Abstract: Self-organizing map (SOM) is a well known data
reduction technique used in data mining. It can reveal structure in
data sets through data visualization that is otherwise hard to detect
from raw data alone. However, interpretation through visual
inspection is prone to errors and can be very tedious. There are
several techniques for the automatic detection of clusters of code
vectors found by SOM, but they generally do not take into account
the distribution of code vectors; this may lead to unsatisfactory
clustering and poor definition of cluster boundaries, particularly
where the density of data points is low. In this paper, we propose the
use of an adaptive heuristic particle swarm optimization (PSO)
algorithm for finding cluster boundaries directly from the code
vectors obtained from SOM. The application of our method to
several standard data sets demonstrates its feasibility. PSO algorithm
utilizes a so-called U-matrix of SOM to determine cluster boundaries;
the results of this novel automatic method compare very favorably to
boundary detection through traditional algorithms namely k-means
and hierarchical based approach which are normally used to interpret
the output of SOM.
Abstract: In this paper, we study the numerical method for solving second-order fuzzy differential equations using Adomian method under strongly generalized differentiability. And, we present an example with initial condition having four different solutions to illustrate the efficiency of the proposed method under strongly generalized differentiability.
Abstract: The purpose of this study was primarily assessing how important economic factors namely: The Thai export price of white rice, the exchange rate, and the world rice consumption affect the overall Thai white rice export, using historical data during the period 1989-2013 from the Thai Rice Exporters Association, and Food and Agricultural Organization of the United Nations. The co-integration method, regression analysis, and error correction model were applied to investigate the econometric model. The findings indicated that in the long-run, the world rice consumption, the exchange rate, and the Thai export price of white rice were the important factors affecting the export quantity of Thai white rice respectively, as indicated by their significant coefficients. Meanwhile, the rice export price was an important factor affecting the export quantity of Thai white rice in the short-run. This information is useful in the business, export opportunities, price competitiveness, and policymaker in Thailand.
Abstract: This paper argues that a product development exercise
involves in addition to the conventional stages, several decisions
regarding other aspects. These aspects should be addressed
simultaneously in order to develop a product that responds to the
customer needs and that helps realize objectives of the stakeholders
in terms of profitability, market share and the like. We present a
framework that encompasses these different development
dimensions. The framework shows that a product development
methodology such as the Quality Function Deployment (QFD) is the
basic tool which allows definition of the target specifications of a
new product. Creativity is the first dimension that enables the
development exercise to live and end successfully. A number of
group processes need to be followed by the development team in
order to ensure enough creativity and innovation. Secondly,
packaging is considered to be an important extension of the product.
Branding strategies, quality and standardization requirements,
identification technologies, design technologies, production
technologies and costing and pricing are also integral parts to the
development exercise. These dimensions constitute the proposed
framework. The paper also presents a mathematical model used to
calculate the design targets based on the target costing principle. The
framework is used to study a case of a new product development in
the telecommunications services sector.
Abstract: We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.
Abstract: Automatic Vehicle Identification (AVI) has many
applications in traffic systems (highway electronic toll collection, red
light violation enforcement, border and customs checkpoints, etc.).
License Plate Recognition is an effective form of AVI systems. In
this study, a smart and simple algorithm is presented for vehicle-s
license plate recognition system. The proposed algorithm consists of
three major parts: Extraction of plate region, segmentation of
characters and recognition of plate characters. For extracting the
plate region, edge detection algorithms and smearing algorithms are
used. In segmentation part, smearing algorithms, filtering and some
morphological algorithms are used. And finally statistical based
template matching is used for recognition of plate characters. The
performance of the proposed algorithm has been tested on real
images. Based on the experimental results, we noted that our
algorithm shows superior performance in car license plate
recognition.
Abstract: Fuzzy fingerprint vault is a recently developed cryptographic construct based on the polynomial reconstruction problem to secure critical data with the fingerprint data. However, the previous researches are not applicable to the fingerprint having a few minutiae since they use a fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use an adaptive degree of the polynomial considering the number of minutiae extracted from each user. Also, we apply multiple polynomials to avoid the possible degradation of the security of a simple solution(i.e., using a low-degree polynomial). Based on the experimental results, our method can make the possible attack difficult 2192 times more than using a low-degree polynomial as well as verify the users having a few minutiae.
Abstract: In this study, the possibility of using potato as a
substrate for glutamic acid production by Brevibacterium linens
was investigated. For preparation of fermentation medium, potato
was hydrolyzed by hydrochloridric acid. The medium contained
potato hydrolysate, tween 80, mineral solution, glucose, and
potassium hydrogen phosphate. The initial pH of the medium was
adjusted to 7-7.5. For achieving the optimum time with maximum
yield, the beakers containing the medium and the inoculums were
incubated in a rotary water bath flask shaker for one to five days.
