Abstract: The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.
Abstract: This paper investigates experimental studies on
vibration suppression for a cantilever beam using an
Electro-Rheological (ER) sandwich shock absorber. ER fluid (ERF) is a
class of smart materials that can undergo significant reversible changes
immediately in its rheological and mechanical properties under the
influence of an applied electric field. Firstly, an ER sandwich beam is
fabricated by inserting a starch-based ERF into a hollow composite
beam. At the same time, experimental investigations are focused on the
frequency response of the ERF sandwich beam. Second, the ERF
sandwich beam is attached to a cantilever beam to become as a shock
absorber. Finally, a fuzzy semi-active vibration control is designed to
suppress the vibration of the cantilever beam via the ERF sandwich
shock absorber. To check the consistency of the proposed fuzzy
controller, the real-time implementation validated the performance of
the controller.
Abstract: The Long-range Energy and Alternatives Planning (LEAP) energy planning system has been developed for South Africa, for the 2005 base year and a limited number of plausible future scenarios that may have significant implications (negative or positive) in terms of environmental impacts. The system quantifies the national energy demand for the domestic, commercial, transport, industry and agriculture sectors, the supply of electricity and liquid fuels, and the resulting emissions. The South African National Energy Research Institute (SANERI) identified the need to develop an environmental assessment tool, based on the LEAP energy planning system, to provide decision-makers and stakeholders with the necessary understanding of the environmental impacts associated with different energy scenarios. A comprehensive analysis of indicators that are used internationally and in South Africa was done and the available data was accessed to select a reasonable number of indicators that could be utilized in energy planning. A consultative process was followed to determine the needs of different stakeholders on the required indicators and also the most suitable form of reporting. This paper demonstrates the application of Energy Environmental Sustainability Indicators (EESIs) as part of the developed tool, which assists with the identification of the environmental consequences of energy generation and use scenarios and thereby promotes sustainability, since environmental considerations can then be integrated into the preparation and adoption of policies, plans, programs and projects. Recommendations are made to refine the tool further for South Africa.
Abstract: Breastfeeding has been receiving much attention of late. Prolonged sitting for breastfeeding often results in back pain of the mothers. This paper reports the findings of a study on the effect of some factors, especially lumbar support, on back pain of breastfeeding mothers. The results showed that the use of lumbar support can reduce back pain of breastfeeding mothers significantly. Back pain was found to increase with breastfeeding time and the rate of increase was lower when lumbar supports were used. When lumbar support thickness was increased gradually from zero (no support) to 11 cm., the degree of low back pain decreased; rapidly at first, then slowly, and leveled off when the thickness reached 9 cm. Younger mothers were less prone to back pain than older mothers. The implications of the findings are discussed.
Abstract: In this paper, we present a novel technique called Self-Learning Expert System (SLES). Unlike Expert System, where there is a need for an expert to impart experiences and knowledge to create the knowledge base, this technique tries to acquire the experience and knowledge automatically. To display this technique at work, a simulation of a mobile robot navigating through an environment with obstacles is employed using visual basic. The mobile robot will move through this area without colliding with any obstacle and save the path that it took. If the mobile robot has to go through a similar environment again, then it will apply this experience to help it move through quicker without having to check for collision.
Abstract: In this paper, we present the region based hidden Markov random field model (RBHMRF), which encodes the characteristics of different brain regions into a probabilistic framework for brain MR image segmentation. The recently proposed TV+L1 model is used for region extraction. By utilizing different spatial characteristics in different brain regions, the RMHMRF model performs beyond the current state-of-the-art method, the hidden Markov random field model (HMRF), which uses identical spatial information throughout the whole brain. Experiments on both real and synthetic 3D MR images show that the segmentation result of the proposed method has higher accuracy compared to existing algorithms.
Abstract: In this work a new offline signature recognition system
based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of
original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained
vectors are calculated to construct a feature vector for each
signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of
the system several experiments are carried out. Offline signature
database from signature verification competition (SVC) 2004 is used
during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.
Abstract: In this paper, a new learning approach for network
intrusion detection using naïve Bayesian classifier and ID3 algorithm
is presented, which identifies effective attributes from the training
dataset, calculates the conditional probabilities for the best attribute
values, and then correctly classifies all the examples of training and
testing dataset. Most of the current intrusion detection datasets are
dynamic, complex and contain large number of attributes. Some of
the attributes may be redundant or contribute little for detection
making. It has been successfully tested that significant attribute
selection is important to design a real world intrusion detection
systems (IDS). The purpose of this study is to identify effective
attributes from the training dataset to build a classifier for network
intrusion detection using data mining algorithms. The experimental
results on KDD99 benchmark intrusion detection dataset demonstrate
that this new approach achieves high classification rates and reduce
false positives using limited computational resources.
