Abstract: COPD is characterized by loss of elastic fibers from
small airways and alveolar walls, with the decrease in elastin
increasing with disease severity. It is unclear why there is a lack of
repair of elastic fibers. We have examined fibroblasts cultured from
lung tissue from normal and COPD subjects to determine if the
secretory profile explains lack of tissue repair. In this study,
fibroblasts were cultured from lung parenchyma of bronchial
carcinoma patients with varying degrees of COPD; controls
(non-COPD, n=5), mild COPD (GOLD 1, n=5) and moderate-severe
COPD (GOLD 2-3, n=12). Measurements were made of proliferation,
senescence-associated beta-galactosidase-1, mRNA expression of
IL-6, IL-8, MMP-1, tropoelastin and versican, and protein levels for
IL-6, IL-8, PGE2, tropoelastin, insoluble elastin, and versican. It was
found that GOLD 2-3 fibroblasts proliferated more slowly (p
Abstract: In this article we explore how computer assisted exercises may allow for bridging the traditional gap between theory and practice in professional education. To educate officers able to master the complexity of the battlefield the Norwegian Military Academy needs to develop a learning environment that allows for creating viable connections between the educational environment and the field of practice. In response to this challenge we explore the conditions necessary to make computer assisted training systems (CATS) a useful tool to create structural similarities between an educational context and the field of military practice. Although, CATS may facilitate work procedures close to real life situations, this case do demonstrate how professional competence also must build on viable learning theories and environments. This paper explores the conditions that allow for using simulators to facilitate professional competence from within an educational setting. We develop a generic didactic model that ascribes learning to participation in iterative cycles of action and reflection. The development of this model is motivated by the need to develop an interdisciplinary professional education rooted in the pattern of military practice.
Abstract: The risk sphere in business is fast changing and expanding. Almost anything has become a risk factor that will have potent, direct, and far reaching impacts on business. This paper examines the intensity of enterprise risk management (ERM) practices among the Malaysian public listed companies. The paper espouses a ERM framework comprising fourteen important implementation elements and processes. Results of the analysis indicate that the intensity of ERM implementation among the respondents is in the ‘good’ category of the semantic scale, which is deemed encouraging vis-à-vis the country’s regulatory regime.
Abstract: In this paper is described a new conception of the
Cartesian robot for automated assembly and also disassembly
process. The advantage of this conception is the utilization the
Cartesian assembly robot with its all peripheral automated devices for
assembly of the assembled product. The assembly product in the end
of the lifecycle can be disassembled with the same Cartesian
disassembly robot with the use of the same peripheral automated
devices and equipment. It is a new approach to problematic solving
and development of the automated assembly systems with respect to
lifecycle management of the assembly product and also assembly
system with Cartesian robot. It is also important to develop the
methodical process for design of automated assembly and
disassembly system with Cartesian robot. Assembly and disassembly
system use the same Cartesian robot input and output devices,
assembly and disassembly units in one workplace with different
application. Result of design methodology is the verification and
proposition of real automated assembly and disassembly workplace
with Cartesian robot for known verified model of assembled actuator.
Abstract: In this paper, image compression using hybrid vector
quantization scheme such as Multistage Vector Quantization
(MSVQ) and Pyramid Vector Quantization (PVQ) are introduced. A
combined MSVQ and PVQ are utilized to take advantages provided
by both of them. In the wavelet decomposition of the image, most of
the information often resides in the lowest frequency subband.
MSVQ is applied to significant low frequency coefficients. PVQ is
utilized to quantize the coefficients of other high frequency
subbands. The wavelet coefficients are derived using lifting scheme.
The main aim of the proposed scheme is to achieve high compression
ratio without much compromise in the image quality. The results are
compared with the existing image compression scheme using MSVQ.
Abstract: The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
Abstract: The 2008 Candlelight Protests of Korea was very
significant to portray the political environment among the South
Korean youth. Many challenges and new advanced technologies have
driven the youth community to be engaged in the political arena that
has shifted them from traditional Korean youth to a very greater
community. Due to historical perspective with the people of North
Korea, the young generation has embraced different view of ethnic
nationalism. This study examines the youth involvement in politics in
line with their level of acceptance the practice of democracy. The
increase usage of new media has shown great results in the survey
results whereby the youth used as a platform to gain political
information and brought higher degree of their sociopolitical interests
among them. Furthermore, the rise of nationalism and patriotism will
be discussed in this paper to the dynamism of the political approaches
used by the Korea government
Abstract: Quantitative trait loci (QTL) experiments have yielded
important biological and biochemical information necessary for
understanding the relationship between genetic markers and
quantitative traits. For many years, most QTL algorithms only
allowed one observation per genotype. Recently, there has been an
increasing demand for QTL algorithms that can accommodate more
than one observation per genotypic distribution. The Bayesian
hierarchical model is very flexible and can easily incorporate this
information into the model. Herein a methodology is presented that
uses a Bayesian hierarchical model to capture the complexity of the
data. Furthermore, the Markov chain Monte Carlo model composition
(MC3) algorithm is used to search and identify important markers. An
extensive simulation study illustrates that the method captures the
true QTL, even under nonnormal noise and up to 6 QTL.
