Abstract: An artificial neural network (ANN) model is
presented for the prediction of kinematic viscosity of binary mixtures
of poly (ethylene glycol) (PEG) in water as a function of temperature,
number-average molecular weight and mass fraction. Kinematic
viscosities data of aqueous solutions for PEG (0.55419×10-6 –
9.875×10-6 m2/s) were obtained from the literature for a wide range
of temperatures (277.15 - 338.15 K), number-average molecular
weight (200 -10000), and mass fraction (0.0 – 1.0). A three layer
feed-forward artificial neural network was employed. This model
predicts the kinematic viscosity with a mean square error (MSE) of
0.281 and the coefficient of determination (R2) of 0.983. The results
show that the kinematic viscosity of binary mixture of PEG in water
could be successfully predicted using an artificial neural network
model.
Abstract: The data is available in abundance in any business
organization. It includes the records for finance, maintenance,
inventory, progress reports etc. As the time progresses, the data keep
on accumulating and the challenge is to extract the information from
this data bank. Knowledge discovery from these large and complex
databases is the key problem of this era. Data mining and machine
learning techniques are needed which can scale to the size of the
problems and can be customized to the application of business. For
the development of accurate and required information for particular
problem, business analyst needs to develop multidimensional models
which give the reliable information so that they can take right
decision for particular problem. If the multidimensional model does
not possess the advance features, the accuracy cannot be expected.
The present work involves the development of a Multidimensional
data model incorporating advance features. The criterion of
computation is based on the data precision and to include slowly
change time dimension. The final results are displayed in graphical
form.
Abstract: Power consumption is rapidly increased in data centers
because the number of data center is increased and more the scale of
data center become larger. Therefore, it is one of key research items to
reduce power consumption in data center. The peak power of a typical
server is around 250 watts. When a server is idle, it continues to use
around 60% of the power consumed when in use, though vendors are
putting effort into reducing this “idle" power load. Servers tend to
work at only around a 5% to 20% utilization rate, partly because of
response time concerns. An average of 10% of servers in their data
centers was unused. In those reason, we propose dynamic power
management system to reduce power consumption in green data
center. Experiment result shows that about 55% power consumption is
reduced at idle time.
Abstract: Activity-Based Costing (ABC) represents an
alternative paradigm to traditional cost accounting system and
it often provides more accurate cost information for decision
making such as product pricing, product mix, and make-orbuy
decisions. ABC models the causal relationships between
products and the resources used in their production and traces
the cost of products according to the activities through the use
of appropriate cost drivers. In this paper, the implementation
of the ABC in a manufacturing system is analyzed and a
comparison with the traditional cost based system in terms of
the effects on the product costs are carried out to highlight the
difference between two costing methodologies. By using this
methodology, a valuable insight into the factors that cause the
cost is provided, helping to better manage the activities of the
company.
Abstract: A sequential treatment of ozonation followed by a
Fenton or photo-Fenton process, using black light lamps (365 nm) in
this latter case, has been applied to remove a mixture of
pharmaceutical compounds and the generated by-products both in
ultrapure and secondary treated wastewater. The scientifictechnological
innovation of this study stems from the in situ
generation of hydrogen peroxide from the direct ozonation of
pharmaceuticals, and can later be used in the application of Fenton
and photo-Fenton processes. The compounds selected as models
were sulfamethoxazol and acetaminophen. It should be remarked that
the use of a second process is necessary as a result of the low
mineralization yield reached by the exclusive application of ozone.
Therefore, the influence of the water matrix has been studied in terms
of hydrogen peroxide concentration, individual compound
concentration and total organic carbon removed. Moreover, the
concentration of different iron species in solution has been measured.
Abstract: Automatic Extraction of Event information from
social text stream (emails, social network sites, blogs etc) is a vital
requirement for many applications like Event Planning and
Management systems and security applications. The key information
components needed from Event related text are Event title, location,
participants, date and time. Emails have very unique distinctions over
other social text streams from the perspective of layout and format
and conversation style and are the most commonly used
communication channel for broadcasting and planning events.
Therefore we have chosen emails as our dataset. In our work, we
have employed two statistical NLP methods, named as Finite State
Machines (FSM) and Hidden Markov Model (HMM) for the
extraction of event related contextual information. An application
has been developed providing a comparison among the two methods
over the event extraction task. It comprises of two modules, one for
each method, and works for both bulk as well as direct user input.
The results are evaluated using Precision, Recall and F-Score.
Experiments show that both methods produce high performance and
accuracy, however HMM was good enough over Title extraction and
FSM proved to be better for Venue, Date, and time.
Abstract: In this paper, a low noise microwave bandpass filter
(BPF) is presented. This filter is fabricated by modifying the
conventional cross-coupled structure. The spurious response is
improved by using the end open coupled lines, and the influence of the
noise is minimized. Impedance matrix of the open end coupled circuit
clarifies the characteristic of the suppression of the spurious response.
