Abstract: The study investigated the educational implications
that can be derived from the work of a variety of celebrated figures
such as Piaget, Vygotsky, and Bruner that will be helpful in the field
of language learning. However, the writer believed these views were
previously expressed not full–fledged by Comenius who has been
described by Howatt (1984) as a genius–the one that the history of
language teaching can claim. And we owe to him more than anyone.
Abstract: The alternative technique for sterilization of culture
medium to replace autoclaving was carried out. For sterilization of
culture medium without autoclaving, some commercial pure essential
oils, bergamot oil, betel oil, cinnamon oil, lavender oil and turmeric
oil, were tested alone or in combinations with some disinfectants,
10% povidone-iodine and 2% iodine + 2.4% potassium iodide. Each
essential oil or combination was added to 25-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, were compared to
control medium, autoclaved at 121 degree Celsius for 15 min. In
vitro sterile conditions were found 20 – 100% from these treated
media compared to 100% sterile condition from autoclaved medium.
Treated media obtained 100% sterile conditions were chosen for
culturing chrysanthemum shoots. It was found that 10% povidoneiodine
in combination with cinnamon oil (3:1) and 2% iodine + 2.4%
potassium iodide in combination with lavender oil (1:3) at the
concentration of 36 3L/25 mL medium provided the promising
growth of shoot explants.
Abstract: A variety of new technology-based services have
emerged with the development of Information and Communication
Technologies (ICTs). Since technology-based services have technology-driven characteristics, the identification of relationships
between technology-based services and ICTs would give meaningful implications. Thus, this paper proposes an approach for identifying the
relationships between technology-based services and ICTs by
analyzing patent documents. First, business model (BM) patents are
classified into relevant service categories. Second, patent citation
analysis is conducted to investigate the technological linkage and impacts between technology-based services and ICTs at macro level.
Third, as a micro level analysis, patent co-classification analysis is
employed to identify the technological linkage and coverage. The
proposed approach could guide and help managers and designers of
technology-based services to discover the opportunity of the development of new technology-based services in emerging service sectors.
Abstract: One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.
Abstract: Cryo-electron microscopy (CEM) in combination with
single particle analysis (SPA) is a widely used technique for
elucidating structural details of macromolecular assemblies at closeto-
atomic resolutions. However, development of automated software
for SPA processing is still vital since thousands to millions of
individual particle images need to be processed. Here, we present our
workflow for automated particle picking. Our approach integrates
peak shape analysis to the classical correlation and an iterative
approach to separate macromolecules and background by
classification. This particle selection workflow furthermore provides
a robust means for SPA with little user interaction. Processing
simulated and experimental data assesses performance of the
presented tools.
Abstract: Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.
Abstract: Genome profiling (GP), a genotype based technology, which exploits random PCR and temperature gradient gel electrophoresis, has been successful in identification/classification of organisms. In this technology, spiddos (Species identification dots) and PaSS (Pattern similarity score) were employed for measuring the closeness (or distance) between genomes. Based on the closeness (PaSS), we can buildup phylogenetic trees of the organisms. We noticed that the topology of the tree is rather robust against the experimental fluctuation conveyed by spiddos. This fact was confirmed quantitatively in this study by computer-simulation, providing the limit of the reliability of this highly powerful methodology. As a result, we could demonstrate the effectiveness of the GP approach for identification/classification of organisms.
Abstract: An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.
Abstract: Lateral-torsional buckling (LTB) is one of the
phenomenae controlling the ultimate bending strength of steel Ibeams
carrying distributed loads on top flange. Built-up I-sections
are used as main beams and distributors. This study investigates the
ultimate bending strength of such beams with sections of different
classes including slender elements. The nominal strengths of the
selected beams are calculated for different unsupported lengths
according to the Provisions of the American Institute of Steel
Constructions (AISC-LRFD). These calculations are compared with
results of a nonlinear inelastic study using accurate FE model for this
type of loading. The goal is to investigate the performance of the
provisions for the selected sections. Continuous distributed load at
the top flange of the beams was applied at the FE model.
Imperfections of different values are implemented to the FE model to
examine their effect on the LTB of beams at failure, and hence, their
effect on the ultimate strength of beams. The study also introduces a
procedure for evaluating the performance of the provisions compared
with the accurate FEA results of the selected sections. A simplified
design procedure is given and recommendations for future code
updates are made.
Abstract: Hierarchical classification is a problem with applications in many areas as protein function prediction where the dates are hierarchically structured. Therefore, it is necessary the development of algorithms able to induce hierarchical classification models. This paper presents experimenters using the algorithm for hierarchical classification called Multi-label Hierarchical Classification using a Competitive Neural Network (MHC-CNN). It was tested in ten datasets the Gene Ontology (GO) Cellular Component Domain. The results are compared with the Clus-HMC and Clus-HSC using the hF-Measure.
Abstract: This study examines the mediating effects of male
dyadic adjustment on the relationships between attachment and
attributional styles, and both psychological and physical husband
violence. Based on data from 68 married violent men recruited
through community organizations that work with violent men,
regression analyses showed that husbands- dyadic adjustment
mediates the associations between avoidant attachment and
attributional style, and psychological aggression, but not physical
violence. Scientific and clinical implications are discussed
Abstract: A compact tunable 10 W picosecond source based on
Yb-doped fiber amplification of gain switch laser diode has been
demonstrated. A gain switch semiconductor laser diode was used as
the seed source, and a multi-stage single mode Yb-doped fiber
preamplifier was combined with two large mode area double-clad
Yb-doped fiber main amplifiers to construct the amplification system.
