Abstract: I/O workload is a critical and important factor to
analyze I/O pattern and to maximize file system performance.
However to measure I/O workload on running distributed parallel file
system is non-trivial due to collection overhead and large volume of
data. In this paper, we measured and analyzed file system activities on
two large-scale cluster systems which had TFlops level high
performance computation resources. By comparing file system
activities of 2009 with those of 2006, we analyzed the change of I/O
workloads by the development of system performance and high-speed
network technology.
Abstract: Spatial and mobile computing evolves. This paper
describes a smart modeling platform called “GeoSEMA". This
approach tends to model multidimensional GeoSpatial Evolutionary
and Mobile Agents. Instead of 3D and location-based issues, there
are some other dimensions that may characterize spatial agents, e.g.
discrete-continuous time, agent behaviors. GeoSEMA is seen as a
devoted design pattern motivating temporal geographic-based
applications; it is a firm foundation for multipurpose and
multidimensional special-based applications. It deals with
multipurpose smart objects (buildings, shapes, missiles, etc.) by
stimulating geospatial agents.
Formally, GeoSEMA refers to geospatial, spatio-evolutive and
mobile space constituents where a conceptual geospatial space model
is given in this paper. In addition to modeling and categorizing
geospatial agents, the model incorporates the concept of inter-agents
event-based protocols. Finally, a rapid software-architecture
prototyping GeoSEMA platform is also given. It will be
implemented/ validated in the next phase of our work.
Abstract: In a competitive production environment, critical
decision making are based on data resulted by random sampling of
product units. Efficiency of these decisions depends on data quality
and also their reliability scale. This point leads to the necessity of a
reliable measurement system. Therefore, the conjecture process and
analysing the errors contributes to a measurement system known as
Measurement System Analysis (MSA). The aim of this research is on
determining the necessity and assurance of extensive development in
analysing measurement systems, particularly with the use of
Repeatability and Reproducibility Gages (GR&R) to improve
physical measurements. Nowadays in productive industries,
repeatability and reproducibility gages released so well but they are
not applicable as well as other measurement system analysis
methods. To get familiar with this method and gain a feedback in
improving measurement systems, this survey would be on
“ANOVA" method as the most widespread way of calculating
Repeatability and Reproducibility (R&R).
Abstract: The problem of frequent pattern discovery is defined
as the process of searching for patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns
has become an important data mining task because it reveals associations, correlations, and many other interesting relationships
hidden in a database. Most of the proposed frequent pattern mining
algorithms have been implemented with imperative programming
languages. Such paradigm is inefficient when set of patterns is large
and the frequent pattern is long. We suggest a high-level declarative
style of programming apply to the problem of frequent pattern
discovery. We consider two languages: Haskell and Prolog. Our
intuitive idea is that the problem of finding frequent patterns should
be efficiently and concisely implemented via a declarative paradigm
since pattern matching is a fundamental feature supported by most
functional languages and Prolog. Our frequent pattern mining
implementation using the Haskell and Prolog languages confirms our
hypothesis about conciseness of the program. The comparative
performance studies on line-of-code, speed and memory usage of
declarative versus imperative programming have been reported in the
paper.
Abstract: Independent spanning trees (ISTs) provide a number of advantages in data broadcasting. One can cite the use in fault tolerance network protocols for distributed computing and bandwidth. However, the problem of constructing multiple ISTs is considered hard for arbitrary graphs. In this paper we present an efficient algorithm to construct ISTs on hypercubes that requires minimum resources to be performed.
Abstract: We present design, fabrication, and characterization of
a small (12 mm × 12 mm × 8 mm) movable railway vehicle for sensor
carrying. The miniature railway vehicle (MRV) was mainly composed
of a vibrational structure and three legs. A railway was designed and
fabricated to power and guide the MRV. It also transmits the sensed
data from the MRV to the signal processing unit. The MRV with legs
on the railway was moving due to its high-frequency vibration. A
model was derived to describe the motion. Besides, FEM simulations
were performed to design the legs. Then, the MRV and the railway
were fabricated by precision machining. Finally, an infrared sensor
was carried and tested. The result shows that the MRV without loading
was moving along the railway and its maximum speed was 12.2 mm/s.
Moreover, the testing signal was sensed by the MRV.
Abstract: The cable tower of Liede Bridge is a double-column curved-lever arched-beam portal framed structure. Being novel and unique in structure, its cable tower differs in complexity from traditional ones. This paper analyzes the ultimate load capacity of cable tower by adopting the finite element calculations and model tests which indicate that constitutive relations applied here give a better simulation of actual failure process of prestressed reinforced concrete. In vertical load, horizontal load and overloading tests, the stepped loading of the tower model is of linear relationship, and the test data has good repeatability. All suggests that the cable tower has good bearing capacity, rational design and high emergency capacity.