Thin layer choromatography was used for quantitative and
qualitative assay of the glutamic acid produced. The results
revealed that as fermentation time increased, pH of the
fermentation medium significantly decreased (P
Abstract: Knowledge of factors, which influence stress and its
distribution, is of key importance to the successful production of
durable restorations. One of this is the marginal geometry. The
objective of this study was to evaluate, by finite element analysis
(FEA), the influence of different marginal designs on the stress
distribution in teeth prepared for cast metal crowns. Five margin
designs were taken into consideration: shoulderless, chamfer,
shoulder, sloped shoulder and shoulder with bevel. For each kind of
preparation three dimensional finite element analyses were initiated.
Maximal equivalent stresses were calculated and stress patterns were
represented in order to compare the marginal designs. Within the
limitation of this study, the shoulder and beveled shoulder margin
preparations of the teeth are preferred for cast metal crowns from
biomechanical point of view.
Abstract: Integrative teaching methodology is based on
connecting and summarizing knowledge from different subjects in
order to create better understanding of different disciplines and
improvement of competences in general. Integrative teaching
methodology was implemented and realised during one academic
year in 17 Latvian schools according with specially worked out
programme by specialists of different fields for adaptation in social
environment of children and young people with learning, cognitive
functions and motor disorders. Implemented integrative teaching
methodology consisted from three subsections which were
specialised for adaptation in social environment, improvement of
cognitive functions and improvement and harmonization of
personality. The results of investigation showed that the use of
integrative teaching methodology is an effective way for
improvement of learning motivation and negotiation of learning
disorders of different age schoolchildren.
Abstract: This article presents a simple way to perform programmed voice commands for the interface with commercial Digital and Analogue Input/Output PCI cards, used in Robotics and Automation applications. Robots and Automation equipment can "listen" to voice commands and perform several different tasks, approaching to the human behavior, and improving the human- machine interfaces for the Automation Industry. Since most PCI Digital and Analogue Input/Output cards are sold with several DLLs included (for use with different programming languages), it is possible to add speech recognition capability, using a standard speech recognition engine, compatible with the programming languages used. It was created in this work a Visual Basic 6 (the world's most popular language) application, that listens to several voice commands, and is capable to communicate directly with several standard 128 Digital I/O PCI Cards, used to control complete Automation Systems, with up to (number of boards used) x 128 Sensors and/or Actuators.
Abstract: This work presents the mixed-mode II/III prestressed split-cantilever beam specimen for the fracture testing of composite materials. In accordance with the concept of prestressed composite beams one of the two fracture modes is provided by the prestressed state of the specimen, and the other one is increased up to fracture initiation by using a testing machine. The novel beam-like specimen is able to provide any combination of the mode-II and mode-III energy release rates. A simple closed-form solution is developed using beam theory as a data reduction scheme and for the calculation of the energy release rates in the new configuration. The applicability and the limitations of the novel fracture mechanical test are demonstrated using unidirectional glass/polyester composite specimens. If only crack propagation onset is involved then the mixed-mode beam specimen can be used to obtain the fracture criterion of transparent composite materials in the GII - GIII plane in a relatively simple way.
Abstract: Human computer interaction has progressed
considerably from the traditional modes of interaction. Vision based
interfaces are a revolutionary technology, allowing interaction
through human actions, gestures. Researchers have developed
numerous accurate techniques, however, with an exception to few
these techniques are not evaluated using standard HCI techniques. In
this paper we present a comprehensive framework to address this
issue. Our evaluation of a computer vision application shows that in
addition to the accuracy, it is vital to address human factors
Abstract: This article presents the results of researchrelated to the assessment protocol weightedcumulative expected transmission time (WCETT)applied to cognitive radio networks.The development work was based on researchdone by different authors, we simulated a network,which communicates wirelessly, using a licensedchannel, through which other nodes are notlicensed, try to transmit during a given time nodeuntil the station's owner begins its transmission.
Abstract: This paper proposes transient angle stability
agents to enhance power system stability. The proposed transient
angle stability agents divided into two strategy agents. The
first strategy agent is a prediction agent that will predict power
system instability. According to the prediction agent-s output,
the second strategy agent, which is a control agent, is automatically
calculating the amount of active power reduction that can
stabilize the system and initiating a control action. The control
action considered is turbine fast valving. The proposed strategies
are applied to a realistic power system, the IEEE 50-
generator system. Results show that the proposed technique can
be used on-line for power system instability prediction and control.