Abstract: Natural organic matter (NOM) is heterogeneous
mixture of organic compounds that enter the water media from
animal and plant remains, domestic and industrial wastes.
Researches showed that NOM is likely precursor material for
disinfection by products (DBPs). Chlorine very commenly used for
disinfection purposes and NOM and chlorine reacts then
Trihalomethane (THM) and Haloacetic acids (HAAs) which are
cancerogenics for human health are produced. The aim of the study is
to search NOM removal by enhanced coagulation from drinking
water source of Eskisehir which is supplied from Porsuk Dam.
Recently, Porsuk dam water is getting highly polluted and therefore
NOM concentration is increasing. Enhanced coagulation studies were
evaluated by measurement of Dissolved Organic Carbon (DOC), UV
absorbance at 254 nm (UV254), and different trihalomethane
formation potential (THMFP) tests. Results of jar test experiments
showed that NOM can be removed from water about 40-50 % of
efficiency by enhanced coagulation. Optimum coagulant type and
coagulant dosages were determined using FeCl3 and Alum.
Abstract: A camera in the building site is exposed to different
weather conditions. Differences between images of the same scene
captured with the same camera arise also due to temperature variations.
The influence of temperature changes on camera parameters
were modelled and integrated into existing analytical camera model.
Modified camera model enables quantitatively assessing the influence
of temperature variations.
Abstract: In-place sorting algorithms play an important role in many fields such as very large database systems, data warehouses, data mining, etc. Such algorithms maximize the size of data that can be processed in main memory without input/output operations. In this paper, a novel in-place sorting algorithm is presented. The algorithm comprises two phases; rearranging the input unsorted array in place, resulting segments that are ordered relative to each other but whose elements are yet to be sorted. The first phase requires linear time, while, in the second phase, elements of each segment are sorted inplace in the order of z log (z), where z is the size of the segment, and O(1) auxiliary storage. The algorithm performs, in the worst case, for an array of size n, an O(n log z) element comparisons and O(n log z) element moves. Further, no auxiliary arithmetic operations with indices are required. Besides these theoretical achievements of this algorithm, it is of practical interest, because of its simplicity. Experimental results also show that it outperforms other in-place sorting algorithms. Finally, the analysis of time and space complexity, and required number of moves are presented, along with the auxiliary storage requirements of the proposed algorithm.
Abstract: The purpose of this study is to investigate the effects
of modality principles in instructional software among first grade
pupils- achievements in the learning of Arabic Language. Two modes
of instructional software were systematically designed and
developed, audio with images (AI), and text with images (TI). The
quasi-experimental design was used in the study. The sample
consisted of 123 male and female pupils from IRBED Education
Directorate, Jordan. The pupils were randomly assigned to any one of
the two modes. The independent variable comprised the two modes
of the instructional software, the students- achievement levels in the
Arabic Language class and gender. The dependent variable was the
achievements of the pupils in the Arabic Language test. The
theoretical framework of this study was based on Mayer-s Cognitive
Theory of Multimedia Learning. Four hypotheses were postulated
and tested. Analyses of Variance (ANOVA) showed that pupils using
the (AI) mode performed significantly better than those using (TI)
mode. This study concluded that the audio with images mode was an
important aid to learning as compared to text with images mode.
Abstract: In this paper, we present the information life cycle, and analyze the importance of managing the corporate application portfolio across this life cycle. The approach presented here does not correspond just to the extension of the traditional information system development life cycle. This approach is based in the generic life cycle employed in other contexts like manufacturing or marketing. In this paper it is proposed a model of an information system life cycle, supported in the assumption that a system has a limited life. But, this limited life may be extended. This model is also applied in several cases; being reported here two examples of the framework application in a construction enterprise, and in a manufacturing enterprise.
