Abstract: This paper is introduced a modification to Diffie-
Hellman protocol to be applicable on the decimal numbers, which
they are the numbers between zero and one. For this purpose we
extend the theory of the congruence. The new congruence is over
the set of the real numbers and it is called the “real congruence"
or the “real modulus". We will refer to the existing congruence by
the “integer congruence" or the “integer modulus". This extension
will define new terms and redefine the existing terms. As the
properties and the theorems of the integer modulus are extended as
well. Modified Diffie-Hellman key exchange protocol is produced a
sharing, secure and decimal secret key for the the cryptosystems that
depend on decimal numbers.
Abstract: Our study proposes an alternative method in building
Fuzzy Rule-Based System (FRB) from Support Vector Machine
(SVM). The first set of fuzzy IF-THEN rules is obtained through
an equivalence of the SVM decision network and the zero-ordered
Sugeno FRB type of the Adaptive Network Fuzzy Inference System
(ANFIS). The second set of rules is generated by combining the
first set based on strength of firing signals of support vectors using
Gaussian kernel. The final set of rules is then obtained from the
second set through input scatter partitioning. A distinctive advantage
of our method is the guarantee that the number of final fuzzy IFTHEN
rules is not more than the number of support vectors in the
trained SVM. The final FRB system obtained is capable of performing
classification with results comparable to its SVM counterpart, but it
has an advantage over the black-boxed SVM in that it may reveal
human comprehensible patterns.
Abstract: Ontology Matching is a task needed in various applica-tions, for example for comparison or merging purposes. In literature,many algorithms solving the matching problem can be found, butmost of them do not consider instances at all. Mappings are deter-mined by calculating the string-similarity of labels, by recognizinglinguistic word relations (synonyms, subsumptions etc.) or by ana-lyzing the (graph) structure. Due to the facts that instances are oftenmodeled within the ontology and that the set of instances describesthe meaning of the concepts better than their meta information,instances should definitely be incorporated into the matching process.In this paper several novel instance-based matching algorithms arepresented which enhance the quality of matching results obtainedwith common concept-based methods. Different kinds of formalismsare use to classify concepts on account of their instances and finallyto compare the concepts directly.KeywordsInstances, Ontology Matching, Semantic Web
Abstract: This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.
Abstract: Snake bite cases in Malaysia most often involve the
species Naja-naja and Calloselasma rhodostoma. In keeping with the
need for a rapid snake venom detection kit in a clinical setting, plate
and dot-ELISA test for the venoms of Naja-naja sumatrana,
Calloselasma rhodostoma and the cobra venom fraction V antigen
was developed. Polyclonal antibodies were raised and further used to
prepare the reagents for the dot-ELISA test kit which was tested in
mice, rabbit and virtual human models. The newly developed dot-
ELISA kit was able to detect a minimum venom concentration of
244ng/ml with cross reactivity of one antibody type. The dot-ELISA
system was sensitive and specific for all three snake venom types in
all tested animal models. The lowest minimum venom concentration
detectable was in the rabbit model, 244ng/ml of the cobra venom
fraction V antigen. The highest minimum venom concentration was
in mice, 1953ng/ml against a multitude of venoms. The developed
dot-ELISA system for the detection of three snake venom types was
successful with a sensitivity of 95.8% and specificity of 97.9%.
Abstract: This research deals with a flexible flowshop
scheduling problem with arrival and delivery of jobs in groups and
processing them individually. Due to the special characteristics of
each job, only a subset of machines in each stage is eligible to
process that job. The objective function deals with minimization of
sum of the completion time of groups on one hand and minimization
of sum of the differences between completion time of jobs and
delivery time of the group containing that job (waiting period) on the
other hand. The problem can be stated as FFc / rj , Mj / irreg which
has many applications in production and service industries. A
mathematical model is proposed, the problem is proved to be NPcomplete,
and an effective heuristic method is presented to schedule
the jobs efficiently. This algorithm can then be used within the body
of any metaheuristic algorithm for solving the problem.
Abstract: Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of classifiers using the same learning algorithm for the base-classifiers. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using a voting methodology of bagging and boosting ensembles with 10 subclassifiers in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-classifiers, as well as other well known combining methods, on standard benchmark datasets and the proposed technique was the most accurate.
