Abstract: The VoIP networks as alternative method to traditional PSTN system has been implemented in a wide variety of structures
with multiple protocols, codecs, software and hardware–based
distributions. The use of cryptographic techniques let the users to have a secure communication, but the calculate throughput as well as the QoS parameters are affected according to the used algorithm. This
paper analyzes the VoIP throughput and the QoS parameters with
different commercial encryption methods. The measurement–based
approach uses lab scenarios to simulate LAN and WAN
environments. Security mechanisms such as TLS, SIAX2, SRTP,
IPSEC and ZRTP are analyzed with μ-LAW and GSM codecs.
Abstract: This paper addresses a current problem that occurs among Thai internet service providers with regard to bandwidth network quality management. The IPSTAR department of Telecom Organization of Thailand public company (TOT); the largest internet service provider in Thailand, is the case study to analyze the problem that exists. The Internet bandwidth network quality management (iBWQM) framework is mainly applied to the problem that has been found. Bandwidth management policy (BMP) and quality of service (QoS) are two antecedents of iBWQM. This paper investigates internet user behavior, marketing demand and network operation views in order to determine bandwidth management policy (e.g. quota management, scheduling and malicious management). The congestion of bandwidth is also analyzed to enhance quality of service (QoS). Moreover, the iBWQM framework is able to improve the quality of service and increase bandwidth utilization, minimize complaint rate concerns to slow speed, and provide network planning guidelines through Thai Internet services providers.
Abstract: In the upstream we place a piece of ring and rotate
it with 83Hz, 166Hz, 333Hz,and 666H to find the effect of the
periodic distortion.In the experiment this type of the perturbation
will not allow since the mechanical failure of any parts of the
equipment in the upstream will destroy the blade system. This type of
study will be only possible by CFD. We use two pumps NS32
(ENSAM) and three blades pump (Tamagawa Univ). The benchmark
computations were performed without perturbation parts, and confirm
the computational results well agreement in head-flow rate. We
obtained the pressure fluctuation growth rate that is representing the
global instability of the turbo-system. The fluctuating torque
components were 0.01Nm(5000rpm), 0.1Nm(10000rmp),
0.04Nm(20000rmp), 0.15Nm( 40000rmp) respectively. Only for
10000rpm(166Hz) the output toque was random, and it implies that it
creates unsteady flow by separations on the blades, and will reduce the
pressure loss significantly
Abstract: The flow field over a flat roof model building has been numerically investigated in order to determine threedimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data. Wind tunnel measurements and numerical predictions have been compared for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions. The proposed calculations have allowed the development of a preliminary procedure to be used as guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a three-dimensional roof architecture dominated by flow separation.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: This paper presents a solution for the behavioural animation of autonomous virtual agent navigation in virtual environments. We focus on using Dempster-Shafer-s Theory of Evidence in developing visual sensor for virtual agent. The role of the visual sensor is to capture the information about the virtual environment or identifie which part of an obstacle can be seen from the position of the virtual agent. This information is require for vitual agent to coordinate navigation in virtual environment. The virual agent uses fuzzy controller as a navigation system and Fuzzy α - level for the action selection method. The result clearly demonstrates the path produced is reasonably smooth even though there is some sharp turn and also still not diverted too far from the potential shortest path. This had indicated the benefit of our method, where more reliable and accurate paths produced during navigation task.
Abstract: Turbulent forced convection flow in a 2-dimensional channel over periodic grooves is numerically investigated. Finite volume method is used to study the effect of turbulence model. The range of Reynolds number varied from 10000 to 30000 for the ribheight to channel-height ratio (B/H) of 2. The downstream wall is heated by a uniform heat flux while the upstream wall is insulated. The investigation is analyzed with different types of nanoparticles such as SiO2, Al2O3, and ZnO, with water as a base fluid are used. The volume fraction is varied from 1% to 4% and the nanoparticle diameter is utilized between 20nm to 50nm. The results revealed 114% heat transfer enhancement compared to the water in a grooved channel by using SiO2 nanoparticle with volume fraction and nanoparticle diameter of 4% and 20nm respectively.
Abstract: Numerical calculations of flow around a square cylinder are presented using the multi-relaxation-time lattice Boltzmann method at Reynolds number 150. The effects of upstream locations, downstream locations and blockage are investigated systematically. A detail analysis are given in terms of time-trace analysis of drag and lift coefficients, power spectra analysis of lift coefficient, vorticity contours visualizations and phase diagrams. A number of physical quantities mean drag coefficient, drag coefficient, Strouhal number and root-mean-square values of drag and lift coefficients are calculated and compared with the well resolved experimental data and numerical results available in open literature. The results had shown that the upstream, downstream and height of the computational domain are at least 7.5, 37.5 and 12 diameters of the cylinder, respectively.