The rejection of spurious suppression region of the proposed filter is
greater than 20 dB from 3-13 GHz. The measured results of the
fabricated filter confirm the concepts of the proposed design and
exhibits high performance.
Abstract: Interactive push VOD system is a new kind of system
that incorporates push technology and interactive technique. It can
push movies to users at high speeds at off-peak hours for optimal
network usage so as to save bandwidth. This paper presents effective
software-based solution for processing mass downstream data at
terminals of interactive push VOD system, where the service can
download movie according to a viewer-s selection. The downstream
data is divided into two catalogs: (1) the carousel data delivered
according to DSM-CC protocol; (2) IP data delivered according to
Euro-DOCSIS protocol. In order to accelerate download speed and
reduce data loss rate at terminals, this software strategy introduces
caching, multi-thread and resuming mechanisms. The experiments
demonstrate advantages of the software-based solution.
Abstract: What influences microsystems (MEMS) and nanosystems (NEMS) innovation teams apart from technology complexity? Based on in-depth interviews with innovators, this research explores the key influences on innovation teams in the early phases of MEMS/NEMS. Projects are rare and may last from 5 to 10 years or more from idea to concept. As fundamental technology development in MEMS/NEMS is highly complex and interdisciplinary by involving expertise from different basic and engineering disciplines, R&D is rather a 'testing of ideas' with many uncertainties than a clearly structured process. The purpose of this study is to explore the innovation teams- environment and give specific insights for future management practices. The findings are grouped into three major areas: people, know-how and experience, and market. The results highlight the importance and differences of innovation teams- composition, transdisciplinary knowledge, project evaluation and management compared to the counterparts from new product development teams.
Abstract: This paper deals with an on-line identification method
of continuous-time Hammerstein systems by using the radial basis
function (RBF) networks and immune algorithm (IA). An unknown
nonlinear static part to be estimated is approximately represented
by the RBF network. The IA is efficiently combined with the
recursive least-squares (RLS) method. The objective function for the
identification is regarded as the antigen. The candidates of the RBF
parameters such as the centers and widths are coded into binary bit
strings as the antibodies and searched by the IA. On the other hand,
the candidates of both the weighting parameters of the RBF network
and the system parameters of the linear dynamic part are updated
by the RLS method. Simulation results are shown to illustrate the
proposed method.
Abstract: Solid dispersions (SD) of curcuminpolyvinylpyrrolidone
in the ratio of 1:2, 1:4, 1:5, 1:6, and 1:8 were
prepared in an attempt to increase the solubility and dissolution.
Solubility, dissolution, powder X-ray diffraction (XRD), differential
scanning calorimetry (DSC) and Fourier transform infrared
spectroscopy (FTIR) of solid dispersions, physical mixtures (PM)
and curcumin were evaluated. Both solubility and dissolution of
curcumin solid dispersions were significantly greater than those
observed for physical mixtures and intact curcumin. The powder
X-ray diffractograms indicated that the amorphous curcumin was
obtained from all solid dispersions. It was found that the optimum
weight ratio for curcumin:PVP K-30 is 1:6. The 1:6 solid dispersion
still in the amorphous from after storage at ambient temperature for 2
years and the dissolution profile did not significantly different from
freshly prepared.
Abstract: Insufficient Quality of Service (QoS) of Voice over
Internet Protocol (VoIP) is a growing concern that has lead the need
for research and study. In this paper we investigate the performance
of VoIP and the impact of resource limitations on the performance of
Access Networks. The impact of VoIP performance in Access
Networks is particularly important in regions where Internet
resources are limited and the cost of improving these resources is
prohibitive. It is clear that perceived VoIP performance, as measured
by mean opinion score [2] in experiments, where subjects are asked
to rate communication quality, is determined by end-to-end delay on
the communication path, delay variation, packet loss, echo, the
coding algorithm in use and noise. These performance indicators can
be measured and the affect in the Access Network can be estimated.
This paper investigates the congestion in the Access Network to the
overall performance of VoIP services with the presence of other
substantial uses of internet and ways in which Access Networks can
be designed to improve VoIP performance. Methods for analyzing
the impact of the Access Network on VoIP performance will be
surveyed and reviewed. This paper also considers some approaches
for improving performance of VoIP by carrying out experiments
using Network Simulator version 2 (NS2) software with a view to
gaining a better understanding of the design of Access Networks.
Abstract: This paper deals with the simulation of a Boost Power Factor Correction (PFC) Converter with Electro Magnetic Interference (EMI) Filter. The diode rectifier with output capacitor gives poor power factor. The Boost Converter of PFC Circuit is analyzed and then simulated with diode rectifier. The Boost PFC Converter with EMI Filter is simulated for resistive load. The power factor is improved using the proposed converter.
