Abstract: Rapid growth of distance learning resulted in
importance to conduct research on students- satisfaction with distance
learning because differences in students- satisfaction might influence
educational opportunities for learning in a relevant Web-based
environment. In line with this, this paper deals with satisfaction of
students with distance module at Faculty of organizational sciences
(FOS) in Serbia as well as some factors affecting differences in their
satisfaction . We have conducted a research on a population of 68
first-year students of distance learning studies at FOS. Using
statistical techniques, we have found out that there is no significant
difference in students- satisfaction with distance learning module
between men and women. In the same way, we also concluded that
there is a difference in satisfaction with distance learning module
regarding to student-s perception of opportunity to gain knowledge as
the classic students.
Abstract: One of the ubiquitous routines in medical practice is searching through voluminous piles of clinical documents. In this paper we introduce a distributed system to search and exchange clinical documents. Clinical documents are distributed peer-to-peer. Relevant information is found in multiple iterations of cross-searches between the clinical text and its domain encyclopedia.
Abstract: Flat double-layer grid is from category of space structures that are formed from two flat layers connected together with diagonal members. Increased stiffness and better seismic resistance in relation to other space structures are advantages of flat double layer space structures. The objective of this study is assessment and calculation of Behavior factor of flat double layer space structures. With regarding that these structures are used widely but Behavior factor used to design these structures against seismic force is not determined and exact, the necessity of study is obvious. This study is theoretical. In this study we used structures with span length of 16m and 20 m. All connections are pivotal. ANSYS software is used to non-linear analysis of structures.
Abstract: This calculation focus on the effect of exchange
interaction J and Coulomb interaction U on spin magnetic moments
(ms) of MnO by using the local spin density approximation plus the
Coulomb interaction (LSDA+U) method within full potential linear
muffin-tin orbital (FP-LMTO). Our calculated results indicated that
the spin magnetic moments correlated to J and U. The relevant
results exhibited the increasing spin magnetic moments with
increasing exchange interaction and Coulomb interaction.
Furthermore, equations of spin magnetic moment, which h good
correspondence to the experimental data 4.58μB, are defined ms =
0.11J +4.52μB and ms = 0.03U+4.52μB. So, the relation of J and U
parameter is obtained, it is obviously, J = -0.249U+1.346 eV.
Abstract: Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.
Abstract: Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web applications design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper proposes an approach to automatic multi-dimensional concern mining for Web Applications, based on concepts analysis, impact analysis, and token-based concern identification. This approach lets the user to analyse and traverse Web software relevant to a particular concern (concept, goal, purpose, etc.) via multi-dimensional separation of concerns, to document, understand and test Web applications. This technique was developed in the context of WAAT (Web Applications Analysis and Testing) project. A semi-automatic tool to support this technique is currently under development.
Abstract: This study focuses on bureau management
technologies and information systems in developing countries.
Developing countries use such systems which facilitate executive and
organizational functions through the utilization of bureau
management technologies and provide the executive staff with
necessary information.
The concepts of data and information differ from each other in
developing countries, and thus the concepts of data processing and
information processing are different. Symbols represent ideas,
objects, figures, letters and numbers. Data processing system is an
integrated system which deals with the processing of the data related
to the internal and external environment of the organization in order
to make decisions, create plans and develop strategies; it goes
without saying that this system is composed of both human beings
and machines. Information is obtained through the acquisition and
the processing of data. On the other hand, data are raw
communicative messages. Within this framework, data processing
equals to producing plausible information out of raw data.
Organizations in developing countries need to obtain information
relevant to them because rapid changes in the organizational arena
require rapid access to accurate information. The most significant
role of the directors and managers who work in the organizational
arena is to make decisions. Making a correct decision is possible only
when the directors and managers are equipped with sound ideas and
appropriate information. Therefore, acquisition, organization and
distribution of information gain significance. Today-s organizations
make use of computer-assisted “Management Information Systems"
in order to obtain and distribute information.
Decision Support System which is closely related to practice is an
information system that facilitates the director-s task of making
decisions. Decision Support System integrates human intelligence,
information technology and software in order to solve the complex
problems. With the support of the computer technology and software
systems, Decision Support System produces information relevant to
the decision to be made by the director and provides the executive
staff with supportive ideas about the decision.
Artificial Intelligence programs which transfer the studies and
experiences of the people to the computer are called expert systems.
An expert system stores expert information in a limited area and can
solve problems by deriving rational consequences.
Bureau management technologies and information systems in
developing countries create a kind of information society and
information economy which make those countries have their places
in the global socio-economic structure and which enable them to play
a reasonable and fruitful role; therefore it is of crucial importance to
make use of information and management technologies in order to
work together with innovative and enterprising individuals and it is
also significant to create “scientific policies" based on information
and technology in the fields of economy, politics, law and culture.
