Abstract: The current work focuses on rephrasing the harmful
effects of mercury that is being released from a number of sources.
Most of the sources are from the industrial waste water. Different
techniques of mercury removal have been discussed and a brief
comparison among these has been made. The experimental work has
been conducted for two most widely used methods of mercury
removal and comparison in terms of their efficiency has been made.
Abstract: With a surge of stream processing applications novel
techniques are required for generation and analysis of association
rules in streams. The traditional rule mining solutions cannot handle
streams because they generally require multiple passes over the data
and do not guarantee the results in a predictable, small time. Though
researchers have been proposing algorithms for generation of rules
from streams, there has not been much focus on their analysis.
We propose Association rule profiling, a user centric process for
analyzing association rules and attaching suitable profiles to them
depending on their changing frequency behavior over a previous
snapshot of time in a data stream.
Association rule profiles provide insights into the changing nature
of associations and can be used to characterize the associations. We
discuss importance of characteristics such as predictability of
linkages present in the data and propose metric to quantify it. We
also show how association rule profiles can aid in generation of user
specific, more understandable and actionable rules.
The framework is implemented as SUPAR: System for Usercentric
Profiling of Association Rules in streaming data. The
proposed system offers following capabilities:
i) Continuous monitoring of frequency of streaming item-sets
and detection of significant changes therein for association rule
profiling.
ii) Computation of metrics for quantifying predictability of
associations present in the data.
iii) User-centric control of the characterization process: user
can control the framework through a) constraint specification and b)
non-interesting rule elimination.
Abstract: An attempt has been made to investigate the
machinability of zirconia toughened alumina (ZTA) inserts while
turning AISI 4340 steel. The insert was prepared by powder
metallurgy process route and the machining experiments were
performed based on Response Surface Methodology (RSM) design
called Central Composite Design (CCD). The mathematical model of
flank wear, cutting force and surface roughness have been developed
using second order regression analysis. The adequacy of model has
been carried out based on Analysis of variance (ANOVA) techniques.
It can be concluded that cutting speed and feed rate are the two most
influential factor for flank wear and cutting force prediction. For
surface roughness determination, the cutting speed & depth of cut
both have significant contribution. Key parameters effect on each
response has also been presented in graphical contours for choosing
the operating parameter preciously. 83% desirability level has been
achieved using this optimized condition.
Abstract: Feature selection plays an important role in applications with high dimensional data. The assessment of the stability of feature selection/ranking algorithms becomes an important issue when the dataset is small and the aim is to gain insight into the underlying process by analyzing the most relevant features. In this work, we propose a graphical approach that enables to analyze the similarity between feature ranking techniques as well as their individual stability. Moreover, it works with whatever stability metric (Canberra distance, Spearman's rank correlation coefficient, Kuncheva's stability index,...). We illustrate this visualization technique evaluating the stability of several feature selection techniques on a spectral binary dataset. Experimental results with a neural-based classifier show that stability and ranking quality may not be linked together and both issues have to be studied jointly in order to offer answers to the domain experts.
Abstract: The objective of this study is to propose a statistical
modeling method which enables simultaneous term structure
estimation of the risk-free interest rate, hazard and loss given default,
incorporating the characteristics of the bond issuing company such as
credit rating and financial information. A reduced form model is used
for this purpose. Statistical techniques such as spline estimation and
Bayesian information criterion are employed for parameter estimation
and model selection. An empirical analysis is conducted using the
information on the Japanese bond market data. Results of the
empirical analysis confirm the usefulness of the proposed method.
Abstract: As data to be stored in storage subsystems
tremendously increases, data protection techniques have become more
important than ever, to provide data availability and reliability. In this
paper, we present the file system-based data protection (WOWSnap)
that has been implemented using WORM (Write-Once-Read-Many)
scheme. In the WOWSnap, once WORM files have been created, only
the privileged read requests to them are allowed to protect data against
any intentional/accidental intrusions. Furthermore, all WORM files
are related to their protection cycle that is a time period during which
WORM files should securely be protected. Once their protection cycle
is expired, the WORM files are automatically moved to the
general-purpose data section without any user interference. This
prevents the WORM data section from being consumed by
unnecessary files. We evaluated the performance of WOWSnap on
Linux cluster.
