Abstract: The objective of this study is to investigate the performance of the electrocoagulation process for color and COD removal in palm oil wastewater using a 10 L batch reactor. Iron was used as electrodes and the distance between electrodes was 2 cm. The effects of operating parameters: current voltage (6, 12 and 18 volt), reaction time (5, 15, 30, 45 and 60 min) and initial pH (4 and 9) of treatment efficiency were examine. The result showed that decolorization and COD removal efficiency increased with the increase in current voltage and reaction time. The proper condition for decolorization achieved at initial pH 4 and 9 were current voltage of 12 volt, reaction time 30 min. The decolorization efficiency reached 90.4% and 88.9%, respectively. COD removal was achiveved at current voltage 12 volt, reaction time 15 min. COD removal efficiency was 89.2 % and 83.0%, respectively. From the results, to show electrocoagulation process can treat palm oil mill wastewater in both acidic and basic condition at high efficiency for color and COD removal. Consequently, electrocoagulation process can be used or applied as a post-treatment step to improve the quality of the final discharge in term of color and residual COD removal.
Abstract: The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.
Abstract: Image registration is the process of establishing point
by point correspondence between images obtained from a same
scene. This process is very useful in remote sensing, medicine,
cartography, computer vision, etc. Then, the task of registration is to
place the data into a common reference frame by estimating the
transformations between the data sets. In this work, we develop a
rigid point registration method based on the application of genetic
algorithms and Hausdorff distance. First, we extract the feature points
from both images based on the algorithm of global and local
curvature corner. After refining the feature points, we use Hausdorff
distance as similarity measure between the two data sets and for
optimizing the search space we use genetic algorithms to achieve
high computation speed for its inertial parallel. The results show the
efficiency of this method for registration of satellite images.
Abstract: This paper addresses the analysis of the interference between complementary ground component (CGC) base station and mobile earth station (MES). In the frequency sharing scenario between CGC base station and MES, the interference from the adjacent beams must be considered. In this paper, we estimated the interference to MES of an integrated satellite system and the result is presented as the carrier to interference ratio(C/I) with respect to the number of CGC base station in the adjacent beam and the ratio of satellite beam center radius to the total beam radius (R1/R). By using these results, we can determine the minimum separation distance between the CGC base stations of adjacent beam and MES for compatibility. This result can be applied to the CGC base station of an integrated satellite system for the effective frequency sharing.
Abstract: In this paper, the detection and tracking of face, mouth, hands and medication bottles in the context of medication intake monitoring with a camera is presented. This is aimed at recognizing medication intake for elderly in their home setting to avoid an inappropriate use. Background subtraction is used to isolate moving objects, and then, skin and bottle segmentations are done in the RGB normalized color space. We use a minimum displacement distance criterion to track skin color regions and the R/G ratio to detect the mouth. The color-labeled medication bottles are simply tracked based on the color space distance to their mean color vector. For the recognition of medication intake, we propose a three-level hierarchal approach, which uses activity-patterns to recognize the normal medication intake activity. The proposed method was tested with three persons, with different medication intake scenarios, and gave an overall precision of over 98%.
Abstract: We have investigated statistical properties of the defect turbulence in 1D CGLE wherein many body interaction is involved between local depressing wave (LDW) and local standing wave (LSW). It is shown that the counting number fluctuation of LDW is subject to the sub-Poisson statistics (SUBP). The physical origin of the SUBP can be ascribed to pair extinction of LDWs based on the master equation approach. It is also shown that the probability density function (pdf) of inter-LDW distance can be identified by the hyper gamma distribution. Assuming a superstatistics of the exponential distribution (Poisson configuration), a plausible explanation is given. It is shown further that the pdf of amplitude of LDW has a fattail. The underlying mechanism of its fluctuation is examined by introducing a generalized fractional Poisson configuration.
Abstract: Pore water pressure is normally because of
consolidation, compaction and water level fluctuation on reservoir.
Measuring, controlling and analyzing of pore water pressure have
significant importance in both of construction and operation period.
Since end of 2002, (dam start up) nature of KARKHEH dam has
been analyzed by using the gathered information from
instrumentation system of dam. In this lecture dam condition after
start up have been analyzed by using the gathered data from located
piezometers in core of dam. According to TERZAGHI equation and
records of piezometers, consolidation lasted around five years during
early years of construction stage, and current pore water pressure in
core of dam is caused by water level fluctuation in reservoir.
