Abstract: We demonstrate that it is possible to compute wave function normalization constants for a class of Schr¨odinger type equations by an algorithm which scales linearly (in the number of eigenfunction evaluations) with the desired precision P in decimals.
Abstract: Massive use of places with strong tourist attraction
with the consequent possibility of losing place-identity produces
harmful effects on cities and their users. In order to mitigate this risk,
areas close to such places can be identified so as to widen the
visitor-s range of action and offer alternative activities integrated
with the main site. The cultural places and appropriate activities can
be identified using a method of analysis and design able to trace the
identity of the places, their characteristics and potential, and to
provide a sustainable improvement. The aim of this work is to
propose PlaceMaker as a method of urban analysis and design which
both detects elements that do not feature in traditional mapping and
which constitute the contemporary identity of the places, and
identifies appropriate project interventions. Two final complex maps
– the first of analysis and the second of design – respectively
represent the identity of places and project interventions. In order to
illustrate the method-s potential; the results of the experimentation
carried out in the Trevi-Pantheon route in Rome and the appropriate
interventions to decongest the area are illustrated.
Abstract: This paper presents a new growing neural network for
cluster analysis and market segmentation, which optimizes the size
and structure of clusters by iteratively checking them for multivariate
normality. We combine the recently published SGNN approach [8]
with the basic principle underlying the Gaussian-means algorithm
[13] and the Mardia test for multivariate normality [18, 19]. The new
approach distinguishes from existing ones by its holistic design and
its great autonomy regarding the clustering process as a whole. Its
performance is demonstrated by means of synthetic 2D data and by
real lifestyle survey data usable for market segmentation.
Abstract: In this paper, a new model predictive PID controller
design method for the slip suppression control of EVs (electric
vehicles) is proposed. The proposed method aims to improve the
maneuverability and the stability of EVs by controlling the wheel
slip ratio. The optimal control gains of PID framework are derived
by the model predictive control (MPC) algorithm. There also include
numerical simulation results to demonstrate the effectiveness of the
method.
Abstract: According to the new developments in the field of information and communication technologies, the necessity arises for active use of these new technologies in education. It is clear that the integration of technology in education system will be different for primary-higher education or traditional- distance education. In this study, the subject of the integration of technology for distance education was discussed. The subject was taken from the viewpoint of students. With using the information of student feedback about education program in which new technological medias are used, how can survey variables can be separated into the factors as positive, negative and supporter and how can be redesigned education strategy of the higher education associations with the examining the variables of each determinated factor is explained. The paper concludes with the recommendations about the necessitity of working as a group of different area experts and using of numerical methods in establishing of education strategy to be successful.
Abstract: Industrial robots become useless without end-effectors
that for many instances are in the form of friction grippers.
Commonly friction grippers apply frictional forces to different
objects on the basis of programmers- experiences. This puts a
limitation on the effectiveness of gripping force that may result in
damaging the object. This paper describes various stages of design
and development of a low cost sensor-based robotic gripper that
would facilitate the task of applying right gripping forces to different
objects. The gripper is also equipped with range sensors in order to
avoid collisions of the gripper with objects. It is a fully functional
automated pick and place gripper which can be used in many
industrial applications. Yet it can also be altered or further developed
in order to suit a larger number of industrial activities. The current
design of gripper could lead to designing completely automated robot
grippers able to improve the efficiency and productivity of industrial
robots.
Abstract: In this paper, applying frequency domain approach, a delayed predator-prey fishery model with prey reserve is investigated. By choosing the delay τ as a bifurcation parameter, It is found that Hopf bifurcation occurs as the bifurcation parameter τ passes a sequence of critical values. That is, a family of periodic solutions bifurcate from the equilibrium when the bifurcation parameter exceeds a critical value. The length of delay which preserves the stability of the positive equilibrium is calculated. Some numerical simulations are included to justify the theoretical analysis results. Finally, main conclusions are given.
Abstract: Nowadays e-Learning is more popular, in Vietnam
especially. In e-learning, materials for studying are very important.
It is necessary to design the knowledge base systems and expert
systems which support for searching, querying, solving of
problems. The ontology, which was called Computational Object
Knowledge Base Ontology (COB-ONT), is a useful tool for
designing knowledge base systems in practice. In this paper, a
design method for knowledge base systems in education using
COKB-ONT will be presented. We also present the design of a
knowledge base system that supports studying knowledge and
solving problems in higher mathematics.
Abstract: The pigments covered by film-forming polymers have
opened a prospect to improve the quality of water-based printing
inks. In this study such pigments were prepared by the initiated
polymerization of styrene and methacrylate derivative monomers in
the aqueous pigment dispersions. The formation of polymer films
covering pigment cores depends on the polymerization time and the
ratio of pigment to monomers. At the time of 4 hours and the ratio of
1/10 almost pigment particles are coated by the polymer. The formed
polymer covers of pigments have the average thickness of 5.95 nm.
The size increasing percentage of the coated particles after a week is
4.5 %, about fourteen-fold lower than of the original ones. The
obtained results indicate that the coated pigments are improved
dispersion stability in water medium along with a guarantee for the
optical colour.
Abstract: Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.
Abstract: The influence of copper promoters and reaction
conditions on the formation of alcohols byproducts of a common
Fischer-Tropsch synthesis used iron-based catalysts were investigated.
