Abstract: This work deals with aspects of support vector learning for large-scale data mining tasks. Based on a decomposition algorithm that can be run in serial and parallel mode we introduce a data transformation that allows for the usage of an expensive generalized kernel without additional costs. In order to speed up the decomposition algorithm we analyze the problem of working set selection for large data sets and analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our modifications and settings lead to improvement of support vector learning performance and thus allow using extensive parameter search methods to optimize classification accuracy.
Abstract: Bologna process has influenced enhancing studentcentered
learning in Estonian higher education since 2009, but there
is no information about what helps or hinders students to achieve
learning outcomes and how quality of student-centered learning
might be improved. The purpose of this study is to analyze two
questions from outcome-based course evaluation questionnaire which
is used in Estonian Entrepreneurship University of Applied Sciences.
In this qualitative research, 384 students from 22 different courses
described what helped and hindered them to achieve learning
outcomes. The analysis showed that the aspects that hinder students
to achieve learning outcomes are mostly personal: time management,
family and personal matters, motivation and non-academic activities.
The results indicate that students- learning is commonly supported by
school, where teacher, teaching and characteristics of teaching
methods help mostly to achieve learning outcomes, also learning
material, practical assignments and independent study was brought
up as one of the key elements.
Abstract: This paper deals with the optimal design of two-channel recursive parallelogram quadrature mirror filter (PQMF) banks. The analysis and synthesis filters of the PQMF bank are composed of two-dimensional (2-D) recursive digital all-pass filters (DAFs) with nonsymmetric half-plane (NSHP) support region. The design problem can be facilitated by using the 2-D doubly complementary half-band (DC-HB) property possessed by the analysis and synthesis filters. For finding the coefficients of the 2-D recursive NSHP DAFs, we appropriately formulate the design problem to result in an optimization problem that can be solved by using a weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The designed 2-D recursive PQMF bank achieves perfect magnitude response and possesses satisfactory phase response without requiring extra phase equalizer. Simulation results are also provided for illustration and comparison.
Abstract: Starting from the basic pillars of the supportability
analysis this paper queries its characteristics in LCI (Life Cycle
Integration) environment. The research methodology contents a
review of modern logistics engineering literature with the objective to
collect and synthesize the knowledge relating to standards of
supportability design in e-logistics environment. The results show
that LCI framework has properties which are in fully compatibility
with the requirement of simultaneous logistics support and productservice
bundle design. The proposed approach is a contribution to the
more comprehensive and efficient supportability design process.
Also, contributions are reflected through a greater consistency of
collected data, automated creation of reports suitable for different
analysis, as well as the possibility of their customization according
with customer needs. In addition to this, convenience of this approach
is its practical use in real time. In a broader sense, LCI allows
integration of enterprises on a worldwide basis facilitating electronic
business.
Abstract: This paper presents an assessment study conducted
among the distance learners in India. Open and distance learning
systems have traveled a long way since its inception and its journey
has witnessed the evolution and adoption of different generations of
technology. This study focuses on the distant learners in India.
Sampling for this study has been derived from the mass enrollment
from Tamil Nadu area, a southern state of India. Learners were
chosen from dual mode universities, private universities, Tamil Nadu
Open University and IGNOU. The main focus of the study is to
examine the coverage and appropriation of students support services
and learning aids. It explores two aspects: the facilities available and
the awareness and use of such services. It includes, self-learning
materials, face-to-face counseling, multimedia learning materials,
website, e-learning, radio and television services etc. While exploring
the student-s perspective on these learning aspects, it is important to
understand the perspectives of the teachers. Two different interests
are visible among the teachers. Majority of the teachers support faceto-
face counseling. However, the young teachers are in favour of
online learning and multimedia supports in teaching. Through the
awareness is somewhat high, the actual participation in online is very
low. This is due to the inadequate infrastructure as well as the
traditional attitudes of the teachers. Still the face-to-face sessions
remain popular than online.
Abstract: With the prevalence of computer and development of information technology, Geographic Information Systems (GIS) have long used for a variety of applications in electrical engineering. GIS are designed to support the analysis, management, manipulation and mapping of spatial data. This paper presents several usages of GIS in power utilities such as automated route selection for the construction of new power lines which uses a dynamic programming model for route optimization, load forecasting and optimizing planning of substation-s location and capacity with comprehensive algorithm which involves an accurate small-area electric load forecasting procedure and simulates the different cost functions of substations.
Abstract: The contribution deals with current or potential approaches to the modeling and optimization of tactical activities. This issue takes on importance in recent times, particularly with the increasing trend of digitized battlefield, the development of C4ISR systems and intention to streamline the command and control process at the lowest levels of command. From fundamental and philosophically point of view, this new approaches seek to significantly upgrade and enhance the decision-making process of the tactical commanders.
