Abstract: Waste management is now a global concern due to its
high environmental impact on climate change. Because of generating
huge amount of waste through our daily activities, managing waste in
an efficient way has become more important than ever. Alternative
Waste Technology (AWT), a new category of waste treatment
technology has been developed for energy recovery in recent years to
address this issue. AWT describes a technology that redirects waste
away from landfill, recovers more useable resources from the waste
flow and reduces the impact on the surroundings. Australia is one of
the largest producers of waste per-capita. A number of AWTs are
using in Australia to produce energy from waste. Presently, it is vital
to identify an appropriate AWT to establish a sustainable waste
management system in Australia. Identification of an appropriate
AWT through Multi-criteria analysis (MCA) of four AWTs by using
five key decision making criteria is presented and discussed in this
paper.
Abstract: Numerical analysis naturally finds applications in all
fields of engineering and the physical sciences, but in the
21st century, the life sciences and even the arts have adopted
elements of scientific computations. The numerical data analysis
became key process in research and development of all the fields [6].
In this paper we have made an attempt to analyze the specified
numerical patterns with reference to the association rule mining
techniques with minimum confidence and minimum support mining
criteria. The extracted rules and analyzed results are graphically
demonstrated. Association rules are a simple but very useful form of
data mining that describe the probabilistic co-occurrence of certain
events within a database [7]. They were originally designed to
analyze market-basket data, in which the likelihood of items being
purchased together within the same transactions are analyzed.
Abstract: It is hard to express emotion through only speech when
we watch a character in a movie or a play because we cannot estimate
the size, kind, and quantity of emotion. So this paper proposes an
artificial emotion model for visualizing current emotion with color and
location in emotion model. The artificial emotion model is designed
considering causality of generated emotion, difference of personality,
difference of continual emotional stimulus, and co-relation of various
emotions. This paper supposed the Emotion Field for visualizing
current emotion with location, and current emotion is expressed by
location and color in the Emotion Field. For visualizing changes
within current emotion, the artificial emotion model is adjusted to
characters in Hamlet.
Abstract: Based on the component approach, three kinds of
dynamic load models, including a single –motor model, a two-motor
model and composite load model have been developed for the
stability studies of Khuzestan power system. The study results are
presented in this paper. Voltage instability is a dynamic phenomenon
and therefore requires dynamic representation of the power system
components. Industrial loads contain a large fraction of induction
machines. Several models of different complexity are available for
the description investigations. This study evaluates the dynamic
performances of several dynamic load models in combination with
the dynamics of a load changing transformer. Case study is steel
industrial substation in Khuzestan power systems.
Abstract: Effectiveness of Artificial Neural Networks (ANN)
and Support Vector Machines (SVM) classifiers for fault diagnosis of
rolling element bearings are presented in this paper. The
characteristic features of vibration signals of rotating driveline that
was run in its normal condition and with faults introduced were used
as input to ANN and SVM classifiers. Simple statistical features such
as standard deviation, skewness, kurtosis etc. of the time-domain
vibration signal segments along with peaks of the signal and peak of
power spectral density (PSD) are used as features to input the ANN
and SVM classifier. The effect of preprocessing of the vibration
signal by Discreet Wavelet Transform (DWT) prior to feature
extraction is also studied. It is shown from the experimental results
that the performance of SVM classifier in identification of bearing
condition is better then ANN and pre-processing of vibration signal
by DWT enhances the effectiveness of both ANN and SVM classifier
Abstract: Although considerable amount of research has attested to the link between work-to-family conflict (WFC) and family-to-work conflict (FWC) and psychological strain and wellbeing, there is a paucity of research investigating the phenomenon in the context of social workers. Moreover, very little is known about the impact of WFC and FWC in developing countries. The present study investigated the mediating effect of psychological strain on the relationship between WFC and FWC with wellbeing of social workers in India. Our findings show that WFC and FWC are influential antecedents of wellbeing; their influence is both direct on psychological strain, and indirect on wellbeing transmitted through psychological strain. Implications of the findings are discussed.
Abstract: One challenging direction of mobile commerce (mcommerce)
that is getting a great deal of attention globally is mobile
financing. The smart-phone and PDA users all around the world are
facing difficulties to become accustomed and trust in m-commerce.
The main rationale can be the slow variation and lack of trust in
mobile payment systems. Mobile payment systems that are in use
need to be more effective and efficient. This paper proposes: the
interface design is not the only factor affecting the m-commerce
adoption and lack of trust; in fact it is the combined effect of
interface usability and trustworthy mobile payment systems, because
it-s the money that the user has to spend at the end of the day, which
the user requires to get transferred securely. The purpose of this
research is to identify the problems regarding the trust and adaption
of m-commerce applications by mobile users and to provide the best
possible solution with respect to human computer interaction (HCI)
principles.