Abstract: In this paper is reported an analysis about the outdoor air pollution of the urban centre of the city of Messina. The variations of the most critical pollutants concentrations (PM10, O3, CO, C6H6) and their trends respect of climatic parameters and vehicular traffic have been studied. Linear regressions have been effectuated for representing the relations among the pollutants; the differences between pollutants concentrations on weekend/weekday were also analyzed. In order to evaluate air pollution and its effects on human health, a method for calculating a pollution index was implemented and applied in the urban centre of the city. This index is based on the weighted mean of the most detrimental air pollutants concentrations respect of their limit values for protection of human health. The analyzed data of the polluting substances were collected by the Assessorship of the Environment of the Regional Province of Messina in the year 2004. A statistical analysis of the air quality index trends is also reported.
Abstract: Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).
Abstract: In this paper we describe the design and implementation of a parallel algorithm for data assimilation with ensemble Kalman filter (EnKF) for oil reservoir history matching problem. The use of large number of observations from time-lapse seismic leads to a large turnaround time for the analysis step, in addition to the time consuming simulations of the realizations. For efficient parallelization it is important to consider parallel computation at the analysis step. Our experiments show that parallelization of the analysis step in addition to the forecast step has good scalability, exploiting the same set of resources with some additional efforts.
Abstract: Given a parallel program to be executed on a heterogeneous
computing system, the overall execution time of the program
is determined by a schedule. In this paper, we analyze the worst-case
performance of the list scheduling algorithm for scheduling tasks
of a parallel program in a mixed-machine heterogeneous computing
system such that the total execution time of the program is minimized.
We prove tight lower and upper bounds for the worst-case
performance ratio of the list scheduling algorithm. We also examine
the average-case performance of the list scheduling algorithm. Our
experimental data reveal that the average-case performance of the list
scheduling algorithm is much better than the worst-case performance
and is very close to optimal, except for large systems with large
heterogeneity. Thus, the list scheduling algorithm is very useful in
real applications.
Abstract: Practicum placements are an critical factor for student teachers on Education Programs. How can student teachers become professionals? This study was to investigate problems, weakness and obstacles of practicum placements and develop guidelines for partnership in the practicum placements. In response to this issue, a partnership concept was implemented for developing student teachers into professionals. Data were collected through questionnaires on attitude toward problems, weaknesses, and obstacles of practicum placements of student teachers in Rajabhat universities and included focus group interviews. The research revealed that learning management, classroom management, curriculum, assessment and evaluation, classroom action research, and teacher demeanor are the important factors affecting the professional development of Education Program student teachers. Learning management plan and classroom management concerning instructional design, teaching technique, instructional media, and student behavior management are another important aspects influencing the professional development for student teachers.
Abstract: Medical image modalities such as computed
tomography (CT), magnetic resonance imaging (MRI), ultrasound
(US), X-ray are adapted to diagnose disease. These modalities
provide flexible means of reviewing anatomical cross-sections and
physiological state in different parts of the human body. The raw
medical images have a huge file size and need large storage
requirements. So it should be such a way to reduce the size of those
image files to be valid for telemedicine applications. Thus the image
compression is a key factor to reduce the bit rate for transmission or
storage while maintaining an acceptable reproduction quality, but it is
natural to rise the question of how much an image can be compressed
and still preserve sufficient information for a given clinical
application. Many techniques for achieving data compression have
been introduced. In this study, three different MRI modalities which
are Brain, Spine and Knee have been compressed and reconstructed
using wavelet transform. Subjective and objective evaluation has
been done to investigate the clinical information quality of the
compressed images. For the objective evaluation, the results show
that the PSNR which indicates the quality of the reconstructed image
is ranging from (21.95 dB to 30.80 dB, 27.25 dB to 35.75 dB, and
26.93 dB to 34.93 dB) for Brain, Spine, and Knee respectively. For
the subjective evaluation test, the results show that the compression
ratio of 40:1 was acceptable for brain image, whereas for spine and
knee images 50:1 was acceptable.
Abstract: Cryptography provides the secure manner of
information transmission over the insecure channel. It authenticates
messages based on the key but not on the user. It requires a lengthy
key to encrypt and decrypt the sending and receiving the messages,
respectively. But these keys can be guessed or cracked. Moreover,
Maintaining and sharing lengthy, random keys in enciphering and
deciphering process is the critical problem in the cryptography
system. A new approach is described for generating a crypto key,
which is acquired from a person-s iris pattern. In the biometric field,
template created by the biometric algorithm can only be
authenticated with the same person. Among the biometric templates,
iris features can efficiently be distinguished with individuals and
produces less false positives in the larger population. This type of iris
code distribution provides merely less intra-class variability that aids
the cryptosystem to confidently decrypt messages with an exact
matching of iris pattern. In this proposed approach, the iris features
are extracted using multi resolution wavelets. It produces 135-bit iris
codes from each subject and is used for encrypting/decrypting the
messages. The autocorrelators are used to recall original messages
from the partially corrupted data produced by the decryption process.