A good compromise of 28%Cu/FeKLaSiO2 can lead to the
optimization of an improved Fischer-Tropsch catalyst. The product
distribution shifts towards hydrocarbons with increasing the reaction
temperature, while pressure promotes the formation of alcohols. It was
found that the production of either alcohols or hydrocarbons followed
A-S-F distributions, and their α parameters were essentially different
which indicated a competition in the growing chain between the two
species. TPD after acetaldehyde adsorption gave strong evidence of
the insertion of a C1 oxygen-containing species into an alkyl chain.
Abstract: This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.
Abstract: The passive electrical properties of a tissue depends
on the intrinsic constituents and its structure, therefore by measuring
the complex electrical impedance of the tissue it might be possible to
obtain indicators of the tissue state or physiological activity [1].
Complete bio-impedance information relative to physiology and
pathology of a human body and functional states of the body tissue or
organs can be extracted by using a technique containing a fourelectrode
measurement setup. This work presents the estimation
measurement setup based on the four-electrode technique. First, the
complex impedance is estimated by three different estimation
techniques: Fourier, Sine Correlation and Digital De-convolution and
then estimation errors for the magnitude, phase, reactance and
resistance are calculated and analyzed for different levels of
disturbances in the observations. The absolute values of relative
errors are plotted and the graphical performance of each technique is
compared.
Abstract: The ability to predict an accurate temperature
distribution requires the knowledge of the losses, the thermal
characteristics of the materials, and the cooling conditions, all of
which are very difficult to quantify. In this paper, the impact of the
effects of iron and copper losses are investigated separately and
their effects on the heating in various points of the stator of an
induction motor, is highlighted by using two simple tests. In addition,
the effect of a defect, such as an open circuit in a phase of the stator,
on the heating is also obtained by a no-load test.
The squirrel cage induction motor is rated at 2.2 kW; 380 V; 5.2
A; Δ connected; 50 Hz; 1420 rpm and the class of insulation F, has
been thermally tested under several load conditions. Several
thermocouples were placed in strategic points of the stator.
Abstract: A higher order spline interpolated contour obtained
with up-sampling of homogenously distributed coordinates for
segmentation of kidney region in different classes of ultrasound
kidney images has been developed and presented in this paper. The
performance of the proposed method is measured and compared with
modified snake model contour, Markov random field contour and
expert outlined contour. The validation of the method is made in
correspondence with expert outlined contour using maximum coordinate
distance, Hausdorff distance and mean radial distance
metrics. The results obtained reveal that proposed scheme provides
optimum contour that agrees well with expert outlined contour.
Moreover this technique helps to preserve the pixels-of-interest
which in specific defines the functional characteristic of kidney. This
explores various possibilities in implementing computer-aided
diagnosis system exclusively for US kidney images.
Abstract: Taxation as a potent fiscal policy instrument through which infrastructures and social services that drive the development process of any society has been ineffective in Nigeria. The adoption of appropriate measures is, however, a requirement for the generation of adequate tax revenue. This study set out to investigates efficiency and effectiveness in the administration of tax in Nigeria, using Cross River State as a case-study. The methodology to achieve this objective is a qualitative technique using structured questionnaires to survey the three senatorial districts in the state; the central limit theory is adopted as our analytical technique. Result showed a significant degree of inefficiency in the administration of taxes. It is recommended that periodic review and update of tax policy will bring innovation and effectiveness in the administration of taxes. Also proper appropriation of tax revenue will drive development in needed infrastructural and social services.
Abstract: We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster validity index, which decides the final number of clusters.
Abstract: With a development of Hybrid Electric Vehicle(HEV),
A photovoltaic(PV) generation system is used for charging batteries in many cases. A dc/dc converter using PV power for a battery charger
requires a high efficiency. In this paper, A ZVS boost converter using the renewable energies for HEV charger is proposed. Through the theoretical analysis and experimental result, operation modes and characteristics of the proposed topology are verified.
Abstract: The 4G front-end transceiver needs a high
performance which can be obtained mainly with an optimal
architecture and a multi-band Local Oscillator. In this study, we
proposed and presented a new architecture of multi-band frequency
synthesizer based on an Inverse Sine Phase Detector Phase Locked
Loop (ISPD PLL) without any filters and any controlled gain block
and associated with adapted multi band LC tuned VCO using a
several numeric controlled capacitive branches but not binary
weighted. The proposed architecture, based on 0.35μm CMOS
process technology, supporting Multi-band GSM/DCS/DECT/
UMTS/WiMax application and gives a good performances: a phase
noise @1MHz -127dBc and a Factor Of Merit (FOM) @ 1MHz -
186dB and a wide band frequency range (from 0.83GHz to 3.5GHz),
that make the proposed architecture amenable for monolithic
integration and 4G multi-band application.
Abstract: Magnetic carbon nanotubes composites were obtained
by filling carbon nanotubes with paramagnetic iron oxide particles.
Detailed investigation of magnetic behaviour of resulting composites
was done at different temperatures. Measurements indicate that these
functionalized nanotubes are superparamagnetic at room temperature;
however, no superparamagnetism was observed at 125 K and 80 K.
The blocking temperature TB was estimated at 145 K. These magnetic
carbon nanotubes have the potential of being used in a wide range of
applications, in particular, the production of nanofluids, which can be
controlled and steered by appropriate magnetic fields.