Abstract: To respond to the Kyoto Protocol, the policy of Payment for Environmental Service (PES), which was entitled “Plain Landscape Afforestation Program (PLAP)", was certified by Executive Yuan in Taiwan on 31 August 2001 and has been implementing for six years since 1 January 2002. Although the PLAP has received a lot of positive comments, there are still many difficulties during the process of implementation, such as insufficient technology for afforestation, private landowners- low interests in participating in PLAP, insufficient subsidies, and so on, which are potential threats that hinder the PLAP from moving forward in future. In this paper, selecting Ping-Tung County in Taiwan as a sample region and targeting those private landowners with and without intention to participate in the PLAP, respectively, we conduct an empirical analysis based on the Logit model to investigate the factors that determine whether those private landowners join the PLAP, so as to realize the incentive effects of the PLAP upon the personal decision on afforestation. The possible factors that might determine private landowner-s participation in the PLAP include landowner-s characteristics, cropland characteristics, as well as policy factors. Among them, the policy factors include afforestation subsidy amount (+), duration of afforestation subsidy (+), the rules on adjoining and adjacent areas (+), and so on, which do not reach the remarkable level in statistics though, but the directions of variable signs are consistent with the intuition behind the policy. As for the landowners- characteristics, each of age (+), education level (–), and annual household income (+) variables reaches 10% of the remarkable level in statistics; as for the cropland characteristics, each of cropland area (+), cropland price (–), and the number of cropland parcels (–) reaches 1% of the remarkable level in statistics. In light of the above, the cropland characteristics are the dominate factor that determines the probability of landowner-s participation in the PLAP. In the Logit model established by this paper, the probability of correctly estimating nonparticipants is 98%, the probability of correctly estimating the participants is 71.8%, and the probability for the overall estimation is 95%. In addition, Hosmer-Lemeshow test and omnibus test also revealed that the Logit model in this paper may provide fine goodness of fit and good predictive power in forecasting private landowners- participation in this program. The empirical result of this paper expects to help the implementation of the afforestation programs in Taiwan.
Abstract: Pomegranate and pomegranate juices (PJs) have taken
great attention for their health benefits in the last years. As there is an
increasing concern about potential health benefits of ellagic acid, it is
of great interest to evaluate alterations in ellagic acid concentration of
commercial PJs. The purpose of this study is to analyze total
phenolic, free and total ellagic acid content of six commercial PJs
sold in Turkish markets using HPLC.
The results showed that some commercial PJs had markedly high
total phenolic and ellagic acid content. Total phenolic substances of
commercial PJs range from 796.71 to 4608.91 mg GAE/l. Free
amount of ellagic acid in commercial PJs range from 27.64 to 111.78
mg/l. Samples are hydrolyzed with concentrated HCl at 93oC for 2
and 24 hour and influences of temperature and time parameters on
hydrolization were investigated. Thermal processing for
pasteurization increased ellagic acid via ellagitannins hydrolysis.
Abstract: Technological newness and innovativeness are
important aspects of small firm development, growth and wealth
creation. The contribution of the study to entrepreneurship
personality research and to technology-related research in
entrepreneurship is that the model of the general personality driven
technological development was developed and empirically tested.
Hypotheses relating the big five personality factors (OCEAN:
openness, conscientiousness, extraversion, agreeableness, and
neuroticism) and technological developments were tested by using
multiple regression analysis on survey data from a sample of 160
entrepreneurs from Slovenia. The model reveals two personality
factors, which are predictive of technological developments:
openness (positive impact) and neuroticism (negative impact). In
addition, a positive impact of firm age on technological
developments was found. Other personality factors
(conscientiousness, extraversion and agreeableness) of entrepreneurs
may not be considered important for their firm technological
developments.
Abstract: In this note first we define the notions of intuitionistic
fuzzy dual positive implicative hyper K-ideals of types
1,2,3,4 and intuitionistic fuzzy dual hyper K-ideals. Then we
give some classifications about these notions according to the
level subsets. Also by given some examples we show that these
notions are not equivalent, however we prove some theorems
which show that there are some relationships between these
notions. Finally we define the notions of product and antiproduct
of two fuzzy subsets and then give some theorems
about the relationships between the intuitionistic fuzzy dual
positive implicative hyper K-ideal of types 1,2,3,4 and their
(anti-)products, in particular we give a main decomposition
theorem.