The tunable pulses with high stability and excellent beam quality
(M2
Abstract: In the framework of the image compression by
Wavelet Transforms, we propose a perceptual method by
incorporating Human Visual System (HVS) characteristics in the
quantization stage. Indeed, human eyes haven-t an equal sensitivity
across the frequency bandwidth. Therefore, the clarity of the
reconstructed images can be improved by weighting the quantization
according to the Contrast Sensitivity Function (CSF). The visual
artifact at low bit rate is minimized. To evaluate our method, we use
the Peak Signal to Noise Ratio (PSNR) and a new evaluating criteria
witch takes into account visual criteria. The experimental results
illustrate that our technique shows improvement on image quality at
the same compression ratio.
Abstract: to simulate the phenomenon of electronic transport in semiconductors, we try to adapt a numerical method, often and most frequently it’s that of Monte Carlo. In our work, we applied this method in the case of a ternary alloy semiconductor GaInP in its cubic form; The Calculations are made using a non-parabolic effective-mass energy band model. We consider a band of conduction to three valleys (ΓLX), major of the scattering mechanisms are taken into account in this modeling, as the interactions with the acoustic phonons (elastic collisions) and optics (inelastic collisions). The polar optical phonons cause anisotropic collisions, intra-valleys, very probable in the III-V semiconductors. Other optical phonons, no polar, allow transitions inter-valleys. Initially, we present the full results obtained by the simulation of Monte Carlo in GaInP in stationary regime. We consider thereafter the effects related to the application of an electric field varying according to time, we thus study the transient phenomenon which make their appearance in ternary material
Abstract: We developed a multi-camera control system that a (one) cameraman can operate several cameras at a compact studio. we analyzed a workflow of a cameraman of some program shootings with two cameras and clarified their heavy tasks. The system based on a dynamic workflow which adapts a program progressing and recommends of cameraman. we perform the automation of multicamera controls by modeling of studio environment and perform automatic camera adjustment for suitable angle of view with face detection. Our experiment at a real program shooting showed that one cameraman can carry out the task of shooting sufficiently.
Abstract: In this article we address the problem of mobile robot formation control. Indeed, the most work, in this domain, have studied extensively classical control for keeping a formation of mobile robots. In this work, we design an FLC (Fuzzy logic Controller) controller for separation and bearing control (SBC). Indeed, the leader mobile robot is controlled to follow an arbitrary reference path, and the follower mobile robot use the FSBC (Fuzzy Separation and Bearing Control) to keep constant relative distance and constant angle to the leader robot. The efficiency and simplicity of this control law has been proven by simulation on different situation.
Abstract: The issue of classifying objects into one of predefined
groups when the measured variables are mixed with different types
of variables has been part of interest among statisticians in many
years. Some methods for dealing with such situation have been
introduced that include parametric, semi-parametric and nonparametric
approaches. This paper attempts to discuss on a problem
in classifying a data when the number of measured mixed variables is
larger than the size of the sample. A propose idea that integrates a
dimensionality reduction technique via principal component analysis
and a discriminant function based on the location model is discussed.
The study aims in offering practitioners another potential tool in a
classification problem that is possible to be considered when the
observed variables are mixed and too large.
Abstract: Combined therapy using Interferon and Ribavirin is the standard treatment in patients with chronic hepatitis C. However, the number of responders to this treatment is low, whereas its cost and side effects are high. Therefore, there is a clear need to predict patient’s response to the treatment based on clinical information to protect the patients from the bad drawbacks, Intolerable side effects and waste of money. Different machine learning techniques have been developed to fulfill this purpose. From these techniques are Associative Classification (AC) and Decision Tree (DT). The aim of this research is to compare the performance of these two techniques in the prediction of virological response to the standard treatment of HCV from clinical information. 200 patients treated with Interferon and Ribavirin; were analyzed using AC and DT. 150 cases had been used to train the classifiers and 50 cases had been used to test the classifiers. The experiment results showed that the two techniques had given acceptable results however the best accuracy for the AC reached 92% whereas for DT reached 80%.
Abstract: Interpolated contour maps drawn for aluminum,
copper and molybdenum in downstream monitoring boreholes of
water dam in Miduk Copper Complex and the values of pH, redox
potential (Eh) and distance from water dam indicate different trends
of variation and behavior of these three elements in downward
groundwater resources. As these maps exhibit, aluminum is dominant
in the most alkaline (pH = 9-11) borehole (MB5) to water dam. The
highest concentration of molybdenum is found in the nearest
borehole (MB6) to water dam. Main concentration of copper is
observed in the most oxidized borehole (MB3 with Eh=293.2mV).
The spatial difference among sampling stations can be attributed to
the existence of faults and diaclases in the geologic structure of
Miduk region which causes the groundwater sampling sites to be
impressed by different contamination sources (toe seepage and upper
seepage water originated from different zones of tailings dump).
Abstract: The internet is constantly expanding. Identifying web
links of interest from web browsers requires users to visit each of the
links listed, individually until a satisfactory link is found, therefore
those users need to evaluate a considerable amount of links before
finding their link of interest; this can be tedious and even
unproductive. By incorporating web assistance, web users could be
benefited from reduced time searching on relevant websites. In this
paper, a rough set approach is presented, which facilitates
classification of unlimited available e-vocabulary, to assist web users
in reducing search times looking for relevant web sites. This
approach includes two methods for identifying relevance data on web
links based on the priority and percentage of relevance. As a result of
these methods, a list of web sites is generated in priority sequence
with an emphasis of the search criteria.