Abstract: This paper introduces a mixed integer programming model to find the optimum development plan for port Anzali. The model minimizes total system costs taking into account both port infrastructure costs and shipping costs. Due to the multipurpose function of the port, the model consists of 1020 decision variables and 2490 constraints. Results of the model determine the optimum number of berths that should be constructed in each period and for each type of cargo. In addition to, the results of sensitivity analysis on port operation quantity provide useful information for managers to choose the best scenario for port planning with the lowest investment risks. Despite all limitations-due to data availability-the model offers a straightforward decision tools to port planners aspiring to achieve optimum port planning steps.
Abstract: In the last decade, carbohydrates have attracted great
attention as renewable resources for the chemical industry.
Carbohydrates are abundantly found in nature in the form of
monomers, oligomers and polymers, or as components of
biopolymers and other naturally occurring substances. As natural
products, they play important roles in conferring certain physical,
chemical, and biological properties to their carrier molecules.The
synthesis of this particular carbohydrate glycomonomer is part of our
work to obtain biodegradable polymers. Our current paper describes
the synthesis and characterization of a novel carbohydrate
glycomonomer starting from D-glucose, in several synthesis steps,
that involve the protection/deprotection of the D-glucose ring via
acetylation, tritylation, then selective deprotection of the aromaticaliphatic
protective group, in order to obtain 1,2,3,4-tetra-O-acetyl-
6-O-allyl-β-D-glucopyranose. The glycomonomer was then obtained
by the allylation in drastic conditions of 1,2,3,4-tetra-O-acetyl-6-Oallyl-
β-D-glucopyranose with allylic alcohol in the presence of
stannic chloride, in methylene chloride, at room temperature. The
proposed structure of the glycomonomer, 2,3,4-tri-O-acetyl-1,6-di-
O-allyl-β-D-glucopyranose, was confirmed by FTIR, NMR and
HPLC-MS spectrometry. This glycomonomer will be further
submitted to copolymerization with certain acrylic or methacrylic
monomers in order to obtain competitive plastic materials for
applications in the biomedical field.
Abstract: Nowadays in applications of renewable energy sources
it is important to develop powerful and energy-saving photovoltaic
converters and to keep the prescriptions of the standards. In grid
connected PV converters the obvious solution to increase the
efficiency is to reduce the switching losses. Our new developed
control method reduces the switching losses and keeps the limitations
of the harmonic distortion standards. The base idea of the method is
the utilization of 3-state control causing discontinuous current mode
at low input power. In the following sections the control theory, the
realizations and the simulation results are presented.
Abstract: Embedding and extraction of a secret information as
well as the restoration of the original un-watermarked image is
highly desirable in sensitive applications like military, medical, and
law enforcement imaging. This paper presents a novel reversible
data-hiding method for digital images using integer to integer
wavelet transform and companding technique which can embed and
recover the secret information as well as can restore the image to its
pristine state. The novel method takes advantage of block based
watermarking and iterative optimization of threshold for companding
which avoids histogram pre and post-processing. Consequently, it
reduces the associated overhead usually required in most of the
reversible watermarking techniques. As a result, it keeps the
distortion small between the marked and the original images.
Experimental results show that the proposed method outperforms the
existing reversible data hiding schemes reported in the literature.
Abstract: Drought is one of the most damaging climate-related
hazards, it is generally considered as a prolonged absence of
precipitation. This normal and recurring climate phenomenon had
plagued civilization throughout history because of the negative
impacts on economical, environmental and social sectors. Drought
characteristics are thus recognized as important factors in water
resources planning and management. The purpose of this study is to
detect the changes in drought frequency, persistence and severity
in the Ruhr river basin. The frequency of drought events was
calculated using the Standardized Precipitation Index (SPI). Used
data are daily precipitation records from seven meteorological
stations covering the period 1961-2007. The main benefit of the
application of this index is its versatility, only rainfall data is required
to deliver five major dimensions of a drought : duration, intensity,
severity, magnitude, and frequency. Furthermore, drought can be
calculated in different time steps. In this study SPI was calculated for
1, 3, 6, 9, 12, and 24 months. Several drought events were detected
in the covered period, these events contain mild, moderate and severe
droughts. Also positive and negative trends in the SPI values were
observed.