Abstract: Environmental decision making, particularly about
hazardous waste management, is inherently exposed to a high
potential conflict, principally because of the trade-off between sociopolitical,
environmental, health and economic factors. The need to
plan complex contexts has led to an increasing request for decision
analytic techniques as support for the decision process. In this work,
alternative systems of asbestos-containing waste management
(ACW) in Puglia (Southern Italy) were explored by a multi-criteria
decision analysis. In particular, through Analytic Hierarchy Process
five alternatives management have been compared and ranked
according to their performance and efficiency, taking into account
environmental, health and socio-economic aspects. A separated
valuation has been performed for different temporal scale. For short
period results showed a narrow deviation between the disposal
alternatives “mono-material landfill in public quarry" and “dedicate
cells in existing landfill", with the best performance of the first one.
While for long period “treatment plant to eliminate hazard from
asbestos-containing waste" was prevalent, although high energy
demand required to achieve the change of crystalline structure. A
comparison with results from a participative approach in valuation
process might be considered as future development of method
application to ACW management.
Abstract: In this paper, the application of the Mode Matching
(MM) method in the case of photonic crystal waveguide
discontinuities is presented. The structure under consideration is
divided into a number of cells, which supports a number of guided
and evanescent modes. These modes can be calculated numerically
by an alternative formulation of the plane wave expansion method
for each frequency. A matrix equation is then formed relating the
modal amplitudes at the beginning and at the end of the structure.
The theory is highly efficient and accurate and can be applied to
study the transmission sensitivity of photonic crystal devices due to
fabrication tolerances. The accuracy of the MM method is compared
to the Finite Difference Frequency Domain (FDFD) and the Adjoint
Variable Method (AVM) and good agreement is observed.
Abstract: This paper presents the automated methods employed
for extracting craniofacial landmarks in white light images as part of
a registration framework designed to support three neurosurgical
procedures. The intraoperative space is characterised by white light
stereo imaging while the preoperative plan is performed on CT scans.
The registration aims at aligning these two modalities to provide a
calibrated environment to enable image-guided solutions. The
neurosurgical procedures can then be carried out by mapping the
entry and target points from CT space onto the patient-s space. The
registration basis adopted consists of natural landmarks (eye corner
and ear tragus). A 5mm accuracy is deemed sufficient for these three
procedures and the validity of the selected registration basis in
achieving this accuracy has been assessed by simulation studies. The
registration protocol is briefly described, followed by a presentation
of the automated techniques developed for the extraction of the
craniofacial features and results obtained from tests on the AR and
FERET databases. Since the three targeted neurosurgical procedures
are routinely used for head injury management, the effect of
bruised/swollen faces on the automated algorithms is assessed. A
user-interactive method is proposed to deal with such unpredictable
circumstances.
Abstract: The governing differential equations of laminated
plate utilizing trigonometric shear deformation theory are derived
using energy approach. The governing differential equations
discretized by different radial basis functions are used to predict the
free vibration behavior of symmetric laminated composite plates.
Effect of orthotropy and span to thickness ratio on frequency
parameter of simply supported laminated plate is presented.
Numerical results show the accuracy and good convergence of radial
basis functions.
Abstract: This paper studies mechanical buckling of
functionally graded beams subjected to axial compressive load that is
simply supported at both ends lies on a continuous elastic foundation.
The displacement field of beam is assumed based on Engesser-Timoshenko beam theory. Applying the Hamilton's principle, the
equilibrium equation is established. The influences of dimensionless geometrical parameter, functionally graded index and foundation
coefficient on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study
is carried out with a known data.
Abstract: In order to apply partially filled steel grid composite deck as the horizontal supporting structure of various kinds of infrastructures, the variation of its flexural strength according to design parameters such as cross and longitudinal bars constituting the steel grid and the type of shear connection is evaluated and compared experimentally. The result shows that the design sensitivity of the deck to the spacing of the cross bars is insignificant in the case of structure with low risk of punching failure or without load distribution problem. By means of shear connection composed by transverse rebar and longitudinal bar without additional shear stud bolts, the complete interaction between steel grid and concrete slab is able to be achieved and the composite deck can develop its bending resistance capacity.
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: The search for factors that influence user behavior has remained an important theme for both the academic and practitioner Information Systems Communities. In this paper we examine relevant user behaviors in the phase after adoption and investigate two factors that are expected to influence such behaviors, namely User Involvement (UI) and Personal Innovativeness in IT (PIIT). We conduct a field study to examine how these factors influence postadoption behavior and how they are interrelated. Building on theoretical premises and prior empirical findings, we propose and test two alternative models of the relationship between these factors. Our results reveal that the best explanation of post-adoption behavior is provided by the model where UI and PIIT independently influence post-adoption behavior. Our findings have important implications for research and practice. To that end, we offer directions for future research.
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: 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: To investigate some relations between higher mathe¬matics scores in Chinese graduate student entrance examination and calculus (resp. linear algebra, probability statistics) scores in subject's completion examination of Chinese university, we select 20 students as a sample, take higher mathematics score as a decision attribute and take calculus score, linear algebra score, probability statistics score as condition attributes. In this paper, we are based on rough-set theory (Rough-set theory is a logic-mathematical method proposed by Z. Pawlak. In recent years, this theory has been widely implemented in the many fields of natural science and societal science.) to investigate importance of condition attributes with respective to decision attribute and strength of condition attributes supporting decision attribute. Results of this investigation will be helpful for university students to raise higher mathematics scores in Chinese graduate student entrance examination.
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: Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.