Abstract: This research studied about green logistics and the
expected benefit that organization gotten when adapted to green
logistics also the organization concerned about the important activity
in green logistics to apply in implementation from study was found
that the benefit of green logistics that organization was gotten by
logistics management which was the increased efficiency process of
management the product from producer to customer all of reduce
production cost, increased value added save energy and prevented
environment together
From study was found that the organization had green logistics to
apply in logistics activities in supply chain since downstream till
upstream to prevent environment as follow 1). Purchasing process,
trade facilitation enhance such as linking of information technology
during business to business (B2B business). 2). Productions process
improved by business logistics improvement 3). Warehouse
management process such as recycled packaging, moving goods in to
warehouse, transportation goods and inside receiving and delivery
products plan.
Abstract: This paper presents an ESN-based Arabic phoneme
recognition system trained with supervised, forced and combined
supervised/forced supervised learning algorithms. Mel-Frequency
Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC)
techniques are used and compared as the input feature extraction
technique. The system is evaluated using 6 speakers from the King
Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia
dialectic and 34 speakers from the Center for Spoken Language
Understanding (CSLU2002) database of speakers with different
dialectics from 12 Arabic countries. Results for the KAPD and
CSLU2002 Arabic databases show phoneme recognition
performances of 72.31% and 38.20% respectively.
Abstract: One of the main issues in Computer Vision is to extract the movement of one or several points or objects of interest in an image or video sequence to conduct any kind of study or control process. Different techniques to solve this problem have been applied in numerous areas such as surveillance systems, analysis of traffic, motion capture, image compression, navigation systems and others, where the specific characteristics of each scenario determine the approximation to the problem. This paper puts forward a Computer Vision based algorithm to analyze fish trajectories in high turbulence conditions in artificial structures called vertical slot fishways, designed to allow the upstream migration of fish through obstructions in rivers. The suggested algorithm calculates the position of the fish at every instant starting from images recorded with a camera and using neural networks to execute fish detection on images. Different laboratory tests have been carried out in a full scale fishway model and with living fishes, allowing the reconstruction of the fish trajectory and the measurement of velocities and accelerations of the fish. These data can provide useful information to design more effective vertical slot fishways.
Abstract: This paper presents a new technique for generating sets of synthetic classifiers to evaluate abstract-level combination methods. The sets differ in terms of both recognition rates of the individual classifiers and degree of similarity. For this purpose, each abstract-level classifier is considered as a random variable producing one class label as the output for an input pattern. From the initial set of classifiers, new slightly different sets are generated by applying specific operators, which are defined at the purpose. Finally, the sets of synthetic classifiers have been used to estimate the performance of combination methods for abstract-level classifiers. The experimental results demonstrate the effectiveness of the proposed approach.
Abstract: Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.
Abstract: Today, incorrect use of lands and land use changes,
excessive grazing, no suitable using of agricultural farms, plowing on
steep slopes, road construct, building construct, mine excavation etc
have been caused increasing of soil erosion and sediment yield. For
erosion and sediment estimation one can use statistical and empirical
methods. This needs to identify land unit map and the map of
effective factors. However, these empirical methods are usually time
consuming and do not give accurate estimation of erosion. In this
study, we applied GIS techniques to estimate erosion and sediment of
Menderjan watershed at upstream Zayandehrud river in center of
Iran. Erosion faces at each land unit were defined on the basis of land
use, geology and land unit map using GIS. The UTM coordinates of
each erosion type that showed more erosion amounts such as rills and
gullies were inserted in GIS using GPS data. The frequency of
erosion indicators at each land unit, land use and their sediment yield
of these indices were calculated. Also using tendency analysis of
sediment yield changes in watershed outlet (Menderjan hydrometric
gauge station), was calculated related parameters and estimation
errors. The results of this study according to implemented watershed
management projects can be used for more rapid and more accurate
estimation of erosion than traditional methods. These results can also
be used for regional erosion assessment and can be used for remote
sensing image processing.
Abstract: The Yasuj city stream named the Beshar supply
water for different usages such as aquaculture farms , drinking,
agricultural and industrial usages. Fish processing plants
,Agricultural farms, waste water of industrial zones and hospitals
waste water which they are generate by human activity produce a
considerable volume of effluent and when they are released in to the
stream they can effect on the water quality and down stream aquatic
systems. This study was conducted to evaluate the effects of outflow
effluent from different human activity and point and non point
pollution sources on the water quality and health of the Beshar
river next to Yasuj. Yasuj is the biggest and most important city in
the Kohkiloye and Boyerahmad province . The Beshar River is one
of the most important aquatic ecosystems in the upstream of the
Karun watershed in south of Iran which is affected by point and non
point pollutant sources . This study was done in order to evaluate the
effects of human activities on the water quality and health of the
Beshar river. This river is approximately 190 km in length and
situated at the geographical positions of 51° 20' to 51° 48' E and 30°
18' to 30° 52' N it is one of the most important aquatic ecosystems of
Kohkiloye and Boyerahmad province in south-west Iran. In this
research project, five study stations were selected to examine water
pollution in the Beshar River systems. Human activity is now one of
the most important factors affecting on hydrology and water quality
of the Beshar river. Humans use large amounts of resources to sustain
various standards of living, although measures of sustainability are
highly variable depending on how sustainability is defined. The
Beshar river ecosystems are particularly sensitive and vulnerable to
human activities. The water samples were analyzed, then some
important water quality parameters such as pH, dissolve oxygen
(DO), Biochemical Oxygen Demand (BOD5), Chemical Oxygen
Demand (COD), Total Suspended Solids (TDS),Turbidity,
Temperature, Nitrates (NO3) and Phosphates (PO4) were estimated
at the two stations. The results show a downward trend in the water
quality at the down stream of the city. The amounts of
BOD5,COD,TSS,T,Turbidity, NO3 and PO4 in the down stream
stations were considerably more than the station 1. By contrast the
amounts of DO in the down stream stations were less than to the
station 1. However when effluent discharge consequence of human
activities are released into the Beshar river near the city, the quality
of river are decreases and the environmental problems of the river
during the next years are predicted to rise.