Abstract: It is crucial to quantitatively evaluate the treatment of
epilepsy patients. This study was undertaken to test the hypothesis that
compared to the healthy control subjects, the epilepsy patients have
abnormal resting-state connectivity. In this study, we used the
imaginary part of coherency to measure the resting-state connectivity.
The analysis results shown that compared to the healthy control
subjects, epilepsy patients tend to have abnormal rhythm brain
connectivity over their epileptic focus.
Abstract: Vehicular Ad-Hoc Networks (VANET) can provide
communications between vehicles or infrastructures. It provides the
convenience of driving and the secure driving to reduce accidents. In
VANET, the security is more important because it is closely related to
accidents. Additionally, VANET raises a privacy issue because it can
track the location of vehicles and users- identity when a security
mechanism is provided. In this paper, we analyze the problem of an
existing solution for security requirements required in VANET, and
resolve the problem of the existing method when a key management
mechanism is provided for the security operation in VANET.
Therefore, we show suitability of the Long Term Evolution (LTE) in
VANET for the solution of this problem.
Abstract: The psychological and physical trauma associated with the loss of a human limb can severely impact on the quality of life of an amputee rendering even the most basic of tasks very difficult. A prosthetic device can be of great benefit to the amputee in the performance of everyday human tasks. This paper outlines a proposed mechanical design of a 12 degree-of-freedom SMA actuated artificial hand. It is proposed that the SMA wires be embedded intrinsically within the hand structure which will allow for significant flexibility for use either as a prosthetic hand solution, or as part of a complete lower arm prosthetic solution. A modular approach is taken in the design facilitating ease of manufacture and assembly, and more importantly, also allows the end user to easily replace SMA wires in the event of failure. A biomimetric approach has been taken during the design process meaning that the artificial hand should replicate that of a human hand as far as is possible with due regard to functional requirements. The proposed design has been exposed to appropriate loading through the use of finite element analysis (FEA) to ensure that it is structurally sound. Theoretical analysis of the mechanical framework was also carried out to establish the limits of the angular displacement and velocity of the finger tip as well finger tip force generation. A combination of various polymers and Titanium, which are suitably lightweight, are proposed for the manufacture of the design.
Abstract: The objective of this project is to produce computer
assisted instruction(CAI) for welding and brazing in order to
determine the efficiency of the instruction package and the study
accomplishment of learner by studying through computer assisted
instruction for welding and brazing it was examined through the
target group surveyed from the 30 students studying in the two year
of 5-year-academic program, department of production technology
education, faculty of industrial education and technology, king
mongkut-s university of technology thonburi. The result of the
research indicated that the media evaluated by experts and subject
matter quality evaluation of computer assisted instruction for welding
and brazing was in line for the good criterion. The mean of score
evaluated before the study, during the study and after the study was
34.58, 83.33 and 83.43, respectively. The efficiency of the lesson was
83.33/83.43 which was higher than the expected value, 80/80. The
study accomplishment of the learner, who utilizes computer assisted
instruction for welding and brazing as a media, was higher and equal
to the significance statistical level of 95%. The value was 1.669
which was equal to 35.36>1.669. It could be summarized that
computer assisted instruction for welding and brazing was the
efficient media to use for studying and teaching.
Abstract: ANNARIMA that combines both autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) model is a valuable tool for modeling and forecasting nonlinear time series, yet the over-fitting problem is more likely to occur in neural network models. This paper provides a hybrid methodology that combines both radial basis function (RBF) neural network and auto regression (AR) model based on binomial smoothing (BS) technique which is efficient in data processing, which is called BSRBFAR. This method is examined by using the data of Canadian Lynx data. Empirical results indicate that the over-fitting problem can be eased using RBF neural network based on binomial smoothing which is called BS-RBF, and the hybrid model–BS-RBFAR can be an effective way to improve forecasting accuracy achieved by BSRBF used separately.
Abstract: In this paper the authors propose a protocol, which uses Elliptic Curve Cryptography (ECC) based on the ElGamal-s algorithm, for sending small amounts of data via an authentication server. The innovation of this approach is that there is no need for a symmetric algorithm or a safe communication channel such as SSL. The reason that ECC has been chosen instead of RSA is that it provides a methodology for obtaining high-speed implementations of authentication protocols and encrypted mail techniques while using fewer bits for the keys. This means that ECC systems require smaller chip size and less power consumption. The proposed protocol has been implemented in Java to analyse its features and vulnerabilities in the real world.