Abstract: Most simple nonlinear thresholding rules for
wavelet- based denoising assume that the wavelet coefficients are independent. However, wavelet coefficients of natural images have significant dependencies. This paper attempts to give a recipe for selecting one of the popular image-denoising algorithms based
on VisuShrink, SureShrink, OracleShrink, BayesShrink and BiShrink and also this paper compares different Bivariate models used for image denoising applications. The first part of the paper
compares different Shrinkage functions used for image-denoising.
The second part of the paper compares different bivariate models
and the third part of this paper uses the Bivariate model with modified marginal variance which is based on Laplacian assumption. This paper gives an experimental comparison on six 512x512 commonly used images, Lenna, Barbara, Goldhill,
Clown, Boat and Stonehenge. The following noise powers 25dB,26dB, 27dB, 28dB and 29dB are added to the six standard images and the corresponding Peak Signal to Noise Ratio (PSNR) values
are calculated for each noise level.
Abstract: Perennial ryegrass (Lolium perenne L.) plants are cultivated for lawn constitution and as forage plants. Considerable number of perennial ryegrass genotypes are present in the flora of our country and they present substantial was performed based on a Project supported bu TUBITAK (Project numver : 106O159) and perannial ryegrass genotypes from 8 provinces were collected during 2006. Seeds of perennial ryegrass were collected from 48 different locations. Populations of turfgrass seeds in flowerpots to be 20 and 1 cm deep greenhouse were sown in three replications at 07.07.2007.Then the growth of turfgrass seedlings in the greenhouse in pots showed sufficiently separated from the plants were planted in each population. Plants planted in the garden of the observation scale of 1-9 was evaluated by the quality, 1 = the weakest / worst, 6 = acceptable and 9 = superior or considered as an ideal. Essentially only recognized in assessing the quality of the color of grass, but the color, density, uniformity, texture (texture), illness or environmental stresses are evaluated as a combination reaction. Turfgrass quality 15.11.2007, 19.03.2008, 27.05.2008, 27.11.2008, 07.03.2009 and 02.06.2009 have been 6 times to be in order. Observations made regarding the quality of grass; 3 years according to seasonal environments turf quality genotypes belonging to 14 different populations were found to be 7.5 and above are reserved for future use in breeding works.The number of genotypes belonging to 41 populations in terms of turfgrass quality was determined as 7.9 of 3 year average seasonal. Argıthan between Doğanhisar (Konya) is located 38.09 latitude and 31.40 longitude, altitude 1158 m in the set that population numbered 41.
Abstract: One of the popular methods for recognition of facial
expressions such as happiness, sadness and surprise is based on
deformation of facial features. Motion vectors which show these
deformations can be specified by the optical flow. In this method, for
detecting emotions, the resulted set of motion vectors are compared
with standard deformation template that caused by facial expressions.
In this paper, a new method is introduced to compute the quantity of
likeness in order to make decision based on the importance of
obtained vectors from an optical flow approach. For finding the
vectors, one of the efficient optical flow method developed by
Gautama and VanHulle[17] is used. The suggested method has been
examined over Cohn-Kanade AU-Coded Facial Expression Database,
one of the most comprehensive collections of test images available.
The experimental results show that our method could correctly
recognize the facial expressions in 94% of case studies. The results
also show that only a few number of image frames (three frames) are
sufficient to detect facial expressions with rate of success of about
83.3%. This is a significant improvement over the available methods.
Abstract: Today, computer systems are more and more complex and support growing security risks. The security managers need to find effective security risk assessment methodologies that allow modeling well the increasing complexity of current computer systems but also maintaining low the complexity of the assessment procedure. This paper provides a brief analysis of common security risk assessment methodologies leading to the selection of a proper methodology to fulfill these requirements. Then, a detailed analysis of the most effective methodology is accomplished, presenting numerical examples to demonstrate how easy it is to use.
Abstract: The promises of component-based technology can only be fully realized when the system contains in its design a necessary level of separation of concerns. The authors propose to focus on the concerns that emerge throughout the life cycle of the system and use them as an architectural foundation for the design of a component-based framework. The proposed model comprises a set of superimposed views of the system describing its functional and non-functional concerns. This approach is illustrated by the design of a specific framework for data analysis and data acquisition and supplemented with experiences from using the systems developed with this framework at the Fermi National Accelerator Laboratory.
Abstract: Lanthanide-doped upconversion nanoparticles which can convert near-infrared lights to visible lights have attracted growing interest because of their great potentials in fluorescence imaging. Upconversion fluorescence imaging technique with excitation in the near-infrared (NIR) region has been used for imaging of biological cells and tissues. However, improving the detection sensitivity and decreasing the absorption and scattering in biological tissues are as yet unresolved problems. In this present study, a novel NIR-reflected multispectral imaging system was developed for upconversion fluorescent imaging in small animals. Based on this system, we have obtained the high contrast images without the autofluorescence when biocompatible UCPs were injected near the body surface or deeply into the tissue. Furthermore, we have extracted respective spectra of the upconversion fluorescence and relatively quantify the fluorescence intensity with the multispectral analysis. To our knowledge, this is the first time to analyze and quantify the upconversion fluorescence in the small animal imaging.