Abstract: The purpose of present paper was to investigate
perceptions of Korean secondary school students about social issues
related to biological sciences. Twenty issues were selected based on
topics of articles in the newspaper from 2005 to 2010. The issues were
categorized into biotechnology, health-disease and environment
domains. Subjects were 541 high school students (male 253 and
female 288). On the survey, students were asked to answer on 5-point
Lickert scales how they thought of the effect of biological phenomena
or events related to biological issues on the individual life and the
society. They perceived that the biological issues would be more
effectible on the society than on the individual life. Female students
had a little more perceptions than males.
Abstract: Case based reasoning (CBR) methodology presents a foundation for a new technology of building intelligent computeraided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. This paper discusses the CBR methodology, the research issues and technical aspects of implementing intelligent medical diagnoses systems. Successful applications in cancer and heart diseases developed by Medical Informatics Research Group at Ain Shams University are also discussed.
Abstract: We investigate efficient spreading codes for transmitter based techniques of code division multiple access (CDMA) systems. The channel is considered to be known at the transmitter which is usual in a time division duplex (TDD) system where the channel is assumed to be the same on uplink and downlink. For such a TDD/CDMA system, both bitwise and blockwise multiuser transmission schemes are taken up where complexity is transferred to the transmitter side so that the receiver has minimum complexity. Different spreading codes are considered at the transmitter to spread the signal efficiently over the entire spectrum. The bit error rate (BER) curves portray the efficiency of the codes in presence of multiple access interference (MAI) as well as inter symbol interference (ISI).
Abstract: As the web continues to grow exponentially, the idea
of crawling the entire web on a regular basis becomes less and less
feasible, so the need to include information on specific domain,
domain-specific search engines was proposed. As more information
becomes available on the World Wide Web, it becomes more difficult
to provide effective search tools for information access. Today,
people access web information through two main kinds of search
interfaces: Browsers (clicking and following hyperlinks) and Query
Engines (queries in the form of a set of keywords showing the topic
of interest) [2]. Better support is needed for expressing one's
information need and returning high quality search results by web
search tools. There appears to be a need for systems that do reasoning
under uncertainty and are flexible enough to recover from the
contradictions, inconsistencies, and irregularities that such reasoning
involves. In a multi-view problem, the features of the domain can be
partitioned into disjoint subsets (views) that are sufficient to learn the
target concept. Semi-supervised, multi-view algorithms, which
reduce the amount of labeled data required for learning, rely on the
assumptions that the views are compatible and uncorrelated. This
paper describes the use of semi-structured machine learning approach
with Active learning for the “Domain Specific Search Engines". A
domain-specific search engine is “An information access system that
allows access to all the information on the web that is relevant to a
particular domain. The proposed work shows that with the help of
this approach relevant data can be extracted with the minimum
queries fired by the user. It requires small number of labeled data and
pool of unlabelled data on which the learning algorithm is applied to
extract the required data.
Abstract: Data clustering is an important data exploration technique
with many applications in data mining. We present an enhanced
version of the well known single link clustering algorithm. We will
refer to this algorithm as DCBOR. The proposed algorithm alleviates
the chain effect by removing the outliers from the given dataset.
So this algorithm provides outlier detection and data clustering
simultaneously. This algorithm does not need to update the distance
matrix, since the algorithm depends on merging the most k-nearest
objects in one step and the cluster continues grow as long as possible
under specified condition. So the algorithm consists of two phases;
at the first phase, it removes the outliers from the input dataset. At
the second phase, it performs the clustering process. This algorithm
discovers clusters of different shapes, sizes, densities and requires
only one input parameter; this parameter represents a threshold for
outlier points. The value of the input parameter is ranging from 0 to
1. The algorithm supports the user in determining an appropriate
value for it. We have tested this algorithm on different datasets
contain outlier and connecting clusters by chain of density points,
and the algorithm discovers the correct clusters. The results of
our experiments demonstrate the effectiveness and the efficiency of
DCBOR.
Abstract: In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.
Abstract: This paper presents a study of the Taguchi design
application to optimize surface quality in damper inserted end milling
operation. Maintaining good surface quality usually involves
additional manufacturing cost or loss of productivity. The Taguchi
design is an efficient and effective experimental method in which a
response variable can be optimized, given various factors, using
fewer resources than a factorial design. This Study included spindle
speed, feed rate, and depth of cut as control factors, usage of different
tools in the same specification, which introduced tool condition and
dimensional variability. An orthogonal array of L9(3^4)was used;
ANOVA analyses were carried out to identify the significant factors
affecting surface roughness, and the optimal cutting combination was
determined by seeking the best surface roughness (response) and
signal-to-noise ratio. Finally, confirmation tests verified that the
Taguchi design was successful in optimizing milling parameters for
surface roughness.