Abstract: Data mining uses a variety of techniques each of which
is useful for some particular task. It is important to have a deep
understanding of each technique and be able to perform sophisticated
analysis. In this article we describe a tool built to simulate a variation
of the Kohonen network to perform unsupervised clustering and
support the entire data mining process up to results visualization. A
graphical representation helps the user to find out a strategy to
optimize classification by adding, moving or delete a neuron in order
to change the number of classes. The tool is able to automatically
suggest a strategy to optimize the number of classes optimization, but
also support both tree classifications and semi-lattice organizations of
the classes to give to the users the possibility of passing from one
class to the ones with which it has some aspects in common.
Examples of using tree and semi-lattice classifications are given to
illustrate advantages and problems. The tool is applied to classify
macroeconomic data that report the most developed countries- import
and export. It is possible to classify the countries based on their
economic behaviour and use the tool to characterize the commercial
behaviour of a country in a selected class from the analysis of
positive and negative features that contribute to classes formation.
Possible interrelationships between the classes and their meaning are
also discussed.
Abstract: In automatic manufacturing and assembling of mechanical, electrical and electronic parts one needs to reliably identify the position of components and to extract the information of these components. Data Matrix Codes (DMC) are established by these days in many areas of industrial manufacturing thanks to their concentration of information on small spaces. In today’s usually order-related industry, where increased tracing requirements prevail, they offer further advantages over other identification systems. This underlines in an impressive way the necessity of a robust code reading system for detecting DMC on the components in factories. This paper compares two methods for estimating the angle of orientation of Data Matrix Codes: one method based on the Hough Transform and the other based on the Mean Shift Algorithm. We concentrate on Data Matrix Codes in industrial environment, punched, milled, lasered or etched on different materials in arbitrary orientation.
Abstract: This project relates to a two-wheeled self balancing
robot for transferring loads on different locations along a path. This
robot specifically functions as a dual mode navigation to navigate
efficiently along a desired path. First, as a plurality of distance
sensors mounted at both sides of the body for collecting information
on tilt angle of the body and second, as a plurality of speed sensors
mounted at the bottom of the body for collecting information of the
velocity of the body in relative to the ground. A microcontroller for
processing information collected from the sensors and configured to
set the path and to balance the body automatically while a processor
operatively coupled to the microcontroller and configured to compute
change of the tilt and velocity of the body. A direct current motor
operatively coupled to the microcontroller for controlling the wheels
and characterized in that a remote control is operatively coupled to
the microcontroller to operate the robot in dual navigation modes.
Abstract: In this paper, the effect of modified clay on the
mechanical efficiency of epoxy resin is examined. Studies by X ray
diffraction and microscopic transient electron method show that
modified clay distribution in polymer area is intercalated kind.
Examination the results of mechanical tests shows that existence of
modified clay in epoxy area increases pressure yield strength, tension
module and nano composite fracture toughness in relate of pure
epoxy. By microscopic examinations it is recognized too that the
action of toughness growth of this kind of nano composite is due to
crack deflection, formation of new surfaces and fracture of clay piles.
Abstract: In this paper, the class of weakly left C-wrpp
semigroups which includes the class of weakly left C-rpp semigroups
as a subclass is introduced. To particularly show that the spined
product of a left C-wrpp semigroup and a right normal band which is a
weakly left C-wrpp semifroup by virtue of left C-full Ehremann cyber
groups recently obtained by authors Li-Shum, results obtained by
Tang and Du-Shum are extended and strengthened.
Abstract: An information procuring and processing emerging technology wireless sensor network (WSN) Consists of autonomous nodes with versatile devices underpinned by applications. Nodes are equipped with different capabilities such as sensing, computing, actuation and wireless communications etc. based on application requirements. A WSN application ranges from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. The nodes are deployed independently to cooperatively monitor the physical and environmental conditions. The architecture of WSN differs based on the application requirements and focus on low cost, flexibility, fault tolerance capability, deployment process as well as conserve energy. In this paper we have present the characteristics, architecture design objective and architecture of WSN
Abstract: In this paper, we propose a practical digital music matching system that is robust to variation in sound qualities. The proposed system is subdivided into two parts: client and server. The client part consists of the input, preprocessing and feature extraction modules. The preprocessing module, including the music onset module, revises the value gap occurring on the time axis between identical songs of different formats. The proposed method uses delta-grouped Mel frequency cepstral coefficients (MFCCs) to extract music features that are robust to changes in sound quality. According to the number of sound quality formats (SQFs) used, a music server is constructed with a feature database (FD) that contains different sub feature databases (SFDs). When the proposed system receives a music file, the selection module selects an appropriate SFD from a feature database; the selected SFD is subsequently used by the matching module. In this study, we used 3,000 queries for matching experiments in three cases with different FDs. In each case, we used 1,000 queries constructed by mixing 8 SQFs and 125 songs. The success rate of music matching improved from 88.6% when using single a single SFD to 93.2% when using quadruple SFDs. By this experiment, we proved that the proposed method is robust to various sound qualities.