Abstract: An experimental campaign of measurements for a
Darrieus vertical-axis wind turbine (VAWT) is presented for open
field conditions. The turbine is characterized by a twisted bladed
design, each blade being placed at a fixed distance from the rotational
shaft. The experimental setup to perform the acquisitions is described.
The results are lower than expected, due to the high influence of the
wind shear.
Abstract: In the present work, we propose a new technique to
enhance the learning capabilities and reduce the computation
intensity of a competitive learning multi-layered neural network
using the K-means clustering algorithm. The proposed model use
multi-layered network architecture with a back propagation learning
mechanism. The K-means algorithm is first applied to the training
dataset to reduce the amount of samples to be presented to the neural
network, by automatically selecting an optimal set of samples. The
obtained results demonstrate that the proposed technique performs
exceptionally in terms of both accuracy and computation time when
applied to the KDD99 dataset compared to a standard learning
schema that use the full dataset.
Abstract: The element of justice or al-‘adl in the context of
Islamic critical thinking deals with the notion of justice in a thinking
process which critically rationalizes the truth in a fair and objective
manner with no irrelevant interference that can jeopardize a sound
judgment. This Islamic axiological element is vital in technological
decision making as it addresses the issues of religious values and
ethics that are primarily set to fulfill the purpose of human life on
earth. The main objective of this study was to examine and analyze
the perception of Muslim engineering students in Malaysian higher
education institutions towards the concept of al-‘adl as an essential
element of Islamic critical thinking. The study employed mixed
methods approach that comprises data collection from the
questionnaire survey and the interview responses. A total of 557
Muslim engineering undergraduates from six Malaysian universities
participated in the study. The study generally indicated that Muslim
engineering undergraduates in the higher institutions have rather
good comprehension and consciousness for al-‘adl with a slight
awareness on the importance of objective thinking. Nonetheless there
were a few items on the concept that have implied a comparatively
low perception on the rational justice in Islam as the means to grasp
the ultimate truth.
Abstract: Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.
Abstract: The knowledge base of welding defect recognition is
essentially incomplete. This characteristic determines that the recognition results do not reflect the actual situation. It also has a further influence on the classification of welding quality. This paper is
concerned with the study of a rough set based method to reduce the influence and improve the classification accuracy. At first, a rough set
model of welding quality intelligent classification has been built. Both condition and decision attributes have been specified. Later on, groups
of the representative multiple compound defects have been chosen
from the defect library and then classified correctly to form the
decision table. Finally, the redundant information of the decision table has been reducted and the optimal decision rules have been reached. By this method, we are able to reclassify the misclassified defects to
the right quality level. Compared with the ordinary ones, this method
has higher accuracy and better robustness.
Abstract: Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.
Abstract: In our modern world, more physical transactions are being substituted by electronic transactions (i.e. banking, shopping, and payments), many businesses and companies are performing most of their operations through the internet. Instead of having a physical commerce, internet visitors are now adapting to electronic commerce (e-Commerce). The ability of web users to reach products worldwide can be greatly benefited by creating friendly and personalized online business portals. Internet visitors will return to a particular website when they can find the information they need or want easily. Dealing with this human conceptualization brings the incorporation of Artificial/Computational Intelligence techniques in the creation of customized portals. From these techniques, Fuzzy-Set technologies can make many useful contributions to the development of such a human-centered endeavor as e-Commerce. The main objective of this paper is the implementation of a Paradigm for the Intelligent Design and Operation of Human-Computer interfaces. In particular, the paradigm is quite appropriate for the intelligent design and operation of software modules that display information (such Web Pages, graphic user interfaces GUIs, Multimedia modules) on a computer screen. The human conceptualization of the user personal information is analyzed throughout a Cascaded Fuzzy Inference (decision-making) System to generate the User Ascribe Qualities, which identify the user and that can be used to customize portals with proper Web links.
Abstract: The aim of every software product is to achieve an
appropriate level of software quality. Developers and designers are
trying to produce readable, reliable, maintainable, reusable and
testable code. To help achieve these goals, several approaches have
been utilized. In this paper, refactoring technique was used to
evaluate software quality with a quality index. It is composed of
different metric sets which describes various quality aspects.
Abstract: Due to the emergence of “Humanized Healthcare"
introduced by Professor Dr. Prawase Wasi in 2003[1], the
development of this paradigm tends to be widely implemented. The
organizations included Healthcare Accreditation Institute (public
organization), National Health Foundation, Mahidol University in
cooperation with Thai Health Promotion Foundation, and National
Health Security Office (Thailand) have selected the hospitals or
infirmaries that are qualified for humanized healthcare since 2008-
2010 and 35 of them are chosen to be the outstandingly navigating
organizations for the development of humanized healthcare,
humanized healthcare award [2].
