Abstract: The new framework the Higher Education is
immersed in involves a complete change in the way lecturers must
teach and students must learn. Whereas the lecturer was the main
character in traditional education, the essential goal now is to
increase the students' participation in the process. Thus, one of the
main tasks of lecturers in this new context is to design activities of
different nature in order to encourage such participation. Seminars
are one of the activities included in this environment. They are active
sessions that enable going in depth into specific topics as support of
other activities. They are characterized by some features such as
favoring interaction between students and lecturers or improving
their communication skills. Hence, planning and organizing strategic
seminars is indeed a great challenge for lecturers with the aim of
acquiring knowledge and abilities. This paper proposes a method
using Artificial Intelligence techniques to obtain student profiles
from their marks and preferences. The goal of building such profiles
is twofold. First, it facilitates the task of splitting the students into
different groups, each group with similar preferences and learning
difficulties. Second, it makes it easy to select adequate topics to be a
candidate for the seminars. The results obtained can be either a
guarantee of what the lecturers could observe during the development
of the course or a clue to reconsider new methodological strategies in
certain topics.
Abstract: This research work is aimed at speech recognition
using scaly neural networks. A small vocabulary of 11 words were
established first, these words are “word, file, open, print, exit, edit,
cut, copy, paste, doc1, doc2". These chosen words involved with
executing some computer functions such as opening a file, print
certain text document, cutting, copying, pasting, editing and exit.
It introduced to the computer then subjected to feature extraction
process using LPC (linear prediction coefficients). These features are
used as input to an artificial neural network in speaker dependent
mode. Half of the words are used for training the artificial neural
network and the other half are used for testing the system; those are
used for information retrieval.
The system components are consist of three parts, speech
processing and feature extraction, training and testing by using neural
networks and information retrieval.
The retrieve process proved to be 79.5-88% successful, which is
quite acceptable, considering the variation to surrounding, state of
the person, and the microphone type.
Abstract: This paper presents the region based segmentation method for ultrasound images using local statistics. In this segmentation approach the homogeneous regions depends on the image granularity features, where the interested structures with dimensions comparable to the speckle size are to be extracted. This method uses a look up table comprising of the local statistics of every pixel, which are consisting of the homogeneity and similarity bounds according to the kernel size. The shape and size of the growing regions depend on this look up table entries. The algorithms are implemented by using connected seeded region growing procedure where each pixel is taken as seed point. The region merging after the region growing also suppresses the high frequency artifacts. The updated merged regions produce the output in formed of segmented image. This algorithm produces the results that are less sensitive to the pixel location and it also allows a segmentation of the accurate homogeneous regions.
Abstract: Traffic Engineering (TE) is the process of controlling
how traffic flows through a network in order to facilitate efficient and
reliable network operations while simultaneously optimizing network
resource utilization and traffic performance. TE improves the
management of data traffic within a network and provides the better
utilization of network resources. Many research works considers intra
and inter Traffic Engineering separately. But in reality one influences
the other. Hence the effective network performances of both inter and
intra Autonomous Systems (AS) are not optimized properly. To
achieve a better Joint Optimization of both Intra and Inter AS TE, we
propose a joint Optimization technique by considering intra-AS
features during inter – AS TE and vice versa. This work considers the
important criterion say latency within an AS and between ASes. and
proposes a Bi-Criteria Latency optimization model. Hence an overall
network performance can be improved by considering this jointoptimization
technique in terms of Latency.
Abstract: The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.
Abstract: In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.
Abstract: Sickness absence represents a major economic and
social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is
often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient
and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using
a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model
selection and a critical analysis of the temporal trends, the occurrence
and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large
sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to
select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model
applicability to complicated longitudinal data.
Abstract: Metal stamping die design is a complex, experiencebased
and time-consuming task. Various artificial intelligence (AI)
techniques are being used by worldwide researchers for stamping die
design to reduce complexity, dependence on human expertise and
time taken in design process as well as to improve design efficiency.
In this paper a comprehensive review of applications of AI
techniques in manufacturability evaluation of sheet metal parts, die
design and process planning of metal stamping die is presented.
Further the salient features of major research work published in the
area of metal stamping are presented in tabular form and scope of
future research work is identified.
Abstract: IVE toolkit has been created for facilitating research,education and development in the field of virtual storytelling and computer games. Primarily, the toolkit is intended for modelling action selection mechanisms of virtual humans, investigating level-of-detail AI techniques for large virtual environments, and for exploring joint behaviour and role-passing technique (Sec. V). Additionally, the toolkit can be used as an AI middleware without any changes. The main facility of IVE is that it serves for prototyping both the AI and virtual worlds themselves. The purpose of this paper is to describe IVE's features in general and to present our current work - including an educational game - on this platform.