Abstract: Wireless sensor networks can be used to measure and monitor many challenging problems and typically involve in monitoring, tracking and controlling areas such as battlefield monitoring, object tracking, habitat monitoring and home sentry systems. However, wireless sensor networks pose unique security challenges including forgery of sensor data, eavesdropping, denial of service attacks, and the physical compromise of sensor nodes. Node in a sensor networks may be vanished due to power exhaustion or malicious attacks. To expand the life span of the sensor network, a new node deployment is needed. In military scenarios, intruder may directly organize malicious nodes or manipulate existing nodes to set up malicious new nodes through many kinds of attacks. To avoid malicious nodes from joining the sensor network, a security is required in the design of sensor network protocols. In this paper, we proposed a security framework to provide a complete security solution against the known attacks in wireless sensor networks. Our framework accomplishes node authentication for new nodes with recognition of a malicious node. When deployed as a framework, a high degree of security is reachable compared with the conventional sensor network security solutions. A proposed framework can protect against most of the notorious attacks in sensor networks, and attain better computation and communication performance. This is different from conventional authentication methods based on the node identity. It includes identity of nodes and the node security time stamp into the authentication procedure. Hence security protocols not only see the identity of each node but also distinguish between new nodes and old nodes.
Abstract: Although Model Driven Architecture has taken
successful steps toward model-based software development, this
approach still faces complex situations and ambiguous questions
while applying to real world software systems. One of these
questions - which has taken the most interest and focus - is how
model transforms between different abstraction levels, MDA
proposes. In this paper, we propose an approach based on Story
Driven Modeling and Aspect Oriented Programming to ease these
transformations. Service Oriented Architecture is taken as the target
model to test the proposed mechanism in a functional system.
Service Oriented Architecture and Model Driven Architecture [1]
are both considered as the frontiers of their own domain in the
software world. Following components - which was the greatest step
after object oriented - SOA is introduced, focusing on more
integrated and automated software solutions. On the other hand - and
from the designers' point of view - MDA is just initiating another
evolution. MDA is considered as the next big step after UML in
designing domain.
Abstract: E-tailing websites are often perceived to be static, impersonal and distant. However, with the movement of the World Wide Web to Web 2.0 in recent years, these online websites have been found to display personalities akin to 'humanistic' qualities and project impressions much like its retailing counterpart i.e. salespeople. This paper examines the personality of e-tailing websites and their impact on consumers- initial trust towards the sites. A total of 239 Internet users participated in this field experiment study which utilized 6 online book retailers- websites that the participants had not previously visited before. Analysis revealed that out of four website personalities (sincerity, competence, excitement and sophistication) only sincerity and competence are able to exert an influence in building consumers- trust upon their first visit to the website. The implications of the findings are further elaborated in this paper.
Abstract: For the communication between human and computer
in an interactive computing environment, the gesture recognition is
studied vigorously. Therefore, a lot of studies have proposed efficient
methods about the recognition algorithm using 2D camera captured
images. However, there is a limitation to these methods, such as the
extracted features cannot fully represent the object in real world.
Although many studies used 3D features instead of 2D features for
more accurate gesture recognition, the problem, such as the processing
time to generate 3D objects, is still unsolved in related researches.
Therefore we propose a method to extract the 3D features combined
with the 3D object reconstruction. This method uses the modified
GPU-based visual hull generation algorithm which disables unnecessary
processes, such as the texture calculation to generate three kinds
of 3D projection maps as the 3D feature: a nearest boundary, a farthest
boundary, and a thickness of the object projected on the base-plane. In
the section of experimental results, we present results of proposed
method on eight human postures: T shape, both hands up, right hand
up, left hand up, hands front, stand, sit and bend, and compare the
computational time of the proposed method with that of the previous
methods.
Abstract: It is hard to percept the interaction process with machines when visual information is not available. In this paper, we have addressed this issue to provide interaction through visual techniques. Posture recognition is done for American Sign Language to recognize static alphabets and numbers. 3D information is exploited to obtain segmentation of hands and face using normal Gaussian distribution and depth information. Features for posture recognition are computed using statistical and geometrical properties which are translation, rotation and scale invariant. Hu-Moment as statistical features and; circularity and rectangularity as geometrical features are incorporated to build the feature vectors. These feature vectors are used to train SVM for classification that recognizes static alphabets and numbers. For the alphabets, curvature analysis is carried out to reduce the misclassifications. The experimental results show that proposed system recognizes posture symbols by achieving recognition rate of 98.65% and 98.6% for ASL alphabets and numbers respectively.