Abstract: Successful public-private-partnership (PPP)
implementation can not be achieved without the active participation of
private sector companies. This paper examines the decision-making of
private sector companies in public works delivered by the PPP model
on the basis of social responsibility theory. It proposes that private
sector companies should indentify objectives of entering into PPP
projects, and shoulder relevant social responsibilities, while a
minimum return should also be guaranteed in their favor, so as to
compensate for their assumed risk and support them to take on
responsibilities in the future. The paper also gives a calculation
regarding the appropriate scale and reasonable degree of private sector
involvement in PPP projects through the cost-benefit analysis in a
specific case study, with the purpose to guide the private sector
companies to create a cooperation environment resembling
“symbiosis" and facilitate the smooth implementation of public works
delivered by the PPP model.
Abstract: Through 1980s, management accounting researchers
described the increasing irrelevance of traditional control and
performance measurement systems. The Balanced Scorecard (BSC)
is a critical business tool for a lot of organizations. It is a
performance measurement system which translates mission and
strategy into objectives. Strategy map approach is a development
variant of BSC in which some necessary causal relations must be
established. To recognize these relations, experts usually use
experience. It is also possible to utilize regression for the same
purpose. Structural Equation Modeling (SEM), which is one of the
most powerful methods of multivariate data analysis, obtains more
appropriate results than traditional methods such as regression. In the
present paper, we propose SEM for the first time to identify the
relations between objectives in the strategy map, and a test to
measure the importance of relations. In SEM, factor analysis and test
of hypotheses are done in the same analysis. SEM is known to be
better than other techniques at supporting analysis and reporting. Our
approach provides a framework which permits the experts to design
the strategy map by applying a comprehensive and scientific method
together with their experience. Therefore this scheme is a more
reliable method in comparison with the previously established
methods.
Abstract: In this paper, a model for an information retrieval
system is proposed which takes into account that knowledge about
documents and information need of users are dynamic. Two
methods are combined, one qualitative or symbolic and the other
quantitative or numeric, which are deemed suitable for many
clustering contexts, data analysis, concept exploring and
knowledge discovery. These two methods may be classified as
inductive learning techniques. In this model, they are introduced to
build “long term" knowledge about past queries and concepts in a
collection of documents. The “long term" knowledge can guide
and assist the user to formulate an initial query and can be
exploited in the process of retrieving relevant information. The
different kinds of knowledge are organized in different points of
view. This may be considered an enrichment of the exploration
level which is coherent with the concept of document/query
structure.
Abstract: Fuzzy random variables have been introduced as an imprecise concept of numeric values for characterizing the imprecise knowledge. The descriptive parameters can be used to describe the primary features of a set of fuzzy random observations. In fuzzy environments, the expected values are usually represented as fuzzy-valued, interval-valued or numeric-valued descriptive parameters using various metrics. Instead of the concept of area metric that is usually adopted in the relevant studies, the numeric expected value is proposed by the concept of distance metric in this study based on two characters (fuzziness and randomness) of FRVs. Comparing with the existing measures, although the results show that the proposed numeric expected value is same with those using the different metric, if only triangular membership functions are used. However, the proposed approach has the advantages of intuitiveness and computational efficiency, when the membership functions are not triangular types. An example with three datasets is provided for verifying the proposed approach.
Abstract: The Institute of Product Development is dealing
with the development, design and dimensioning of micro components
and systems as a member of the Collaborative Research
Centre 499 “Design, Production and Quality Assurance of
Molded micro components made of Metallic and Ceramic Materials".
Because of technological restrictions in the miniaturization
of conventional manufacturing techniques, shape and
material deviations cannot be scaled down in the same proportion
as the micro parts, rendering components with relatively
wide tolerance fields. Systems that include such components
should be designed with this particularity in mind, often requiring
large clearance. On the end, the output of such systems
results variable and prone to dynamical instability. To save
production time and resources, every study of these effects
should happen early in the product development process and
base on computer simulation to avoid costly prototypes. A
suitable method is proposed here and exemplary applied to a
micro technology demonstrator developed by the CRC499. It
consists of a one stage planetary gear train in a sun-planet-ring
configuration, with input through the sun gear and output
through the carrier. The simulation procedure relies on ordinary
Multi Body Simulation methods and subsequently adds
other techniques to further investigate details of the system-s
behavior and to predict its response. The selection of the relevant
parameters and output functions followed the engineering
standards for regular sized gear trains. The first step is to
quantify the variability and to reveal the most critical points of
the system, performed through a whole-mechanism Sensitivity
Analysis. Due to the lack of previous knowledge about the system-s
behavior, different DOE methods involving small and
large amount of experiments were selected to perform the SA.