Abstract: In this paper, an algorithm for detecting and attenuating
puff noises frequently generated under the mobile environment is
proposed. As a baseline system, puff detection system is designed
based on Gaussian Mixture Model (GMM), and 39th Mel Frequency
Cepstral Coefficient (MFCC) is extracted as feature parameters. To
improve the detection performance, effective acoustic features for puff
detection are proposed. In addition, detected puff intervals are
attenuated by high-pass filtering. The speech recognition rate was
measured for evaluation and confusion matrix and ROC curve are used
to confirm the validity of the proposed system.
Abstract: Despite the fact that Arabic language is currently one
of the most common languages worldwide, there has been only a
little research on Arabic speech recognition relative to other
languages such as English and Japanese. Generally, digital speech
processing and voice recognition algorithms are of special
importance for designing efficient, accurate, as well as fast automatic
speech recognition systems. However, the speech recognition process
carried out in this paper is divided into three stages as follows: firstly,
the signal is preprocessed to reduce noise effects. After that, the
signal is digitized and hearingized. Consequently, the voice activity
regions are segmented using voice activity detection (VAD)
algorithm. Secondly, features are extracted from the speech signal
using Mel-frequency cepstral coefficients (MFCC) algorithm.
Moreover, delta and acceleration (delta-delta) coefficients have been
added for the reason of improving the recognition accuracy. Finally,
each test word-s features are compared to the training database using
dynamic time warping (DTW) algorithm. Utilizing the best set up
made for all affected parameters to the aforementioned techniques,
the proposed system achieved a recognition rate of about 98.5%
which outperformed other HMM and ANN-based approaches
available in the literature.
Abstract: This paper explores the plant maintenance management system that has been used by giant oil and gas company in Malaysia. The system also called as PMMS used to manage the upstream operations for more than 100 plants of the case study company. Moreover, from the observations, focus group discussion with PMMS personnel and application through simulation (SAP R/3), the paper reviews the step-by-step approach and the elements that required for the PMMS. The findings show that the PMMS integrates the overall business strategy in upstream operations that consist of asset management, work management and performance management. In addition, PMMS roles are to help operations personnel organize and plan their daily activities, to improve productivity and reduce equipment downtime and to help operations management analyze the facilities and create performance, and to provide and maintain the operational effectiveness of the facilities.
Abstract: Automatic detection of syllable repetition is one of the
important parameter in assessing the stuttered speech objectively.
The existing method which uses artificial neural network (ANN)
requires high levels of agreement as prerequisite before attempting to
train and test ANNs to separate fluent and nonfluent. We propose
automatic detection method for syllable repetition in read speech for
objective assessment of stuttered disfluencies which uses a novel
approach and has four stages comprising of segmentation, feature
extraction, score matching and decision logic. Feature extraction is
implemented using well know Mel frequency Cepstra coefficient
(MFCC). Score matching is done using Dynamic Time Warping
(DTW) between the syllables. The Decision logic is implemented by
Perceptron based on the score given by score matching. Although
many methods are available for segmentation, in this paper it is done
manually. Here the assessment by human judges on the read speech
of 10 adults who stutter are described using corresponding method
and the result was 83%.
Abstract: A state of the art Speaker Identification (SI) system
requires a robust feature extraction unit followed by a speaker
modeling scheme for generalized representation of these features.
Over the years, Mel-Frequency Cepstral Coefficients (MFCC)
modeled on the human auditory system has been used as a standard
acoustic feature set for speech related applications. On a recent
contribution by authors, it has been shown that the Inverted Mel-
Frequency Cepstral Coefficients (IMFCC) is useful feature set for
SI, which contains complementary information present in high
frequency region. This paper introduces the Gaussian shaped filter
(GF) while calculating MFCC and IMFCC in place of typical
triangular shaped bins. The objective is to introduce a higher
amount of correlation between subband outputs. The performances
of both MFCC & IMFCC improve with GF over conventional
triangular filter (TF) based implementation, individually as well as
in combination. With GMM as speaker modeling paradigm, the
performances of proposed GF based MFCC and IMFCC in
individual and fused mode have been verified in two standard
databases YOHO, (Microphone Speech) and POLYCOST
(Telephone Speech) each of which has more than 130 speakers.