Abstract: The Swine flu outbreak in humans is due to a new
strain of influenza A virus subtype H1N1 that derives in part from
human influenza, avian influenza, and two separated strains of swine
influenza. It can be transmitted from human to human. A
mathematical model for the transmission of Swine flu is developed in
which the human populations are divided into two classes, the risk
and non-risk human classes. Each class is separated into susceptible,
exposed, infectious, quarantine and recovered sub-classes. In this
paper, we formulate the dynamical model of Swine flu transmission
and the repetitive contacts between the people are also considered.
We analyze the behavior for the transmission of this disease. The
Threshold condition of this disease is found and numerical results are
shown to confirm our theoretical predictions.
Abstract: Protein 3D structure prediction has always been an
important research area in bioinformatics. In particular, the
prediction of secondary structure has been a well-studied research
topic. Despite the recent breakthrough of combining multiple
sequence alignment information and artificial intelligence algorithms
to predict protein secondary structure, the Q3 accuracy of various
computational prediction algorithms rarely has exceeded 75%. In a
previous paper [1], this research team presented a rule-based method
called RT-RICO (Relaxed Threshold Rule Induction from Coverings)
to predict protein secondary structure. The average Q3 accuracy on
the sample datasets using RT-RICO was 80.3%, an improvement
over comparable computational methods. Although this demonstrated
that RT-RICO might be a promising approach for predicting
secondary structure, the algorithm-s computational complexity and
program running time limited its use. Herein a parallelized
implementation of a slightly modified RT-RICO approach is
presented. This new version of the algorithm facilitated the testing of
a much larger dataset of 396 protein domains [2]. Parallelized RTRICO
achieved a Q3 score of 74.6%, which is higher than the
consensus prediction accuracy of 72.9% that was achieved for the
same test dataset by a combination of four secondary structure
prediction methods [2].
Abstract: Current spectrums of a high power induction machine was calculated for the cases of full symmetry, static and dynamic eccentricity. The calculations involve integration of 93 electrical plus four mechanical ordinary differential equations. Electrical equations account for variable inductances affected by slotting and eccentricities. The calculations were followed by Fourier analysis of the stator currents in steady state operation. The paper presents the stator current spectrums in full symmetry, static and dynamic eccentricity cases, and demonstrates the harmonics present in each case. The effect of dynamic eccentricity is demonstrating via comparing the current spectrums related to dynamic eccentricity cases with the full symmetry one. The paper includes one case study, refers to dynamic eccentricity, to present the spectrum of the measured current and demonstrate the existence of the harmonics related to dynamic eccentricity. The zooms of current spectrums around the main slot harmonic zone are included to simplify the comparison and prove the existence of the dynamic eccentricity harmonics in both calculated and measured current spectrums.
Abstract: This study aimed to evaluate regional soil Borkhar of
the metals Lead has been made. In this field study fires visits to the
regions. The limit of this study located in the East refineries,
petrochemical and power plant to 20 km was selected. The 41 soil
samples from depths of 0 to 10 cm in area and were randomized. Soil
samples were transported to the laboratory and by air was dry and
passed through 2-mil thickness sieve. In the laboratory of physical
and chemical characteristics and concentrations of total absorption
was measured. The results showed that the amount of lead in soil in
many parts of the range higher than the standard limit. Survey maps
show that the lead spatial distribution of the region does not special
pattern.
Abstract: The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.
Abstract: This paper describes a one-dimensional numerical model for natural gas production from the dissociation of methane hydrate in hydrate-capped gas reservoir under depressurization and thermal stimulation. Some of the hydrate reservoirs discovered are overlying a free-gas layer, known as hydrate-capped gas reservoirs. These reservoirs are thought to be easiest and probably the first type of hydrate reservoirs to be produced. The mathematical equations that can be described this type of reservoir include mass balance, heat balance and kinetics of hydrate decomposition. These non-linear partial differential equations are solved using finite-difference fully implicit scheme. In the model, the effect of convection and conduction heat transfer, variation change of formation porosity, the effect of using different equations of state such as PR and ER and steam or hot water injection are considered. In addition distributions of pressure, temperature, saturation of gas, hydrate and water in the reservoir are evaluated. It is shown that the gas production rate is a sensitive function of well pressure.
Abstract: In this paper, we first give the representation of the general solution of the following least-squares problem (LSP): Given matrices X ∈ Rn×p, B ∈ Rp×p and A0 ∈ Rr×r, find a matrix A ∈ Rn×n such that XT AX − B = min, s. t. A([1, r]) = A0, where A([1, r]) is the r×r leading principal submatrix of the matrix A. We then consider a best approximation problem: given an n × n matrix A˜ with A˜([1, r]) = A0, find Aˆ ∈ SE such that A˜ − Aˆ = minA∈SE A˜ − A, where SE is the solution set of LSP. We show that the best approximation solution Aˆ is unique and derive an explicit formula for it. Keyw