It intends to resolve the repudiation and key management problems.
Results were analyzed in both conventional iris cryptography system
(CIC) and non-repudiation iris cryptography system (NRIC). It
shows that this new approach provides considerably high
authentication in enciphering and deciphering processes.
Abstract: This paper presents a threshold voltage model of pocket implanted sub-100 nm n-MOSFETs incorporating the drain and substrate bias effects using two linear pocket profiles. Two linear equations are used to simulate the pocket profiles along the channel at the surface from the source and drain edges towards the center of the n-MOSFET. Then the effective doping concentration is derived and is used in the threshold voltage equation that is obtained by solving the Poisson-s equation in the depletion region at the surface. Simulated threshold voltages for various gate lengths fit well with the experimental data already published in the literature. The simulated result is compared with the two other pocket profiles used to derive the threshold voltage models of n-MOSFETs. The comparison shows that the linear model has a simple compact form that can be utilized to study and characterize the pocket implanted advanced ULSI devices.
Abstract: Rainfall data at fine resolution and knowledge of its
characteristics plays a major role in the efficient design and operation
of agricultural, telecommunication, runoff and erosion control as well
as water quality control systems. The paper is aimed to study the
statistical distribution of hourly rainfall depth for 12 representative
stations spread across Peninsular Malaysia. Hourly rainfall data of 10
to 22 years period were collected and its statistical characteristics
were estimated. Three probability distributions namely, Generalized
Pareto, Exponential and Gamma distributions were proposed to
model the hourly rainfall depth, and three goodness-of-fit tests,
namely, Kolmogorov-Sminov, Anderson-Darling and Chi-Squared
tests were used to evaluate their fitness. Result indicates that the east
cost of the Peninsular receives higher depth of rainfall as compared
to west coast. However, the rainfall frequency is found to be
irregular. Also result from the goodness-of-fit tests show that all the
three models fit the rainfall data at 1% level of significance.
However, Generalized Pareto fits better than Exponential and
Gamma distributions and is therefore recommended as the best fit.
Abstract: The vast amount of information on the World Wide
Web is created and published by many different types of providers.
Unlike books and journals, most of this information is not subject to
editing or peer review by experts. This lack of quality control and the
explosion of web sites make the task of finding quality information
on the web especially critical. Meanwhile new facilities for
producing web pages such as Blogs make this issue more significant
because Blogs have simple content management tools enabling nonexperts
to build easily updatable web diaries or online journals. On
the other hand despite a decade of active research in information
quality (IQ) there is no framework for measuring information quality
on the Blogs yet. This paper presents a novel experimental
framework for ranking quality of information on the Weblog. The
results of data analysis revealed seven IQ dimensions for the Weblog.
For each dimension, variables and related coefficients were
calculated so that presented framework is able to assess IQ of
Weblogs automatically.
Abstract: Tumor classification is a key area of research in the
field of bioinformatics. Microarray technology is commonly used in
the study of disease diagnosis using gene expression levels. The
main drawback of gene expression data is that it contains thousands
of genes and a very few samples. Feature selection methods are used
to select the informative genes from the microarray. These methods
considerably improve the classification accuracy. In the proposed
method, Genetic Algorithm (GA) is used for effective feature
selection. Informative genes are identified based on the T-Statistics,
Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate
solutions of GA are obtained from top-m informative genes. The
classification accuracy of k-Nearest Neighbor (kNN) method is used
as the fitness function for GA. In this work, kNN and Support Vector
Machine (SVM) are used as the classifiers. The experimental results
show that the proposed work is suitable for effective feature
selection. With the help of the selected genes, GA-kNN method
achieves 100% accuracy in 4 datasets and GA-SVM method
achieves in 5 out of 10 datasets. The GA with kNN and SVM
methods are demonstrated to be an accurate method for microarray
based tumor classification.
Abstract: In Both developed and developing countries,
governments play a basic role in making policies, programs and
instruments which support the development of micro, small and
medium enterprises. One of the mechanisms employed to nurture
small firms for more than two decades is business incubation. One of
the mechanisms employed to nurture small firms for more than two
decades is technology business incubation. The main aim of this
research was to establish influencing factors in Technology Business
Incubator's effectiveness and their explanatory model. Therefore,
among 56 Technology Business Incubators in Iran, 32 active
incubators were selected and by stratified random sampling, 528
start-ups were chosen. The validity of research questionnaires
was determines by expert consensus, item analysis and factor
analysis; and their reliability calculated by Cronbach-s alpha.
Data analysis was then made through SPSS and LISREL soft wares.
Both organizational procedures and entrepreneurial behaviors were
the meaningful mediators. Organizational procedures with (P < .01, β
=0.45) was stronger mediator for the improvement of Technology
Business Incubator's effectiveness comparing to entrepreneurial
behavior with (P < .01, β =0.36).
Abstract: COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network.