Abstract: This paper compares Hilditch, Rosenfeld, Zhang-
Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms
for Javanese character image recognition. Thinning is an effective
process when the focus in not on the size of the pattern, but rather on
the relative position of the strokes in the pattern. The research
analyzes the thinning of 60 Javanese characters.
Time-wise, Zhang-Suen algorithm gives the best results with the
average process time being 0.00455188 seconds. But if we look at
the percentage of pixels that meet one-pixel thickness, Rosenfelt
algorithm gives the best results, with a 99.98% success rate. From the
number of pixels that are erased, NWG algorithm gives the best
results with the average number of pixels erased being 84.12%. It can
be concluded that the Hilditch algorithm performs least successfully
compared to the other three algorithms.
Abstract: This paper presents an approach based on the
adoption of a distributed cognition framework and a non parametric
multicriteria evaluation methodology (DEA) designed specifically to
compare e-commerce websites from the consumer/user viewpoint. In
particular, the framework considers a website relative efficiency as a
measure of its quality and usability. A website is modelled as a black
box capable to provide the consumer/user with a set of
functionalities. When the consumer/user interacts with the website to
perform a task, he/she is involved in a cognitive activity, sustaining a
cognitive cost to search, interpret and process information, and
experiencing a sense of satisfaction. The degree of ambiguity and
uncertainty he/she perceives and the needed search time determine
the effort size – and, henceforth, the cognitive cost amount – he/she
has to sustain to perform his/her task. On the contrary, task
performing and result achievement induce a sense of gratification,
satisfaction and usefulness. In total, 9 variables are measured,
classified in a set of 3 website macro-dimensions (user experience,
site navigability and structure). The framework is implemented to
compare 40 websites of businesses performing electronic commerce
in the information technology market. A questionnaire to collect
subjective judgements for the websites in the sample was purposely
designed and administered to 85 university students enrolled in
computer science and information systems engineering
undergraduate courses.
Abstract: This paper presents a hybrid approach for solving nqueen problem by combination of PSO and SA. PSO is a population based heuristic method that sometimes traps in local maximum. To solve this problem we can use SA. Although SA suffer from many iterations and long time convergence for solving some problems, By good adjusting initial parameters such as temperature and the length of temperature stages SA guarantees convergence. In this article we use discrete PSO (due to nature of n-queen problem) to achieve a good local maximum. Then we use SA to escape from local maximum. The experimental results show that our hybrid method in comparison of SA method converges to result faster, especially for high dimensions n-queen problems.
Abstract: In this paper we present a combined
hashing/watermarking method for image authentication. A robust
image hash, invariant to legitimate modifications, but fragile to
illegitimate modifications is generated from the local image
characteristics. To increase security of the system the watermark is
generated using the image hash as a key. Quantized Index
Modulation of DCT coefficients is used for watermark embedding.
Watermark detection is performed without use of the original image.
Experimental results demonstrate the effectiveness of the presented
method in terms of robustness and fragility.
Abstract: The identification and elimination of bad
measurements is one of the basic functions of a robust state estimator
as bad data have the effect of corrupting the results of state
estimation according to the popular weighted least squares method.
However this is a difficult problem to handle especially when dealing
with multiple errors from the interactive conforming type. In this
paper, a self adaptive genetic based algorithm is proposed. The
algorithm utilizes the results of the classical linearized normal
residuals approach to tune the genetic operators thus instead of
making a randomized search throughout the whole search space it is
more likely to be a directed search thus the optimum solution is
obtained at very early stages(maximum of 5 generations). The
algorithm utilizes the accumulating databases of already computed
cases to reduce the computational burden to minimum. Tests are
conducted with reference to the standard IEEE test systems. Test
results are very promising.
Abstract: As mobile ad hoc networks (MANET) have different
characteristics from wired networks and even from standard wireless
networks, there are new challenges related to security issues that
need to be addressed. Due to its unique features such as open nature,
lack of infrastructure and central management, node mobility and
change of dynamic topology, prevention methods from attacks on
them are not enough. Therefore intrusion detection is one of the
possible ways in recognizing a possible attack before the system
could be penetrated. All in all, techniques for intrusion detection in
old wireless networks are not suitable for MANET. In this paper, we
classify the architecture for Intrusion detection systems that have so
far been introduced for MANETs, and then existing intrusion
detection techniques in MANET presented and compared. We then
indicate important future research directions.