Abstract: Epstein-Barr virus (EBV) is implicated in the pathogenesis of the endemic Burkitt-s lymphoma (BL). The EBVpositive BL-derived cell lines initially maintain the original tumor phenotype of EBV infection (latency I, LatI), but most of them drift toward a lymphoblast phenotype of EBV latency III (LatIII) during in vitro culturing. The aim of the present work was to characterize the B-cell subsets in EBV-positive BL cell lines and to verify whether a particular cell subset correlates with the type of EBV infection. The phenotype analysis of two EBV-negative and eleven EBV-positive (three of LatI and eight of LatIII) BL cell lines was performed by polychromatic flow cytomery, based on expression pattern of CD19, CD10, CD38, CD27, and CD5 markers. Two cell subsets, CD19+CD10+ and CD19+CD10-, were defined in LatIII BL cell lines. In both subsets, the CD27 and CD5 cell surface expression was detected in a proportion of the cells.
Abstract: The purpose of this paper primarily intends to develop GIS interface for estimating sequences of stream-flows at ungauged stations based on known flows at gauged stations. The integrated GIS interface is composed of three major steps. The first, precipitation characteristics using statistical analysis is the procedure for making multiple linear regression equation to get the long term mean daily flow at ungauged stations. The independent variables in regression equation are mean daily flow and drainage area. Traditionally, mean flow data are generated by using Thissen polygon method. However, method for obtaining mean flow data can be selected by user such as Kriging, IDW (Inverse Distance Weighted), Spline methods as well as other traditional methods. At the second, flow duration curve (FDC) is computing at unguaged station by FDCs in gauged stations. Finally, the mean annual daily flow is computed by spatial interpolation algorithm. The third step is to obtain watershed/topographic characteristics. They are the most important factors which govern stream-flows. In summary, the simulated daily flow time series are compared with observed times series. The results using integrated GIS interface are closely similar and are well fitted each other. Also, the relationship between the topographic/watershed characteristics and stream flow time series is highly correlated.
Abstract: XML is an important standard of data exchange and
representation. As a mature database system, using relational database
to support XML data may bring some advantages. But storing XML in
relational database has obvious redundancy that wastes disk space,
bandwidth and disk I/O when querying XML data. For the efficiency
of storage and query XML, it is necessary to use compressed XML
data in relational database. In this paper, a compressed relational
database technology supporting XML data is presented. Original
relational storage structure is adaptive to XPath query process. The
compression method keeps this feature. Besides traditional relational
database techniques, additional query process technologies on
compressed relations and for special structure for XML are presented.
In this paper, technologies for XQuery process in compressed
relational database are presented..
Abstract: Clustering unstructured text documents is an
important issue in data mining community and has a number of
applications such as document archive filtering, document
organization and topic detection and subject tracing. In the real
world, some of the already clustered documents may not be of
importance while new documents of more significance may evolve.
Most of the work done so far in clustering unstructured text
documents overlooks this aspect of clustering. This paper, addresses
this issue by using the Fading Function. The unstructured text
documents are clustered. And for each cluster a statistics structure
called Cluster Profile (CP) is implemented. The cluster profile
incorporates the Fading Function. This Fading Function keeps an
account of the time-dependent importance of the cluster. The work
proposes a novel algorithm Clustering n-ary Merge Algorithm
(CnMA) for unstructured text documents, that uses Cluster Profile
and Fading Function. Experimental results illustrating the
effectiveness of the proposed technique are also included.
