Abstract: We introduce an algorithm based on the
morphological shared-weight neural network. Being nonlinear and
translation-invariant, the MSNN can be used to create better
generalization during face recognition. Feature extraction is
performed on grayscale images using hit-miss transforms that are
independent of gray-level shifts. The output is then learned by
interacting with the classification process. The feature extraction and
classification networks are trained together, allowing the MSNN to
simultaneously learn feature extraction and classification for a face.
For evaluation, we test for robustness under variations in gray levels
and noise while varying the network-s configuration to optimize
recognition efficiency and processing time. Results show that the
MSNN performs better for grayscale image pattern classification
than ordinary neural networks.
Abstract: Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.
Abstract: Horseradish (Armoracia rusticana) is a perennial herb belonging to the Brassicaceae family and contains biologically active substances. The aim of the current research was to determine best method for extraction of phenolic compounds from horseradish roots showing high antiradical activity. Three genotypes (No. 105; No. 106 and variety ‘Turku’) of horseradish roots were extracted with eight different solvents: n-hexane, ethyl acetate, diethyl ether, 2-propanol, acetone, ethanol (95%), ethanol / water / acetic acid (80/20/1 v/v/v) and ethanol / water (80/20 by volume) using two extraction methods (conventional and Soxhlet). As the best solvents ethanol and ethanol / water solutions can be chosen. Although in Soxhlet extracts TPC was higher, scavenging activity of DPPH˙ radicals did not increase. It can be concluded that using Soxhlet extraction method more compounds that are not effective antioxidants.
Abstract: In this paper we propose an NLP-based method for
Ontology Population from texts and apply it to semi automatic
instantiate a Generic Knowledge Base (Generic Domain Ontology) in
the risk management domain. The approach is semi-automatic and
uses a domain expert intervention for validation. The proposed
approach relies on a set of Instances Recognition Rules based on
syntactic structures, and on the predicative power of verbs in the
instantiation process. It is not domain dependent since it heavily
relies on linguistic knowledge.
A description of an experiment performed on a part of the
ontology of the PRIMA1 project (supported by the European
community) is given. A first validation of the method is done by
populating this ontology with Chemical Fact Sheets from
Environmental Protection Agency2. The results of this experiment
complete the paper and support the hypothesis that relying on the
predicative power of verbs in the instantiation process improves the
performance.
Abstract: This study examined the effects of eight weeks of
whole-body vibration training (WBVT) on vertical and decuple jump
performance in handball athletes. Sixteen collegiate Level I handball
athletes volunteered for this study. They were divided equally as
control group and experimental group (EG). During the period of the
study, all athletes underwent the same handball specific training, but
the EG received additional WBVT (amplitude: 2 mm, frequency: 20 -
40 Hz) three time per week for eight consecutive weeks. The vertical
jump performance was evaluated according to the maximum height of
squat jump (SJ) and countermovement jump (CMJ). Single factor
ANCOVA was used to examine the differences in each parameter
between the groups after training with the pretest values as a covariate.
The statistic significance was set at p < .05. After 8 weeks WBVT, the
EG had significantly improved the maximal height of SJ (40.92 ± 2.96
cm vs. 48.40 ± 4.70 cm, F = 5.14, p < .05) and the maximal height
CMJ (47.25 ± 7.48 cm vs. 52.20 ± 6.25 cm, F = 5.31, p < .05). 8 weeks
of additional WBVT could improve the vertical and decuple jump
performance in handball athletes. Enhanced motor unit
synchronization and firing rates, facilitated muscular contraction
stretch-shortening cycle, and improved lower extremity
neuromuscular coordination could account for these enhancements.
Abstract: Although backpropagation ANNs generally predict
better than decision trees do for pattern classification problems, they
are often regarded as black boxes, i.e., their predictions cannot be
explained as those of decision trees. In many applications, it is
desirable to extract knowledge from trained ANNs for the users to
gain a better understanding of how the networks solve the problems.