Abstract: The OTOP Entrepreneurship that used to create
substantial source of income for local Thai communities are now in a
stage of exigent matters that required assistances from public sectors
due to over Entrepreneurship of duplicative ideas, unable to adjust
costs and prices, lack of innovation, and inadequate of quality
control. Moreover, there is a repetitive problem of middlemen who
constantly corner the OTOP market. Local OTOP producers become
easy preys since they do not know how to add more values, how to
create and maintain their own brand name, and how to create proper
packaging and labeling. The suggested solutions to local OTOP
producers are to adopt modern management techniques, to find
knowhow to add more values to products and to unravel other
marketing problems. The objectives of this research are to study the
prevalent OTOP products management and to discover direction to
manage OTOP products to enhance the effectiveness of OTOP
Entrepreneurship in Nonthaburi Province, Thailand. There were 113
participants in this study. The research tools can be divided into two
parts: First part is done by questionnaire to find responses of the
prevalent OTOP Entrepreneurship management. Second part is the
use of focus group which is conducted to encapsulate ideas and local
wisdom. Data analysis is performed by using frequency, percentage,
mean, and standard deviation as well as the synthesis of several small
group discussions. The findings reveal that 1) Business Resources:
the quality of product is most important and the marketing of product
is least important. 2) Business Management: Leadership is most
important and raw material planning is least important. 3) Business
Readiness: Communication is most important and packaging is least
important. 4) Support from public sector: Certified from the
government is most important and source of raw material is the least
important.
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) is one of the techniques for high speed data rate communication with main consideration for 4G and 5G systems. In OFDM, there are several mapping schemes which provide a way of parallel transmission. In this paper, comparisons of mapping schemes used by some standards have been made and also has been discussed about the performance of the non-conventional modulation technique. The Comparisons of Bit Error Rate (BER) performances for conventional and non-conventional modulation schemes have been done using MATLAB software. Mentioned schemes used in OFDM system can be selected on the basis of the requirement of power or spectrum efficiency and BER analysis.
Abstract: The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method. In our work the effectiveness of proposed changes to MFCC called Modified Function Cepstral Coefficients (MODFCC) were tested and compared against the original MFCC and RASTA-MFCC features. The prosodic features such as jitter and shimmer are added to baseline spectral features. The above-mentioned techniques were tested with impulsive signals under various noisy conditions within AURORA databases.
Abstract: Ultrafast doped zinc oxide crystal promised us a good
opportunity to build new instruments for ICF fusion neutron
measurement. Two pulsed neutron detectors based on ZnO crystal
wafer have been conceptually designed, the superfast ZnO timing
detector and the scintillation recoil proton neutron detection system.
The structure of these detectors was presented, and some characters
were studied as well. The new detectors could be much faster than
existing systems, and would be more competent for ICF neutron
diagnostics.
Abstract: Wireless Sensor Network is Multi hop Self-configuring
Wireless Network consisting of sensor nodes. The deployment of
wireless sensor networks in many application areas, e.g., aggregation
services, requires self-organization of the network nodes into clusters.
Efficient way to enhance the lifetime of the system is to partition the
network into distinct clusters with a high energy node as cluster head.
The different methods of node clustering techniques have appeared in
the literature, and roughly fall into two families; those based on the
construction of a dominating set and those which are based solely on
energy considerations. Energy optimized cluster formation for a set
of randomly scattered wireless sensors is presented. Sensors within a
cluster are expected to be communicating with cluster head only. The
energy constraint and limited computing resources of the sensor nodes
present the major challenges in gathering the data. In this paper we
propose a framework to study how partially correlated data affect the
performance of clustering algorithms. The total energy consumption
and network lifetime can be analyzed by combining random geometry
techniques and rate distortion theory. We also present the relation
between compression distortion and data correlation.
Abstract: Spam mails are unwanted mails sent to large number
of users. Spam mails not only consume the network resources, but
cause security threats as well. This paper proposes an efficient
technique to detect, and to prevent spam mail in the sender side rather
than the receiver side. This technique is based on a counter set on the
sender server. When a mail is transmitted to the server, the mail server
checks the number of the recipients based on its counter policy. The
counter policy performed by the mail server is based on some
pre-defined criteria. When the number of recipients exceeds the
counter policy, the mail server discontinues the rest of the process, and
sends a failure mail to sender of the mail; otherwise the mail is
transmitted through the network. By using this technique, the usage of
network resources such as bandwidth, and memory is preserved. The
simulation results in real network show that when the counter is set on
the sender side, the time required for spam mail detection is 100 times
faster than the time the counter is set on the receiver side, and the
network resources are preserved largely compared with other
anti-spam mail techniques in the receiver side.
