Abstract: CONWIP (constant work-in-process) as a pull
production system have been widely studied by researchers to date.
The CONWIP pull production system is an alternative to pure push
and pure pull production systems. It lowers and controls inventory
levels which make the throughput better, reduces production lead
time, delivery reliability and utilization of work. In this article a
CONWIP pull production system was simulated. It was simulated
push and pull planning system. To compare these systems via a
production planning system (PPS) game were adjusted parameters of
each production planning system. The main target was to reduce the
total WIP and achieve throughput and delivery reliability to
minimum values. Data was recorded and evaluated. A future state
was made for real production of plastic components and the setup of
the two indicators with CONWIP pull production system which can
greatly help the company to be more competitive on the market.
Abstract: This paper presents a novel approach for representing
the spatio-temporal topology of the camera network with overlapping
and non-overlapping fields of view (FOVs). The topology is
determined by tracking moving objects and establishing object
correspondence across multiple cameras. To track people successfully
in multiple camera views, we used the Merge-Split (MS) approach for
object occlusion in a single camera and the grid-based approach for
extracting the accurate object feature. In addition, we considered the
appearance of people and the transition time between entry and exit
zones for tracking objects across blind regions of multiple cameras
with non-overlapping FOVs. The main contribution of this paper is to
estimate transition times between various entry and exit zones, and to
graphically represent the camera topology as an undirected weighted
graph using the transition probabilities.
Abstract: Wireless sensor networks (WSNs) consist of number
of tiny, low cost and low power sensor nodes to monitor some physical phenomenon. The major limitation in these networks is the use of non-rechargeable battery having limited power supply. The
main cause of energy consumption in such networks is
communication subsystem. This paper presents an energy efficient
Cluster Cooperative Caching at Sensor (C3S) based upon grid type clustering. Sensor nodes belonging to the same cluster/grid form a
cooperative cache system for the node since the cost for
communication with them is low both in terms of energy
consumption and message exchanges. The proposed scheme uses
cache admission control and utility based data replacement policy to
ensure that more useful data is retained in the local cache of a node.
Simulation results demonstrate that C3S scheme performs better in
various performance metrics than NICoCa which is existing
cooperative caching protocol for WSNs.
Abstract: The general idea behind the filter is to average a pixel
using other pixel values from its neighborhood, but simultaneously to
take care of important image structures such as edges. The main
concern of the proposed filter is to distinguish between any variations
of the captured digital image due to noise and due to image structure.
The edges give the image the appearance depth and sharpness. A
loss of edges makes the image appear blurred or unfocused.
However, noise smoothing and edge enhancement are traditionally
conflicting tasks. Since most noise filtering behaves like a low pass
filter, the blurring of edges and loss of detail seems a natural
consequence. Techniques to remedy this inherent conflict often
encompass generation of new noise due to enhancement.
In this work a new fuzzy filter is presented for the noise reduction
of images corrupted with additive noise. The filter consists of three
stages. (1) Define fuzzy sets in the input space to computes a fuzzy
derivative for eight different directions (2) construct a set of IFTHEN
rules by to perform fuzzy smoothing according to
contributions of neighboring pixel values and (3) define fuzzy sets in
the output space to get the filtered and edged image.
Experimental results are obtained to show the feasibility of the
proposed approach with two dimensional objects.
Abstract: Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.
Abstract: Saddlepoint approximations is one of the tools to obtain
an expressions for densities and distribution functions. We approximate
the densities of the observed gaps between the hypopnea events
using the Huzurbazar saddlepoint approximation. We demonstrate the
density of a maximum likelihood estimator in exponential families.
Abstract: The purpose of this study was to investigate the relationship between hope and resilience with work engagement. A total of 422 staff nurses working in three public hospitals in Peninsular Malaysia participated in this study. Statistical results using regression analysis revealed that hope and resilience were positively related to work engagement. Possible reasons for these findings, as well as their implications and future research directions are discussed.