A new rule extraction algorithm, called rule extraction from artificial
neural networks (REANN) is proposed and implemented to extract
symbolic rules from ANNs. A standard three-layer feedforward ANN
is the basis of the algorithm. A four-phase training algorithm is
proposed for backpropagation learning. Explicitness of the extracted
rules is supported by comparing them to the symbolic rules generated
by other methods. Extracted rules are comparable with other methods
in terms of number of rules, average number of conditions for a rule,
and predictive accuracy. Extensive experimental studies on several
benchmarks classification problems, such as breast cancer, iris,
diabetes, and season classification problems, demonstrate the
effectiveness of the proposed approach with good generalization
ability.
Abstract: The feature extraction method(s) used to recognize
hand-printed characters play an important role in ICR applications.
In order to achieve high recognition rate for a recognition system, the
choice of a feature that suits for the given script is certainly an
important task. Even if a new feature required to be designed for a
given script, it is essential to know the recognition ability of the
existing features for that script. Devanagari script is being used in
various Indian languages besides Hindi the mother tongue of majority
of Indians. This research examines a variety of feature extraction
approaches, which have been used in various ICR/OCR applications,
in context to Devanagari hand-printed script. The study is conducted
theoretically and experimentally on more that 10 feature extraction
methods. The various feature extraction methods have been evaluated
on Devanagari hand-printed database comprising more than 25000
characters belonging to 43 alphabets. The recognition ability of the
features have been evaluated using three classifiers i.e. k-NN, MLP
and SVM.
Abstract: Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.
Abstract: Nowadays, hand vein recognition has attracted more attentions in identification biometrics systems. Generally, hand vein image is acquired with low contrast and irregular illumination. Accordingly, if you have a good preprocessing of hand vein image, we can easy extracted the feature extraction even with simple binarization. In this paper, a proposed approach is processed to improve the quality of hand vein image. First, a brief survey on existing methods of enhancement is investigated. Then a Radon Like features method is applied to preprocessing hand vein image. Finally, experiments results show that the proposed method give the better effective and reliable in improving hand vein images.
Abstract: This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.
Abstract: Detection and recognition of the Human Body Composition and extraction their measures (width and length of human body) in images are a major issue in detecting objects and the important field in Image, Signal and Vision Computing in recent years. Finding people and extraction their features in Images are particularly important problem of object recognition, because people can have high variability in the appearance. This variability may be due to the configuration of a person (e.g., standing vs. sitting vs. jogging), the pose (e.g. frontal vs. lateral view), clothing, and variations in illumination. In this study, first, Human Body is being recognized in image then the measures of Human Body extract from the image.
Abstract: In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.
Abstract: The changing economic climate has made global
manufacturing a growing reality over the last decade, forcing
companies from east and west and all over the world to
collaborate beyond geographic boundaries in the design,
manufacture and assemble of products. The ISO10303 and
ISO14649 Standards (STEP and STEP-NC) have been
developed to introduce interoperability into manufacturing
enterprises so as to meet the challenge of responding to
production on demand. This paper describes and illustrates a
STEP compliant CAD/CAPP/CAM System for the manufacture
of rotational parts on CNC turning centers. The information
models to support the proposed system together with the data
models defined in the ISO14649 standard used to create the NC
programs are also described. A structured view of a STEP
compliant CAD/CAPP/CAM system framework supporting the
next generation of intelligent CNC controllers for turn/mill
component manufacture is provided. Finally a proposed
computational environment for a STEP-NC compliant system
for turning operations (SCSTO) is described. SCSTO is the
experimental part of the research supported by the specification
of information models and constructed using a structured
methodology and object-oriented methods. SCSTO was
developed to generate a Part 21 file based on machining
features to support the interactive generation of process plans
utilizing feature extraction. A case study component has been
developed to prove the concept for using the milling and turning
parts of ISO14649 to provide a turn-mill CAD/CAPP/CAM
environment.