Although there is time lag between water level fluctuation and results
of piezometers. These time lags have been checked and the results
clearly show that one of the most important causes of it is distance
between piezometer and reservoir.
Abstract: This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.
Abstract: This research is aimed at studying the nature of
problems and demands of the training for community leaders in the
upper northeastern region of Thailand. Population and group
samplings are based on 360 community leaders in the region who
have experienced prior training from the Udonthani Rajabhat
University. Stratified random samplings have been drawn upon 186
participants. The research tools is questionnaires. The frequency,
percentage and standard deviation are employed in data analysis. The
findings indicate that most of community leaders are males and
senior adults. The problems in training are associated with the
inconveniences of long-distance travelling to training locations,
inadequacy of learning centers and training sites and high training
costs. The demand of training is basically motivated by a desire for
self-development in modern knowledge in keeping up-to-date with
the changing world and the need for technological application and
facilitation in shortening the distance to training locations and in
limiting expensive training costs.
Abstract: Mammalian genomes contain large number of
retroelements (SINEs, LINEs and LTRs) which could affect
expression of protein coding genes through associated transcription
factor binding sites (TFBS). Activity of the retroelement-associated
TFBS in many genes is confirmed experimentally but their global
functional impact remains unclear. Human SINEs (Alu repeats) and
mouse SINEs (B1 and B2 repeats) are known to be clustered in GCrich
gene rich genome segments consistent with the view that they
can contribute to regulation of gene expression. We have shown
earlier that Alu are involved in formation of cis-regulatory modules
(clusters of TFBS) in human promoters, and other authors reported
that Alu located near promoter CpG islands have an increased
frequency of CpG dinucleotides suggesting that these Alu are
undermethylated. Human Alu and mouse B1/B2 elements have an
internal bipartite promoter for RNA polymerase III containing
conserved sequence motif called B-box which can bind basal
transcription complex TFIIIC. It has been recently shown that TFIIIC
binding to B-box leads to formation of a boundary which limits
spread of repressive chromatin modifications in S. pombe. SINEassociated
B-boxes may have similar function but conservation of
TFIIIC binding sites in SINEs located near mammalian promoters
has not been studied earlier. Here we analysed abundance and
distribution of retroelements (SINEs, LINEs and LTRs) in annotated
sequences of the Database of mammalian transcription start sites
(DBTSS). Fractions of SINEs in human and mouse promoters are
slightly lower than in all genome but >40% of human and mouse
promoters contain Alu or B1/B2 elements within -1000 to +200 bp
interval relative to transcription start site (TSS). Most of these SINEs
is associated with distal segments of promoters (-1000 to -200 bp
relative to TSS) indicating that their insertion at distances >200 bp
upstream of TSS is tolerated during evolution. Distribution of SINEs
in promoters correlates negatively with the distribution of CpG
sequences. Using analysis of abundance of 12-mer motifs from the
B1 and Alu consensus sequences in genome and DBTSS it has been
confirmed that some subsegments of Alu and B1 elements are poorly
conserved which depends in part on the presence of CpG
dinucleotides. One of these CpG-containing subsegments in B1
elements overlaps with SINE-associated B-box and it shows better
conservation in DBTSS compared to genomic sequences. It has been
also studied conservation in DBTSS and genome of the B-box
containing segments of old (AluJ, AluS) and young (AluY) Alu
repeats and found that CpG sequence of the B-box of old Alu is
better conserved in DBTSS than in genome. This indicates that Bbox-
associated CpGs in promoters are better protected from
methylation and mutation than B-box-associated CpGs in genomic
SINEs. These results are consistent with the view that potential
TFIIIC binding motifs in SINEs associated with human and mouse
promoters may be functionally important. These motifs may protect
promoters from repressive histone modifications which spread from
adjacent sequences. This can potentially explain well known
clustering of SINEs in GC-rich gene rich genome compartments and
existence of unmethylated CpG islands.