Abstract: Vehicle suspension design must fulfill
some conflicting criteria. Among those is ride comfort
which is attained by minimizing the acceleration
transmitted to the sprung mass, via suspension spring
and damper. Also good handling of a vehicle is a
desirable property which requires stiff suspension and
therefore is in contrast with a vehicle with good ride.
Among the other desirable features of a suspension is
the minimization of the maximum travel of suspension.
This travel which is called suspension working space in
vehicle dynamics literature is also a design constraint
and it favors good ride. In this research a full car 8
degrees of freedom model has been developed and the
three above mentioned criteria, namely: ride, handling
and working space has been adopted as objective
functions. The Multi Objective Programming (MOP)
discipline has been used to find the Pareto Front and
some reasoning used to chose a design point between
these non dominated points of Pareto Front.
Abstract: In quality control of freeze-dried durian, crispiness is
a key quality index of the product. Generally, crispy testing has to be
done by a destructive method. A nondestructive testing of the
crispiness is required because the samples can be reused for other
kinds of testing. This paper proposed a crispiness classification
method of freeze-dried durians using fuzzy logic for decision
making. The physical changes of a freeze-dried durian include the
pores appearing in the images. Three physical features including (1)
the diameters of pores, (2) the ratio of the pore area and the
remaining area, and (3) the distribution of the pores are considered to
contribute to the crispiness. The fuzzy logic is applied for making the
decision. The experimental results comparing with food expert
opinion showed that the accuracy of the proposed classification
method is 83.33 percent.
Abstract: Distance education program is a dimension of contemporary and new education technologies. Concepts and applications in this field are the results of a series of educational demands and developments in various communication and education technologies. Distance education applications have some conceptual bases. These are creating new education opportunities, realizing work-education unity, getting democratic in education, lifelong education, tendency to individual matters, effective use of institutions, integration of technology and education, tendency to individual and social needs, taking three dimensional integration as the main principle (publishing, printed materials and face to face education), reaching maximum mass, individual and mass education integrity and education demand and financial matters balance. Economics, Business Administration and Open Education faculties, which have been giving education within Anadolu University since 1982 in Turkey, are carrying on education with nearly 1.000.000 students. The aim of this study is to determine organizational commitment levels of students who have been studying at Anadolu University Economics, Business Administration and Open Education faculties in the scope of affective, continuance and nominative commitment in Allen&Meyer model. In the study, organizational commitment of the Economics, Business Administration and Open Education faculty students, who are receiving education by means of distance education, to their faculties is dealt after introducing Anadolu University Distance Education system which gives higher education via distance education method in Turkey. In order to increase the success level of faculties it is required for students to have high level of organizational commitment to their faculties. A questionnaire has been applied by using “Organizational Commitment Scale", developed by Meyer&Allen to determine organizational commitments of Economics, Business Administration and Open Education students. Organizational commitment is dealt with as affective, continuance and nominative commitment. The questionnaire was applied face to face to randomly chosen 500 students living in Eskişehir and the data was downloaded to the computer by using SPSS program and the results were analyzed in terms of demographic features (gender, age, marital status, years of study, work and income level) of students by using frequency test, ttest and ANOVA test. As a result of these analyses, when the comments of Open Education Faculty students on levels of affective, continuance and nominative commitment to their faculties were examined, it has been revealed that continuance commitment level has the highest rate. Among the female participants; continuance commitment is high in the age range of 30-40, for normative commitment it is 17-22. However no dominant age range was defined for affective commitment. Regarding the marital status; continuance commitment average is higher among married participants; but nominative affective commitment average is higher among single participants. As to the years of study, affective and continuance commitment is higher among senior students while normative commitment is higher among junior students. Moreover; in terms of continuance, affective and normative commitment, those who do not work and have low income have higher level of all there commitment types than those who work and have relatively high income.
Abstract: This paper presents a new feature based dense stereo
matching algorithm to obtain the dense disparity map via dynamic
programming. After extraction of some proper features, we use some
matching constraints such as epipolar line, disparity limit, ordering
and limit of directional derivative of disparity as well. Also, a coarseto-
fine multiresolution strategy is used to decrease the search space
and therefore increase the accuracy and processing speed. The
proposed method links the detected feature points into the chains and
compares some of the feature points from different chains, to
increase the matching speed. We also employ color stereo matching
to increase the accuracy of the algorithm. Then after feature
matching, we use the dynamic programming to obtain the dense
disparity map. It differs from the classical DP methods in the stereo
vision, since it employs sparse disparity map obtained from the
feature based matching stage. The DP is also performed further on a
scan line, between any matched two feature points on that scan line.
Thus our algorithm is truly an optimization method. Our algorithm
offers a good trade off in terms of accuracy and computational
efficiency. Regarding the results of our experiments, the proposed
algorithm increases the accuracy from 20 to 70%, and reduces the
running time of the algorithm almost 70%.