Abstract: Due to the dynamic nature of the Cloud, continuous monitoring of QoS requirements is necessary to manage the Cloud computing environment. The process of QoS monitoring and SLA violation detection consists of: collecting low and high level information pertinent to the service, analyzing the collected information, and taking corrective actions when SLA violations are detected. In this paper, we detail the architecture and the implementation of the first step of this process. More specifically, we propose an event-based approach to obtain run time information of services developed as BPEL processes. By catching particular events (i.e., the low level information), our approach recognizes the run-time execution path of a monitored service and uses the BPEL execution patterns to compute QoS of the composite service (i.e., the high level information).
Abstract: Verification of real-time software systems can be
expensive in terms of time and resources. Testing is the main method
of proving correctness but has been shown to be a long and time
consuming process. Everyday engineers are usually unwilling to
adopt formal approaches to correctness because of the overhead
associated with developing their knowledge of such techniques.
Performance modelling techniques allow systems to be evaluated
with respect to timing constraints. This paper describes PARTES, a
framework which guides the extraction of performance models from
programs written in an annotated subset of C.
Abstract: Multimedia, as it stands now is perhaps the most
diverse and rich culture around the globe. One of the major needs of
Multimedia is to have a single system that enables people to
efficiently search through their multimedia catalogues. Many
Domain Specific Systems and architectures have been proposed but
up till now no generic and complete architecture is proposed. In this
paper, we have suggested a generic architecture for Multimedia
Database. The main strengths of our architecture besides being
generic are Semantic Libraries to reduce semantic gap, levels of
feature extraction for more specific and detailed feature extraction
according to classes defined by prior level, and merging of two types
of queries i.e. text and QBE (Query by Example) for more accurate
yet detailed results.
Abstract: The purpose of this study is to analyze the cognitive
and travel experience the situation of the tourist attraction of the sport
tourism in Penghu. This study used a questionnaires, the main island
of Taiwan to Penghu in the way of marine sports tourists adopted the
designated convenience sampling method, a total of 1447 valid
questionnaires. After statistical analysis, this study found that: 1.
Tourists to Penghu sports tourism attraction cognitive as “good air
quality, suitable for water activities". 2. Tourists in Penghu's tourism
experience, “Let me taste the delicious specialties and snacks". 3. The
attraction of the sport tourism, travel experience and perceived value
are correlated, and both the perceived value with a high degree of
predictive ability. Based on the findings of this study not only for
Penghu's tourism industry with the unit in charge of the proposed
operating and suggestions for future research to other researchers.
Abstract: Silk sericin (SS) is a glue-like protein from silkworm
cocoon. With its outstanding moisturization and activation collagen
synthesis properties, silk protein is applied for wound healing. Since
wound dressing in film preparation can facilitate patients-
convenience and reduce risk of wound contraction, SS and polyvinyl
alcohol (PVA) films were prepared with various concentrations of
SS. Their physical properties such as surface density, light
transmission, protein dissolution and tensile modulus were
investigated. The results presented that 3% SS with 2% PVA is the
best ingredient for SS film forming.
Abstract: Mammographic images and data analysis to
facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file
formats and relate these to other patient information.
This would optimize the use of the data as both primary
reporting and enhanced information extraction of research data could be performed from the single dataset. One desired
improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically
available in the images.
The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research
purposes. An interface was developed for accessing, adding,
updating, modifying and extracting data from the common
database, enhancing the future possible application of the data in CAD processing.
Technically, future developments envisaged include the creation of an advanced search function to selects image files
based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a
user friendly configuration utility for importing of the required fields from the DICOM files must be done.
Abstract: A preliminary evaluation of the feasibility of installing small wind turbines on offshore oil and gas extraction platforms is presented. Some aerodynamic considerations are developed in order to determine the best rotor architecture to exploit the wind potential on such installations, assuming that wind conditions over the platforms are similar to those registered on the roofs of urban buildings. Economical considerations about both advantages and disadvantages of the exploitation of wind energy on offshore extraction platforms with respect to conventional offshore wind plants, is also presented. Finally, wind charts of European offshore winds are presented together with a map of the major offshore installations.