Abstract: In text categorization problem the most used method
for documents representation is based on words frequency vectors
called VSM (Vector Space Model). This representation is based only
on words from documents and in this case loses any “word context"
information found in the document. In this article we make a
comparison between the classical method of document representation
and a method called Suffix Tree Document Model (STDM) that is
based on representing documents in the Suffix Tree format. For the
STDM model we proposed a new approach for documents
representation and a new formula for computing the similarity
between two documents. Thus we propose to build the suffix tree
only for any two documents at a time. This approach is faster, it has
lower memory consumption and use entire document representation
without using methods for disposing nodes. Also for this method is
proposed a formula for computing the similarity between documents,
which improves substantially the clustering quality. This
representation method was validated using HAC - Hierarchical
Agglomerative Clustering. In this context we experiment also the
stemming influence in the document preprocessing step and highlight
the difference between similarity or dissimilarity measures to find
“closer" documents.
Abstract: This paper presents the application of a signal
intensity independent registration criterion for 2D rigid body
registration of medical images using 1D binary projections. The
criterion is defined as the weighted ratio of two projections. The ratio
is computed on a pixel per pixel basis and weighting is performed by
setting the ratios between one and zero pixels to a standard high
value. The mean squared value of the weighted ratio is computed
over the union of the one areas of the two projections and it is
minimized using the Chebyshev polynomial approximation using
n=5 points. The sum of x and y projections is used for translational
adjustment and a 45deg projection for rotational adjustment. 20 T1-
T2 registration experiments were performed and gave mean errors
1.19deg and 1.78 pixels. The method is suitable for contour/surface
matching. Further research is necessary to determine the robustness
of the method with regards to threshold, shape and missing data.
Abstract: In many cases, there are some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrate models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long term research project is given to compare the suggested model with the MpO model.
Abstract: The fast growing accessibility and capability of emerging technologies have fashioned enormous possibilities of designing, developing and implementing innovative teaching methods in the classroom. The global technological scenario has paved the way to new pedagogies in teaching-learning process focusing on technology based learning environment and its impact on student achievement. The present experimental study was conducted to determine the effectiveness of technology based learning environment on student achievement in English as a foreign language. The sample of the study was 90 students of 10th grade of a public school located in Islamabad. A pretest- posttest equivalent group design was used to compare the achievement of the two groups. A Pretest and A posttest containing 50 items each from English textbook were developed and administered. The collected data were statistically analyzed. The results showed that there was a significant difference between the mean scores of Experimental group and the Control group. The performance of Experimental group was better on posttest scores that indicted that teaching through technology based learning environment enhanced the achievement level of the students. On the basis of the results, it was recommended that teaching and learning through information and communication technologies may be adopted to enhance the language learning capability of the students.
Abstract: This study proposes a multi-response surface
optimization problem (MRSOP) for determining the proper choices
of a process parameter design (PPD) decision problem in a noisy
environment of a grease position process in an electronic industry.
The proposed models attempts to maximize dual process responses
on the mean of parts between failure on left and right processes. The
conventional modified simplex method and its hybridization of the
stochastic operator from the hunting search algorithm are applied to
determine the proper levels of controllable design parameters
affecting the quality performances. A numerical example
demonstrates the feasibility of applying the proposed model to the
PPD problem via two iterative methods. Its advantages are also
discussed. Numerical results demonstrate that the hybridization is
superior to the use of the conventional method. In this study, the
mean of parts between failure on left and right lines improve by
39.51%, approximately. All experimental data presented in this
research have been normalized to disguise actual performance
measures as raw data are considered to be confidential.
Abstract: Study was conducted to determine the concentration of
copper, cadmium, lead and zinc in Cabomba furcata that found
abundance in Lake Chini. This aquatic plant was collected randomly
within the lake for heavy metal determination. Water quality
measurement was undertaken in situ for temperature, pH,
conductivity and dissolved oksigen using portable multi sensor probe
YSI model 556. The C. furcata was digested using wet digestion
method and heavy metal concentrations were analysed using Atomic
Absorption Spectrometer (AAS) Perkin Elmer 4100B (flame
method). Result of water quality classify Lake Chini between class II
to class III using Malaysian Water Quality Standard. According to
this standard, Lake Chini has moderate quality, which normal for
natural lake. Heavy metal concentrations in C.furcata were low and
found to be lower than the critical toxic value in aquatic plants. Oneway
ANOVA test indicated the heavy metal concentrations in
C.furcata were significantly differ between sampling location. Water
quality and heavy metal concentrations indicates that Lake Chini was
not receives anthropogenic load from nearby activities.