Abstract: Electrical distribution systems are incurring large losses as the loads are wide spread, inadequate reactive power compensation facilities and their improper control. A comprehensive static VAR compensator consisting of capacitor bank in five binary sequential steps in conjunction with a thyristor controlled reactor of smallest step size is employed in the investigative work. The work deals with the performance evaluation through analytical studies and practical implementation on an existing system. A fast acting error adaptive controller is developed suitable both for contactor and thyristor switched capacitors. The switching operations achieved are transient free, practically no need to provide inrush current limiting reactors, TCR size minimum providing small percentages of nontriplen harmonics, facilitates stepless variation of reactive power depending on load requirement so as maintain power factor near unity always. It is elegant, closed loop microcontroller system having the features of self regulation in adaptive mode for automatic adjustment. It is successfully tested on a distribution transformer of three phase 50 Hz, Dy11, 11KV/440V, 125 KVA capacity and the functional feasibility and technical soundness are established. The controller developed is new, adaptable to both LT & HT systems and practically established to be giving reliable performance.
Abstract: The production of devices in nanoscale with specific
molecular rectifying function is one of the most significant goals in
state-of-art technology. In this work we show by ab initio quantum
mechanics calculations coupled with non-equilibrium Green
function, the design of an organic two-terminal device. These
molecular structures have molecular source and drain with several
bridge length (from five up to 11 double bonds). Our results are
consistent with significant features as a molecular rectifier and can be
raised up as: (a) it can be used as bi-directional symmetrical rectifier;
(b) two devices integrated in one (FET with one operational region,
and Thyristor thiristor); (c) Inherent stability due small intrinsic
capacitance under forward/reverse bias. We utilize a scheme for the
transport mechanism based on previous properties of ¤Ç bonds type
that can be successfully utilized to construct organic nanodevices.
Abstract: One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.
Abstract: Along with the basic features of students\' culture
information, with its widely usage oriented on implementation of the
new information technologies in educational process that determines
the search for ways of pointing to the similarity of interdisciplinary
connections content, aims and objectives of the study. In this regard,
the article questions about students\' information culture, and also
presented information about the aims and objectives of the
information culture process among students. In the formation of a
professional interest in relevant information, which is an opportunity
to assist in informing the professional activities of the essence of
effective use of interactive methods and innovative technologies in
the learning process. The result of the experiment proves the
effectiveness of the information culture process of students in
training the system of higher education based on the credit
technology. The main purpose of this paper is a comprehensive
review of students\' information culture.
Abstract: Heterogeneous catalysis is vital for a number of
chemical, refinery and pollution control processes. The use of
catalyst pellets of hollow cylindrical shape provide several distinct
advantages over other common shapes, and can therefore help to
enhance conversion levels in reactors. A better utilization of the
catalytic material is probably most notable of these features due to
the absence of the pellet core, which helps to significantly lower the
effect of the internal transport resistance. This is reflected in the
enhancement of the effectiveness factor. For the case of the first order
irreversible kinetics, a substantial increase in the effectiveness factor
can be obtained by varying shape parameters. Important shape
parameters of a finite hollow cylinder are the ratio of the inside to the
outside radii (κ) and the height to the diameter ratio (γ). A high value
of κ the generally helps to enhance the effectiveness factor. On the
other hand, lower values of the effectiveness factors are obtained
when the dimension of the height and the diameter are comparable.
Thus, the departure of parameter γ from the unity favors higher
effectiveness factor. Since a higher effectiveness factor is a measure
of a greater utilization of the catalytic material, higher conversion
levels can be achieved using the hollow cylindrical pellets possessing
optimized shape parameters.
Abstract: Wrist pulse analysis for identification of health status
is found in Ancient Indian as well as Chinese literature. The preprocessing
of wrist pulse is necessary to remove outlier pulses and
fluctuations prior to the analysis of pulse pressure signal. This paper
discusses the identification of irregular pulses present in the pulse
series and intricacies associated with the extraction of time domain
pulse features. An approach of Dynamic Time Warping (DTW) has
been utilized for the identification of outlier pulses in the wrist pulse
series. The ambiguity present in the identification of pulse features is
resolved with the help of first derivative of Ensemble Average of
wrist pulse series. An algorithm for detecting tidal and dicrotic notch
in individual wrist pulse segment is proposed.
Abstract: This paper addresses integration issues in supply
chain, and tries to investigate how different aspects of integration are
linked with some product features. Integration in this study is
interpreted as "internal", "upstream" (supply), and "downstream"
(demand). Two features of product innovative and quality are
considered. To examine the relationships between supply chain
integrations – as mentioned above, and product features, this research
follows the survey method in automotive industry.The results imply
that supply chain upstream integration has a higher impact on product
quality, comparing to internal and supply chain downstream
integrations. It is also found that the influence of supply chain
downstream integration on product innovation is greater than other
variables. In brief, this study mainly tackles the importance of
specific level of supply chain integrations and its effects on two
product features.