Abstract: Iron in groundwater is one of the problems that render the water unsuitable for drinking. The concentration above 0.3 mg/L is common in groundwater. The conventional method of removal is by precipitation under oxic condition. In this study, iron removal under anaerobic conditions was examined by batch experiment as a main purpose. The process involved by purging of groundwater samples with H2S to form iron sulfide. Removal up to 83% for 1 mg/L iron solution was achieved. The removal efficiency dropped to 82% and 75% for the higher initial iron concentrations 3.55 and 5.01 mg/L, respectively. The average residual sulfide concentration in water after the process was 25*g/L. The Eh level during the process was -272 mV. The removal process was found to follow the first order reaction with average rate constant of 4.52 x 10-3. The half-life for the concentrations to reduce from initial values was 157 minutes.
Abstract: This paper features the modeling and design of a
Robust Decentralized Fast Output Sampling (RDFOS) Feedback
control technique for the active vibration control of a smart flexible
multimodel Euler-Bernoulli cantilever beams for a multivariable
(MIMO) case by retaining the first 6 vibratory modes. The beam
structure is modeled in state space form using the concept of
piezoelectric theory, the Euler-Bernoulli beam theory and the Finite
Element Method (FEM) technique by dividing the beam into 4 finite
elements and placing the piezoelectric sensor / actuator at two finite
element locations (positions 2 and 4) as collocated pairs, i.e., as
surface mounted sensor / actuator, thus giving rise to a multivariable
model of the smart structure plant with two inputs and two outputs.
Five such multivariable models are obtained by varying the
dimensions (aspect ratios) of the aluminium beam. Using model
order reduction technique, the reduced order model of the higher
order system is obtained based on dominant Eigen value retention
and the Davison technique. RDFOS feedback controllers are
designed for the above 5 multivariable-multimodel plant. The closed
loop responses with the RDFOS feedback gain and the magnitudes of
the control input are obtained and the performance of the proposed
multimodel smart structure system is evaluated for vibration control.
Abstract: For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach in order to make a solver quickly. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem. It is noted that our formal modeling language is not intend for providing an efficient notation for data mining application, but for facilitating a designer who develops solvers in machine learning.
Abstract: Today-s Information and Knowledge Society has
placed new demands on education and a new paradigm of education
is required. Learning, facilitated by educational systems and the
pedagogic process, is globally undergoing dramatic changes. The aim
of this paper is the development of a simple Instructional Design tool
for E-Learning, named IDEL (Instructional Design for Electronic
Learning), that provides the educators with facilities to create their
own courses with the essential educational material and manage
communication with students. It offers flexibility in the way of
learning and provides ease in employment and reusability of
resources. IDEL is a web-based Instructional System and is designed
to facilitate course design process in accordance with the ADDIE
model and the instructional design principles with emphasis placed
on the use of technology enhanced learning. An example case of
using the ADDIE model to systematically develop a course and its
implementation with the aid of IDEL is given and some results from
student evaluation of the tool and the course are reported.
Abstract: This paper presents a new method for read out of the piezoresistive accelerometer sensors. The circuit works based on Instrumentation amplifier and it is useful for reducing offset In Wheatstone Bridge. The obtained gain is 645 with 1μv/°c Equivalent drift and 1.58mw power consumption. A Schmitt trigger and multiplexer circuit control output node. a high speed counter is designed in this work .the proposed circuit is designed and simulated In 0.18μm CMOS technology with 1.8v power supply.
Abstract: This paper addresses the problem of determining the current 3D location of a moving object and robustly tracking it from a sequence of camera images. The approach presented here uses a particle filter and does not perform any explicit triangulation. Only the color of the object to be tracked is required, but not any precisemotion model. The observation model we have developed avoids the color filtering of the entire image. That and the Monte Carlotechniques inside the particle filter provide real time performance.Experiments with two real cameras are presented and lessons learned are commented. The approach scales easily to more than two cameras and new sensor cues.
Abstract: Series of experimental tests were conducted on a
section of a 660 kW wind turbine blade to measure the pressure
distribution of this model oscillating in plunging motion. In order to
minimize the amount of data required to predict aerodynamic loads
of the airfoil, a General Regression Neural Network, GRNN, was
trained using the measured experimental data. The network once
proved to be accurate enough, was used to predict the flow behavior
of the airfoil for the desired conditions.
Results showed that with using a few of the acquired data, the
trained neural network was able to predict accurate results with
minimal errors when compared with the corresponding measured
values. Therefore with employing this trained network the
aerodynamic coefficients of the plunging airfoil, are predicted
accurately at different oscillation frequencies, amplitudes, and angles
of attack; hence reducing the cost of tests while achieving acceptable
accuracy.