Abstract: The purpose of this study is to introduce a new
interface program to calculate a dose distribution with Monte Carlo method in complex heterogeneous systems such as organs or tissues
in proton therapy. This interface program was developed under
MATLAB software and includes a friendly graphical user interface
with several tools such as image properties adjustment or results display. Quadtree decomposition technique was used as an image
segmentation algorithm to create optimum geometries from Computed Tomography (CT) images for dose calculations of proton
beam. The result of the mentioned technique is a number of nonoverlapped
squares with different sizes in every image. By this way
the resolution of image segmentation is high enough in and near
heterogeneous areas to preserve the precision of dose calculations
and is low enough in homogeneous areas to reduce the number of
cells directly. Furthermore a cell reduction algorithm can be used to combine neighboring cells with the same material. The validation of this method has been done in two ways; first, in comparison with experimental data obtained with 80 MeV proton beam in Cyclotron
and Radioisotope Center (CYRIC) in Tohoku University and second, in comparison with data based on polybinary tissue calibration method, performed in CYRIC. These results are presented in this paper. This program can read the output file of Monte Carlo code while region of interest is selected manually, and give a plot of dose distribution of proton beam superimposed onto the CT images.
Abstract: In this paper a new method is suggested for
distributed data-mining by the probability patterns. These patterns
use decision trees and decision graphs. The patterns are cared to be
valid, novel, useful, and understandable. Considering a set of
functions, the system reaches to a good pattern or better objectives.
By using the suggested method we will be able to extract the useful
information from massive and multi-relational data bases.
Abstract: Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification
Abstract: The normalized difference vegetation index (NDVI)
and normalized difference moisture index (NDMI) derived from the
moderate resolution imaging spectroradiometer (MODIS) have been
widely used to identify spatial information of drought condition. The
relationship between NDVI and NDMI has been analyzed using
Pearson correlation analysis and showed strong positive relationship.
The drought indices have detected drought conditions and identified
spatial extents of drought. A comparison between normal year and
drought year demonstrates that the amplitude analysis considered both
vegetation and moisture condition is an effective method to identify
drought condition. We proposed the amplitude analysis is useful for
quick spatial assessment of drought information at a regional scale.
Abstract: Aurein 1.2 is a 13-residue amphipathic peptide with antibacterial and anticancer activity. Aurein1.2 and its retro analog were synthesized to study the activity of the peptides in relation to their structure. The antibacterial test result showed the retro-analog is inactive. The secondary structural analysis by CD spectra indicated that both of the peptides at TFE/Water adopt alpha-helical conformation. MD simulation was performed on aurein 1.2 and retro-analog in water and TFE in order to analyse the factors that are involved in the activity difference between retro and the native peptide. The simulation results are discussed and validated in the light of experimental data from the CD experiment. Both of the peptides showed a relatively similar pattern for their hydrophobicity, hydrophilicity, solvent accessible surfaces, and solvent accessible hydrophobic surfaces. However, they showed different in directions of dipole moment of peptides. Also, Our results further indicate that the reversion of the amino acid sequence affects flexibility .The data also showed that factors causing structural rigidity may decrease the activity. Consequently, our finding suggests that in the case of sequence-reversed peptide strategy, one has to pay attention to the role of amino acid sequence order in making flexibility and role of dipole moment direction in peptide activity. KeywordsAntimicrobial peptides, retro, molecular dynamic, circular dichroism.
Abstract: In this paper, at first we explain about negative
hypergeometric distribution and its properties. Then we use the w-function
and the Stein identity to give a result on the poisson
approximation to the negative hypergeometric distribution in terms of the total variation distance between the negative hypergeometric and
poisson distributions and its upper bound.
Abstract: Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.