innovative technology enterprises to enhance the business
performance in terms of product competitiveness, innovation and
sales. Recognition of the company capability by auditing allows them
to further pursue advancement, strategic planning and hence gain
competitive advantages. This paper attempts to develop an
Organizations- Knowledge Capabilities Assessment (OKCA) method
to assess the knowledge capabilities of technology companies. The
OKCA is a questionnaire-based assessment tool which has been
developed to uncover the impact of various knowledge capabilities on
different organizational performance. The collected data is then
analyzed to find out the crucial elements for different technological
companies. Based on the results, innovative technology enterprises are
able to recognize the direction for further improvement on business
performance and future development plan. External environmental
factors affecting organization performance can be found through the
further analysis of some selected reference companies.
Abstract: This paper investigates the aerodynamic characters of a model ducted fan system, analyses the basic principle of the effect of thrust promotion and torque reduction, discovers the relationship between the revolutions per minute(RPM) of the fan and the characters of thrust, as well as system torque. Firstly a model ducted fan has been designed and manufactured according to the specific structure of flow field, then CFD simulation has been carried out to analyze such aerodynamics, finally bench tests have been used to validate the simulation results and system configuration.
Abstract: In this paper, we proposed the effects of Mo thickness
on the properties of AZO/Mo/AZO multilayer thin films for
opto-electronics applications. The structural, optical and electrical
properties of AZO/Mo/AZO thin films were investigated.
Optimization of the thin films coatings resulted with low resistivity of
9.98 × 10-5 )-cm, mobility of 12.75 cm2/V-s, carrier concentration of
1.05 × 1022 cm-3, maximum transmittance of 79.13% over visible
spectrum of 380 – 780 nm and Haacke figure of merit (FOM) are 5.95
× 10-2 )-1 under Mo layer thickness of 15 nm. These results indicate an
alternative candidate for use as a transparent electrode in solar cells
and various displays applications.