Abstract: This paper presents an efficient VLSI architecture
design to achieve real time video processing using Full-Search Block
Matching (FSBM) algorithm. The design employs parallel bank
architecture with minimum latency, maximum throughput, and full
hardware utilization. We use nine parallel processors in our
architecture and each controlled by a state machine. State machine
control implementation makes the design very simple and cost
effective. The design is implemented using VHDL and the
programming techniques we incorporated makes the design
completely programmable in the sense that the search ranges and the
block sizes can be varied to suit any given requirements. The design
can operate at frequencies up to 36 MHz and it can function in QCIF
and CIF video resolution at 1.46 MHz and 5.86 MHz, respectively.
Abstract: The authors present an algorithm for order reduction of linear time invariant dynamic systems using the combined advantages of the eigen spectrum analysis and the error minimization by particle swarm optimization technique. Pole centroid and system stiffness of both original and reduced order systems remain same in this method to determine the poles, whereas zeros are synthesized by minimizing the integral square error in between the transient responses of original and reduced order models using particle swarm optimization technique, pertaining to a unit step input. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. The algorithm is illustrated with the help of two numerical examples and the results are compared with the other existing techniques.
Abstract: By systematically applying different engineering
methods, difficult financial problems become approachable. Using a
combination of theory and techniques such as wavelet transform,
time series data mining, Markov chain based discrete stochastic
optimization, and evolutionary algorithms, this work formulated a
strategy to characterize and forecast non-linear time series. It
attempted to extract typical features from the volatility data sets of
S&P100 and S&P500 indices that include abrupt drops, jumps and
other non-linearity. As a result, accuracy of forecasting has reached
an average of over 75% surpassing any other publicly available
results on the forecast of any financial index.
Abstract: In this paper channel estimation techniques are
considered as the support methods for OFDM transmission systems
based on Non Binary LDPC (Low Density Parity Check) codes.
Standard frequency domain pilot aided LS (Least Squares) and
LMMSE (Linear Minimum Mean Square Error) estimators are
investigated. Furthermore, an iterative algorithm is proposed as a
solution exploiting the NB-LDPC channel decoder to improve the
performance of the LMMSE estimator. Simulation results of signals
transmitted through fading mobile channels are presented to compare
the performance of the proposed channel estimators.
Abstract: Enterprise Architecture (EA) is a framework for description, coordination and alignment of all activities across the organization in order to achieve strategic goals using ICT enablers. A number of EA-compatible frameworks have been developed. We, in this paper, mainly focus on Federal Enterprise Architecture Framework (FEAF) since its reference models are plentiful. Among these models we are interested here in its business reference model (BRM). The test process is one important subject of an EA project which is to somewhat overlooked. This lack of attention may cause drawbacks or even failure of an enterprise architecture project. To address this issue we intend to use International Software Testing Qualification Board (ISTQB) framework and standard test suites to present a method to improve EA testing process. The main challenge is how to communicate between the concepts of EA and ISTQB. In this paper, we propose a method for integrating these concepts.
Abstract: This paper presents a new study on the applications of
optimization and regression analysis techniques for optimal
calculation of partial ratios of four-step helical gearboxes for getting
minimal gearbox length. In the paper, basing on the moment
equilibrium condition of a mechanic system including four gear units
and their regular resistance condition, models for determination of the
partial ratios of the gearboxes are proposed. In particular, explicit
models for calculation of the partial ratios are proposed by using
regression analysis. Using these models, the determination of the
partial ratios is accurate and simple.
Abstract: Combined therapy using Interferon and Ribavirin is the standard treatment in patients with chronic hepatitis C. However, the number of responders to this treatment is low, whereas its cost and side effects are high. Therefore, there is a clear need to predict patient’s response to the treatment based on clinical information to protect the patients from the bad drawbacks, Intolerable side effects and waste of money. Different machine learning techniques have been developed to fulfill this purpose. From these techniques are Associative Classification (AC) and Decision Tree (DT). The aim of this research is to compare the performance of these two techniques in the prediction of virological response to the standard treatment of HCV from clinical information. 200 patients treated with Interferon and Ribavirin; were analyzed using AC and DT. 150 cases had been used to train the classifiers and 50 cases had been used to test the classifiers. The experiment results showed that the two techniques had given acceptable results however the best accuracy for the AC reached 92% whereas for DT reached 80%.
Abstract: This paper highlights some interesting facts on South African-s waste situation and management strategies, in particular the Integrated Waste Management. South Africa supports a waste hierarchy by promoting cleaner production, waste minimisation, reuse, recycling and waste treatment with disposal and remediation as the last preferred options in waste management. The drivers for waste management techniques are identified as increased demand for waste service provision; increased demand for waste minimisation; recycling and recovery; land use, physical and environmental limitations; and socio-economic and demographic factors. The South African government recognizes the importance of scientific research as outlined on the white paper on Integrated Pollution and Waste Management (IP and WM) (DEAT, 2000).