Abstract: This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.
Abstract: InGaAsN and GaAsN epitaxial layers with similar
nitrogen compositions in a sample were successfully grown on a
GaAs (001) substrate by solid source molecular beam epitaxy. An
electron cyclotron resonance nitrogen plasma source has been used to
generate atomic nitrogen during the growth of the nitride layers. The
indium composition changed from sample to sample to give
compressive and tensile strained InGaAsN layers. Layer
characteristics have been assessed by high-resolution x-ray
diffraction to determine the relationship between the lattice constant
of the GaAs1-yNy layer and the fraction x of In. The objective was to
determine the In fraction x in an InxGa1-xAs1-yNy epitaxial layer which
exactly cancels the strain present in a GaAs1-yNy epitaxial layer with
the same nitrogen content when grown on a GaAs substrate.
Abstract: This essay presents applicative methods to reduce human exposure levels in the area around base transceiver stations in a environment with multiple sources based on ITU-T recommendation K.70. An example is presented to understand the mitigation techniques and their results and also to learn how they can be applied, especially in developing countries where there is not much research on non-ionizing radiations.
Abstract: A dissimilarity measure between the empiric
characteristic functions of the subsamples associated to the different
classes in a multivariate data set is proposed. This measure can be
efficiently computed, and it depends on all the cases of each class. It
may be used to find groups of similar classes, which could be joined
for further analysis, or it could be employed to perform an
agglomerative hierarchical cluster analysis of the set of classes. The
final tree can serve to build a family of binary classification models,
offering an alternative approach to the multi-class SVM problem. We
have tested this dendrogram based SVM approach with the oneagainst-
one SVM approach over four publicly available data sets,
three of them being microarray data. Both performances have been
found equivalent, but the first solution requires a smaller number of
binary SVM models.
Abstract: This paper compares six approaches of object serialization
from qualitative and quantitative aspects. Those are object
serialization in Java, IDL, XStream, Protocol Buffers, Apache Avro,
and MessagePack. Using each approach, a common example is
serialized to a file and the size of the file is measured. The qualitative
comparison works are investigated in the way of checking whether
schema definition is required or not, whether schema compiler is
required or not, whether serialization is based on ascii or binary, and
which programming languages are supported. It is clear that there
is no best solution. Each solution makes good in the context it was
developed.
Abstract: The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia and to measure the positive effect, if any, of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.
Abstract: This paper introduces a novel design for boring bar with enhanced damping capability. The principle followed in the design phase was to enhance the damping capability minimizing the loss in static stiffness through implementation of composite material interfaces. The newly designed tool has been compared to a conventional tool. The evaluation criteria were the dynamic characteristics, frequency and damping ratio, of the machining system, as well as the surface roughness of the machined workpieces. The use of composite material in the design of damped tool has been demonstrated effective. Furthermore, the autoregressive moving average (ARMA) models presented in this paper take into consideration the interaction between the elastic structure of the machine tool and the cutting process and can therefore be used to characterize the machining system in operational conditions.
Abstract: Naïve Bayes classifiers are simple probabilistic
classifiers. Classification extracts patterns by using data file with a set
of labeled training examples and is currently one of the most
significant areas in data mining. However, Naïve Bayes assumes the
independence among the features. Structural learning among the
features thus helps in the classification problem. In this study, the use
of structural learning in Bayesian Network is proposed to be applied
where there are relationships between the features when using the
Naïve Bayes. The improvement in the classification using structural
learning is shown if there exist relationship between the features or
when they are not independent.
Abstract: Experiments were carried out at the Latvia State
Institute of Fruit-Growing in 2011. Fresh-cut minimally processed
apple and pear mixed salad were packed by passive modified
atmosphere (MAP) in PP containers, which were hermetically sealed
by breathable conventional BOPP PropafreshTM P2GAF, and Amcor
Agrifresh films. Biodegradable NatureFlexTM NVS INNOVIA Films
and VC999 BioPack PLA films coated with a barrier of pure silicon
oxide (SiOx) were used to compare the fresh-cut produce quality
with this packed in conventional packaging films. Samples were cold
stored at temperature +4.0±0.5 °C up to 10 days. The quality of salad
was evaluated by physicochemical properties – weight losses,
moisture, firmness, the effect of packaging modes on the colour,
dynamics in headspace atmosphere concentration (CO2 and O2),
titratable acidity values, as well as by microbiological contamination
(yeasts, moulds and total bacteria count) of salads, analyzing before
packaging and after 2, 4, 6, 8, and 10 storage days.