Abstract: In this paper, an approach to reduce the computation steps required by fast neural networksfor the searching process is presented. The principle ofdivide and conquer strategy is applied through imagedecomposition. Each image is divided into small in sizesub-images and then each one is tested separately usinga fast neural network. The operation of fast neuralnetworks based on applying cross correlation in thefrequency domain between the input image and theweights of the hidden neurons. Compared toconventional and fast neural networks, experimentalresults show that a speed up ratio is achieved whenapplying this technique to locate human facesautomatically in cluttered scenes. Furthermore, fasterface detection is obtained by using parallel processingtechniques to test the resulting sub-images at the sametime using the same number of fast neural networks. Incontrast to using only fast neural networks, the speed upratio is increased with the size of the input image whenusing fast neural networks and image decomposition.
Abstract: Plant tissue culture is an important in vitro technology applied for agricultural and industrial production. A sterile condition of culture medium is one of the main aspects. The alternative technique for medium sterilization to replace autoclaving was carried out. For sterilization of plant tissue culture medium without autoclaving, ten commercial pure essential oils and 5 disinfectants were tested. Each essential oil or disinfectant was added to a 20-mL Murashige and Skoog (MS) medium before medium was solidified in a 120-mL container, kept for 2 weeks before evaluating sterile conditions. Treated media, supplemented with essential oils or disinfectants, were compared to control medium, autoclaved at 121 degree Celsius for 15 min. Sterile conditions of MS medium were found 100% from betel oil or clove oil (18 mL/20 mL medium), cinnamon oil (36 mL/20 mL medium), lavender oil or holy basil oil (108 mL/20 mL medium), and lemon oil or tea tree oil or turmeric oil (252 mL/20 mL medium), compared to 100% sterile condition from autoclaved medium. For disinfectants, 2% iodine + 2.4% potassium iodide, 2% merbromine solution, 10% povidone-iodine, 6% sodium hypochlorite or 0.1% thimerosal at 36 mL/20 mL medium provided 100% sterile conditions. Furthermore, growth of new shoots from chrysanthemum node explants on treated media (fresh weight, shoot length, root length and number of node) were also reported and discussed in the comparison of those on autoclaved medium.
Abstract: Production of biogas from bakery waste was enhanced
by additional bacterial cell. This study was divided into 2 steps. First
step, grease waste from bakery industry-s grease trap was initially
degraded by Pseudomonas aeruginosa. The concentration of byproduct,
especially glycerol, was determined and found that glycerol
concentration increased from 12.83% to 48.10%. Secondary step, 3
biodigesters were set up in 3 different substrates: non-degraded waste
as substrate in first biodigester, degraded waste as substrate in
secondary biodigester, and degraded waste mixed with swine manure
in ratio 1:1 as substrate in third biodigester. The highest
concentration of biogas was found in third biodigester that was
44.33% of methane and 63.71% of carbon dioxide. The lower
concentration at 24.90% of methane and 18.98% of carbon dioxide
was exhibited in secondary biodigester whereas the lowest was found
in non-degraded waste biodigester. It was demonstrated that the
biogas production was greatly increased with the initial grease waste
degradation by Pseudomonas aeruginosa.
Abstract: In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.
Abstract: In this paper, an analytical approach is used to study the coupled lateral-torsional vibrations of laminated composite beam. It is known that in such structures due to the fibers orientation in various layers, any lateral displacement will produce a twisting moment. This phenomenon is modeled by the bending-twisting material coupling rigidity and its main feature is the coupling of lateral and torsional vibrations. In addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies. Then, the governing differential equations are derived using the Hamilton-s principle and the mathematical model matches the Timoshenko beam model when neglecting the effect of bending-twisting rigidity. The equations of motion which form a system of three coupled PDEs are solved analytically to study the free vibrations of the beam in lateral and rotational modes due to the bending, as well as the torsional mode caused by twisting. The analytic solution is carried out in three steps: 1) assuming synchronous motion for the kinematic variables which are the lateral, rotational and torsional displacements, 2) solving the ensuing eigenvalue problem which contains three coupled second order ODEs and 3) imposing different boundary conditions related to combinations of simply, clamped and free end conditions. The resulting natural frequencies and mode shapes are compared with similar results in the literature and good agreement is achieved.