The research aims to study the current issue, characteristics and
patterns of hospital administration contributing to humanized
healthcare system in Thailand. The selected case studies are from
four hospitals including Dansai Crown Prince Hospital, Leoi;
Ubolrattana Hospital, Khon Kaen; Kapho Hospital, Pattani; and
Prathai Hospital, Nakhonrachasima. The methodology is in-depth
interviewing with 10 staffs working as hospital executive directors,
and representatives from leader groups including directors,
multidisciplinary hospital committees, personnel development
committees, physicians and nurses in each hospital. (Total=40) In
addition, focus group discussions between hospital staffs and general
people (including patients and their relatives, the community leader,
and other people) are held by means of setting 4 groups including 8
people within each group. (Total=128) The observation on the
working in each hospital is also implemented. The findings of the
study reveal that there are five important aspects found in each
hospital including (1) the quality improvement under the mental and
spiritual development policy from the chief executives and lead
teams, leaders as Role model and they have visionary leadership; (2)
the participation hospital administration system focusing on learning
process and stakeholder- needs, spiritual human resource
management and development; (3) the relationship among people
especially staffs, team work skills, mutual understanding, effective
communication and personal inner-development; (4) organization
culture relevant to the awareness of patients- rights as well as the
participation policy including spiritual growth achieving to the same
goals, sharing vision, developing public mind, and caring; and (5)
healing structures or environment providing warmth and convenience
for hospital staffs, patients and their relatives and visitors.
Abstract: In this paper, we propose the Modified Synchronous Detection (MSD) Method for determining the reference compensating currents of the shunt active power filter under non sinusoidal voltages conditions. For controlling the inverter switching we used the PI regulator. The numerical simulation results, using Power System Blockset Toolbox PSB of Matlab, from a complete structure, are presented and discussed.
Abstract: Serious games have proven to be a useful instrument
to engage learners and increase motivation. Nevertheless, a broadly
accepted, practical instructional design approach to serious games
does not exist. In this paper, we introduce the use of an instructional
design model that has not been applied to serious games yet, and has
some advantages compared to other design approaches. We present
the case of mechanics mechatronics education to illustrate the close
match with timing and role of knowledge and information that the
instructional design model prescribes and how this has been
translated to a rigidly structured game design. The structured
approach answers the learning needs of applicable knowledge within
the target group. It combines advantages of simulations with
strengths of entertainment games to foster learner-s motivation in the
best possible way. A prototype of the game will be evaluated along a
well-respected evaluation method within an advanced test setting
including test and control group.
Abstract: Iron ore and coal are the two major important raw
materials being used in Iron making industries. Usually ore fines
containing around 5% Alumina are rejected due to higher proportion
of alumina. Therefore, a technology or process which may reduce
the alumina content by 2% by beneficiation process will be highly
attractive . In addition fine coals with ash content is used nearly 12%
is directly injected in blast furnace. Fast fluidization is a technology
by using dry beneficiation of coal and iron ore can be done. During
the fluidization process the iron ore band coal is fluidized at high
velocity in the riser of a fast fluidized bed, the heavier and coarse
particles is generally settled at the bottom in a dense zone of the riser
while the finer and lighter particle are entrained to the top dilute zone
and then via a cyclone is fed back to the bottom of the riser column.
Most of the alumina and low ash fine size coals being lighter are
expected to move up to the riser and by a natural beneficiation of
ores is expected to take place in the riser. Therefore in this study an
attempt has been made for dry beneficiation of iron ore and coal in a
fluidized bed and its hydrodynamic characterization.
Abstract: One of the main processes of supply chain
management is supplier selection process which its accurate
implementation can dramatically increase company competitiveness.
In presented article model developed based on the features of
second tiers suppliers and four scenarios are predicted in order to
help the decision maker (DM) in making up his/her mind. In addition
two tiers of suppliers have been considered as a chain of suppliers.
Then the proposed approach is solved by a method combined of
concepts of fuzzy set theory (FST) and linear programming (LP)
which has been nourished by real data extracted from an engineering
design and supplying parts company. At the end results reveal the
high importance of considering second tier suppliers features as
criteria for selecting the best supplier.