Abstract: We present a preliminary x-ray study on human-hair
microstructures for a health-state indicator, in particular a cancer
case. As an uncomplicated and low-cost method of x-ray technique,
the human-hair microstructure was analyzed by wide-angle x-ray
diffractions (XRD) and small-angle x-ray scattering (SAXS). The
XRD measurements exhibited the simply reflections at the d-spacing
of 28 Å, 9.4 Å and 4.4 Å representing to the periodic distance of the
protein matrix of the human-hair macrofibrous and the diameter and
the repeated spacing of the polypeptide alpha helixes of the
photofibrils of the human-hair microfibrous, respectively. When
compared to the normal cases, the unhealthy cases including to the
breast- and ovarian-cancer cases obtained higher normalized ratios of
the x-ray diffracting peaks of 9.4 Å and 4.4 Å. This likely resulted
from the varied distributions of microstructures by a molecular
alteration. As an elemental analysis by x-ray fluorescence (XRF), the
normalized quantitative ratios of zinc(Zn)/calcium(Ca) and
iron(Fe)/calcium(Ca) were determined. Analogously, both Zn/Ca and
Fe/Ca ratios of the unhealthy cases were obtained higher than both of
the normal cases were. Combining the structural analysis by XRD
measurements and the elemental analysis by XRF measurements
exhibited that the modified fibrous microstructures of hair samples
were in relation to their altered elemental compositions. Therefore,
these microstructural and elemental analyses of hair samples will be
benefit to associate with a diagnosis of cancer and genetic diseases.
This functional method would lower a risk of such diseases by the
early diagnosis. However, the high-intensity x-ray source, the highresolution
x-ray detector, and more hair samples are necessarily
desired to develop this x-ray technique and the efficiency would be
enhanced by including the skin and fingernail samples with the
human-hair analysis.
Abstract: Nano fibers produced by electrospinning are of industrial and scientific attention due to their special characteristics such as long length, small diameter and high surface area. Applications of electrospun structures in nanotechnology are included tissue scaffolds, fibers for drug delivery, composite reinforcement, chemical sensing, enzyme immobilization, membrane-based filtration, protective clothing, catalysis, solar cells, electronic devices and others. Many polymer and ceramic precursor nano fibers have been successfully electrospun with diameters in the range from 1 nm to several microns. The process is complex so that fiber diameter is influenced by various material, design and operating parameters. The objective of this work is to apply genetic algorithm on the parameters of electrospinning which have the most significant effect on the nano fiber diameter to determine the optimum parameter values before doing experimental set up. Effective factors including initial polymer concentration, initial jet radius, electrical potential, relaxation time, initial elongation, viscosity and distance between nozzle and collector are considered to determine finest diameter which is selected by user.
Abstract: Ants are fascinating creatures that demonstrate the
ability to find food and bring it back to their nest. Their ability as a
colony, to find paths to food sources has inspired the development of
algorithms known as Ant Colony Systems (ACS). The principle of
cooperation forms the backbone of such algorithms, commonly used
to find solutions to problems such as the Traveling Salesman
Problem (TSP). Ants communicate to each other through chemical
substances called pheromones. Modeling individual ants- ability to
manipulate this substance can help an ACS find the best solution.
This paper introduces a Dynamic Ant Colony System with threelevel
updates (DACS3) that enhance an existing ACS. Experiments
were conducted to observe single ant behavior in a colony of
Malaysian House Red Ants. Such behavior was incorporated into the
DACS3 algorithm. We benchmark the performance of DACS3 versus
DACS on TSP instances ranging from 14 to 100 cities. The result
shows that the DACS3 algorithm can achieve shorter distance in
most cases and also performs considerably faster than DACS.
Abstract: Different types of aggregation operators such as the
ordered weighted quasi-arithmetic mean (Quasi-OWA) operator and
the normalized Hamming distance are studied. We introduce the use
of the OWA operator in generalized distances such as the quasiarithmetic
distance. We will call these new distance aggregation the
ordered weighted quasi-arithmetic distance (Quasi-OWAD) operator.
We develop a general overview of this type of generalization and
study some of their main properties such as the distinction between
descending and ascending orders. We also consider different families
of Quasi-OWAD operators such as the Minkowski ordered weighted
averaging distance (MOWAD) operator, the ordered weighted
averaging distance (OWAD) operator, the Euclidean ordered
weighted averaging distance (EOWAD) operator, the normalized
quasi-arithmetic distance, etc.