Abstract: Atherosclerosis was identified as a chronic inflammatory process resulting from interactions between plasma lipoproteins, cellular components (monocyte, macrophages, T lymphocytes, endothelial cells and smooth muscle cells) and the extracellular matrix of the arterial wall. Several types of genes were known to express during formation of atherosclerosis. This study is carried out to identify unknown differentially expressed gene (DEG) in atherogenesis. Rabbit’s aorta tissues were stained by H&E for histomorphology. GeneFishing™ PCR analysis was performed from total RNA extracted from the aorta tissues. The DNA fragment from DEG was cloned, sequenced and validated by Real-time PCR. Histomorphology showed intimal thickening in the aorta. DEG detected from ACP-41 was identified as cathepsin B gene and showed upregulation at week-8 and week-12 of atherogenesis. Therefore, ACP-based GeneFishing™ PCR facilitated identification of cathepsin B gene which was differentially expressed during development of atherosclerosis.
Abstract: An electric power system includes a generating, a
transmission, a distribution, and consumers subsystems. An electrical
power network in Tanzania keeps growing larger by the day and
become more complex so that, most utilities have long wished for
real-time monitoring and remote control of electrical power system
elements such as substations, intelligent devices, power lines,
capacitor banks, feeder switches, fault analyzers and other physical
facilities. In this paper, the concept of automation of management of
power systems from generation level to end user levels was
determined by using Power System Simulator for Engineering
(PSS/E) version 30.3.2.
Abstract: This paper presents the work of signal discrimination
specifically for Electrocardiogram (ECG) waveform. ECG signal is
comprised of P, QRS, and T waves in each normal heart beat to
describe the pattern of heart rhythms corresponds to a specific
individual. Further medical diagnosis could be done to determine any
heart related disease using ECG information. The emphasis on QRS
Complex classification is further discussed to illustrate the
importance of it. Pan-Tompkins Algorithm, a widely known
technique has been adapted to realize the QRS Complex
classification process. There are eight steps involved namely
sampling, normalization, low pass filter, high pass filter (build a band
pass filter), derivation, squaring, averaging and lastly is the QRS
detection. The simulation results obtained is represented in a
Graphical User Interface (GUI) developed using MATLAB.
Abstract: MANEMO is the integration of Network Mobility
(NEMO) and Mobile Ad Hoc Network (MANET). A MANEMO
node has an interface to both a MANET and NEMO network, and
therefore should choose the optimal interface for packet delivery,
however such a handover between interfaces will introduce packet
loss. We define the steps necessary for a MANEMO handover,
using Mobile IP and NEMO to signal the new binding to the
relevant Home Agent(s). The handover steps aim to minimize the
packet loss by avoiding waiting for Duplicate Address Detection
and Neighbour Unreachability Detection. We present expressions for
handover delay and packet loss, and then use numerical examples to
evaluate a MANEMO handover. The analysis shows how the packet
loss depends on level of nesting within NEMO, the delay between
Home Agents and the load on the MANET, and hence can be used
to developing optimal MANEMO handover algorithms.
Abstract: In the last few years, several steps were taken in order
to improve the quality of corporate governance for Romanian listed
companies. Higher standards of corporate governance is documented
in the literature to lead to a better information environment, and,
consequently, to increase analysts forecast accuracy. Accordingly, the
purpose of this paper is to investigate the extent to which corporate
governance policies affect analysts forecasts for companies listed on
Bucharest Stock Exchange. The results showed that there is indeed a
negative correlation between a corporate governance index – used as
a proxy for the quality of corporate governance practices - and
analysts forecast errors.
Abstract: The aim of this study is to identify the conditions of
implementation for reconfigurability in summarizing past flexible
manufacturing systems (FMS) research by drawing overall
conclusions from many separate High Performance Manufacturing
(HPM) studies. Meta-analysis will be applied to links between HPM
programs and their practices related to FMS and manufacturing
performance with particular reference to responsiveness performance.
More specifically, an application of meta-analysis will be made with
reference to two of the main steps towards the development of an
empirically-tested theory: testing the adequacy of the measurement of
variables and testing the linkages between the variables.