In this particular case the parameter space can be divided into
two well defined groups, one of them containing the gear-s profile
information and the other the components- spatial location.
This has been exploited to explore the different DOE techniques
more promptly. A reduced set of parameters is derived for
further investigation and to feed the final optimization process,
whether as optimization parameters or as external perturbation
collective. The 10 most relevant perturbation factors and 4 to 6
prospective variable parameters are considered in a new, simplified
model. All of the parameters are affected by the mentioned
production variability. The objective functions of interest
are based on scalar output-s variability measures, so the
problem becomes an optimization under robustness and reliability constrains. The study shows an initial step on the development
path of a method to design and optimize complex micro
mechanisms composed of wide tolerated elements accounting
for the robustness and reliability of the systems- output.
Abstract: Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.
Abstract: This study investigates the use of genetic algorithms
in information retrieval. The method is shown to be applicable to
three well-known documents collections, where more relevant
documents are presented to users in the genetic modification. In this
paper we present a new fitness function for approximate information
retrieval which is very fast and very flexible, than cosine similarity
fitness function.
Abstract: A compact 1x3 power splitter based on Photonic
Crystal Waveguides (PCW) with flexible power splitting ratio is
presented in this paper. Multimode interference coupler (MMI) is
integrated with PCW. The device size reduction compared with the
conventional MMI power splitter is attributed to the large dispersion
of the PCW. Band Solve tool is used to calculate the band structure of
PCW. Finite Difference Time Domain (FDTD) method is adopted to
simulate the relevant structure at 1550nm wavelength. The device is
polarization insensitive and allows the control of output (o/p) powers
within certain percentage points for both polarizations.
Abstract: 98% of the energy needed in Taiwan has been
imported. The prices of petroleum and electricity have been
increasing. In addition, facility capacity, amount of electricity
generation, amount of electricity consumption and number of Taiwan
Power Company customers have continued to increase. For these
reasons energy conservation has become an important topic. In the
past linear regression was used to establish the power consumption
models for chillers. In this study, grey prediction is used to evaluate
the power consumption of a chiller so as to lower the total power
consumption at peak-load (so that the relevant power providers do not
need to keep on increasing their power generation capacity and facility
capacity).
In grey prediction, only several numerical values (at least four
numerical values) are needed to establish the power consumption
models for chillers. If PLR, the temperatures of supply chilled-water
and return chilled-water, and the temperatures of supply cooling-water
and return cooling-water are taken into consideration, quite accurate
results (with the accuracy close to 99% for short-term predictions)
may be obtained. Through such methods, we can predict whether the
power consumption at peak-load will exceed the contract power
capacity signed by the corresponding entity and Taiwan Power
Company. If the power consumption at peak-load exceeds the power
demand, the temperature of the supply chilled-water may be adjusted
so as to reduce the PLR and hence lower the power consumption.
Abstract: This paper discusses the utilization of marine biomass as an energy resource in Japan. A marine biomass energy system in Japan was proposed consisting of seaweed cultivation (Laminaria japonica) at offshore marine farms, biogas production via methane fermentation of the seaweeds, and fuel cell power generation driven by the generated biogas. We estimated energy output, energy supply potential, and CO2 mitigation in Japan on the basis of the proposed system. As a result, annual energy production was estimated to be 1.02-109 kWh/yr at nine available sites. Total CO2 mitigation was estimated to be 1.04-106 tonnes per annum at the nine sites. However, the CO2 emission for the construction of relevant facilities is not taken into account in this paper. The estimated CO2 mitigation is equivalent to about 0.9% of the required CO2 mitigation for Japan per annum under the Kyoto Protocol framework.
Abstract: In this paper we present a linear autozeroing ultra lowvoltage amplifier. The autozeroing performed by all ULV circuits is important to reduce the impact of noise and especially avoid power supply noise in mixed signal low-voltage CMOS circuits. The simulated data presented is relevant for a 90nm TSMC CMOS process.
Abstract: Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.
Abstract: As in today's semiconductor industries test costs can make up to 50 percent of the total production costs, an efficient test error detection becomes more and more important. In this paper, we present a new machine learning approach to test error detection that should provide a faster recognition of test system faults as well as an improved test error recall. The key idea is to learn a classifier ensemble, detecting typical test error patterns in wafer test results immediately after finishing these tests. Since test error detection has not yet been discussed in the machine learning community, we define central problem-relevant terms and provide an analysis of important domain properties. Finally, we present comparative studies reflecting the failure detection performance of three individual classifiers and three ensemble methods based upon them. As base classifiers we chose a decision tree learner, a support vector machine and a Bayesian network, while the compared ensemble methods were simple and weighted majority vote as well as stacking. For the evaluation, we used cross validation and a specially designed practical simulation. By implementing our approach in a semiconductor test department for the observation of two products, we proofed its practical applicability.