Abstract: Motion capture devices have been utilized in
producing several contents, such as movies and video games. However,
since motion capture devices are expensive and inconvenient to use,
motions segmented from captured data was recycled and synthesized
to utilize it in another contents, but the motions were generally
segmented by contents producers in manual. Therefore, automatic
motion segmentation is recently getting a lot of attentions. Previous
approaches are divided into on-line and off-line, where on-line
approaches segment motions based on similarities between
neighboring frames and off-line approaches segment motions by
capturing the global characteristics in feature space. In this paper, we
propose a graph-based high-level motion segmentation method. Since
high-level motions consist of several repeated frames within temporal
distances, we consider all similarities among all frames within the
temporal distance. This is achieved by constructing a graph, where
each vertex represents a frame and the edges between the frames are
weighted by their similarity. Then, normalized cuts algorithm is used
to partition the constructed graph into several sub-graphs by globally
finding minimum cuts. In the experiments, the results using the
proposed method showed better performance than PCA-based method
in on-line and GMM-based method in off-line, as the proposed method
globally segment motions from the graph constructed based
similarities between neighboring frames as well as similarities among
all frames within temporal distances.
Abstract: A multi-agent type robot for disaster response in calamity scene is proposed in this paper. The proposed grouped rescue robots can perform cooperative reconnaissance and surveillance to achieve a given rescue mission. The multi-agent rescue of dual set robot consists of one master set and three slave units. The research for this rescue robot system is going to detect at harmful environment where human is unreachable, such as the building is infected with virus or the factory has hazardous liquid in effluent. As a dual set robot, with Bluetooth and communication network, the master set can connect with slave units and send information back to computer by wireless and monitor. Therefore, rescuer can be informed the real-time information in a calamity area. Furthermore, each slave robot is able to obstacle avoidance by ultrasonic sensors, and encodes distance and location by compass. The master robot can integrate every devices information to increase the efficiency of prospected and research unknown area.
Abstract: This paper considers the design of a motion planner
that will simultaneously accomplish control and motion planning of a
n-link nonholonomic mobile manipulator, wherein, a n-link
holonomic manipulator is coupled with a nonholonomic mobile
platform, within an obstacle-ridden environment. This planner,
derived from the Lyapunov-based control scheme, generates
collision-free trajectories from an initial configuration to a final
configuration in a constrained environment cluttered with stationary
solid objects of different shapes and sizes. We demonstrate the
efficiency of the control scheme and the resulting acceleration
controllers of the mobile manipulator with results through computer
simulations of an interesting scenario.
Abstract: PROFIBUS (PROcess FIeld BUS) which is defined with international standarts (IEC61158, EN50170) is the most popular fieldbus, and provides a communication between industrial applications which are located in different control environment and location in manufacturing, process and building automation. Its communication speed is from 9.6 Kbps to 12 Mbps over distances from 100 to 1200 meters, and so it is to be often necessary to interconnect them in order to break these limits. Unfortunately this interconnection raises several issues and the solutions found so far are not very satisfactory. In this paper, we propose a new solution to interconnect PROFIBUS segments, which uses a wireless MAN based on the IEEE 802.16 standard as a backbone system. Also, the solution which is described a model for internetworking unit integrates the traffic generated by PROFIBUS segments into IEEE 802.16 wireless MAN using encapsulation technique.
Abstract: Intrusion detection systems (IDS)are crucial components
of the security mechanisms of today-s computer systems.
Existing research on intrusion detection has focused on sequential
intrusions. However, intrusions can also be formed by concurrent
interactions of multiple processes. Some of the intrusions caused
by these interactions cannot be detected using sequential intrusion
detection methods. Therefore, there is a need for a mechanism that
views the distributed system as a whole. L-BIDS (Lattice-Based
Intrusion Detection System) is proposed to address this problem. In
the L-BIDS framework, a library of intrusions and distributed traces
are represented as lattices. Then these lattices are compared in order
to detect intrusions in the distributed traces.
Abstract: Solar power plants(SPPs) have shown a lot of good outcomes
in providing a various functions depending on industrial expectations by
deploying ad-hoc networking with helps of light loaded and battery powered
sensor nodes. In particular, it is strongly requested to develop an algorithm to
deriver the sensing data from the end node of solar power plants to the sink node
on time. In this paper, based on the above observation we have proposed an
IEEE802.15.4 based self routing scheme for solar power plants. The proposed
beacon based priority routing Algorithm (BPRA) scheme utilizes beacon
periods in sending message with embedding the high priority data and thus
provides high quality of service(QoS) in the given criteria. The performance
measures are the packet Throughput, delivery, latency, total energy
consumption. Simulation results under TinyOS Simulator(TOSSIM) have
shown the proposed scheme outcome the conventional Ad hoc On-Demand
Distance Vector(AODV) Routing in solar power plants.