Abstract: Free and open source software is gaining popularity at
an unprecedented rate of growth. Organizations despite some
concerns about the quality have been using them for various
purposes. One of the biggest concerns about free and open source
software is post release software defects and their fixing. Many
believe that there is no appropriate support available to fix the bugs.
On the contrary some believe that due to the active involvement of
internet user in online forums, they become a major source of
communicating the identification and fixing of defects in open source
software. The research model of this empirical investigation
establishes and studies the relationship between open source software
defects and online public forums. The results of this empirical study
provide evidence about the realities of software defects myths of
open source software. We used a dataset consist of 616 open source
software projects covering a broad range of categories to study the
research model of this investigation. The results of this investigation
show that online forums play a significant role identifying and fixing
the defects in open source software.
Abstract: Wrist pulse analysis for identification of health status
is found in Ancient Indian as well as Chinese literature. The preprocessing
of wrist pulse is necessary to remove outlier pulses and
fluctuations prior to the analysis of pulse pressure signal. This paper
discusses the identification of irregular pulses present in the pulse
series and intricacies associated with the extraction of time domain
pulse features. An approach of Dynamic Time Warping (DTW) has
been utilized for the identification of outlier pulses in the wrist pulse
series. The ambiguity present in the identification of pulse features is
resolved with the help of first derivative of Ensemble Average of
wrist pulse series. An algorithm for detecting tidal and dicrotic notch
in individual wrist pulse segment is proposed.
Abstract: In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.
Abstract: In this paper, a neural network technique is applied to
real-time classifying media while a projectile is penetrating through
them. A laboratory-scaled penetrating setup was built for the
experiment. Features used as the network inputs were extracted from
the acceleration of penetrator. 6000 set of features from a single
penetration with known media and status were used to train the neural
network. The trained system was tested on 30 different penetration
experiments. The system produced an accuracy of 100% on the
training data set. And, their precision could be 99% for the test data
from 30 tests.
Abstract: With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.
Abstract: The security of power systems against malicious cyberphysical
data attacks becomes an important issue. The adversary
always attempts to manipulate the information structure of the power
system and inject malicious data to deviate state variables while
evading the existing detection techniques based on residual test. The
solutions proposed in the literature are capable of immunizing the
power system against false data injection but they might be too costly
and physically not practical in the expansive distribution network.
To this end, we define an algebraic condition for trustworthy power
system to evade malicious data injection. The proposed protection
scheme secures the power system by deterministically reconfiguring
the information structure and corresponding residual test. More
importantly, it does not require any physical effort in either microgrid
or network level. The identification scheme of finding meters being
attacked is proposed as well. Eventually, a well-known IEEE 30-bus
system is adopted to demonstrate the effectiveness of the proposed
schemes.
Abstract: The Long-range Energy and Alternatives Planning (LEAP) energy planning system has been developed for South Africa, for the 2005 base year and a limited number of plausible future scenarios that may have significant implications (negative or positive) in terms of environmental impacts. The system quantifies the national energy demand for the domestic, commercial, transport, industry and agriculture sectors, the supply of electricity and liquid fuels, and the resulting emissions. The South African National Energy Research Institute (SANERI) identified the need to develop an environmental assessment tool, based on the LEAP energy planning system, to provide decision-makers and stakeholders with the necessary understanding of the environmental impacts associated with different energy scenarios. A comprehensive analysis of indicators that are used internationally and in South Africa was done and the available data was accessed to select a reasonable number of indicators that could be utilized in energy planning. A consultative process was followed to determine the needs of different stakeholders on the required indicators and also the most suitable form of reporting. This paper demonstrates the application of Energy Environmental Sustainability Indicators (EESIs) as part of the developed tool, which assists with the identification of the environmental consequences of energy generation and use scenarios and thereby promotes sustainability, since environmental considerations can then be integrated into the preparation and adoption of policies, plans, programs and projects. Recommendations are made to refine the tool further for South Africa.
Abstract: This paper provides an introduction into the evolution
of information and communication technology and illustrates its
usage in the work domain. The paper is sub-divided into two parts.
The first part gives an overview over the different phases of
information processing in the work domain. It starts by charting the
past and present usage of computers in work environments and shows
current technological trends, which are likely to influence future
business applications. The second part starts by briefly describing,
how the usage of computers changed business processes in the past,
and presents first Ambient Intelligence applications based on
identification and localization information, which are already used in
the production and retail sector. Based on current systems and
prototype applications, the paper gives an outlook of how Ambient
Intelligence technologies could change business processes in the
future.
Abstract: The identification and elimination of bad
measurements is one of the basic functions of a robust state estimator
as bad data have the effect of corrupting the results of state
estimation according to the popular weighted least squares method.
However this is a difficult problem to handle especially when dealing
with multiple errors from the interactive conforming type. In this
paper, a self adaptive genetic based algorithm is proposed. The
algorithm utilizes the results of the classical linearized normal
residuals approach to tune the genetic operators thus instead of
making a randomized search throughout the whole search space it is
more likely to be a directed search thus the optimum solution is
obtained at very early stages(maximum of 5 generations). The
algorithm utilizes the accumulating databases of already computed
cases to reduce the computational burden to minimum. Tests are
conducted with reference to the standard IEEE test systems. Test
results are very promising.
Abstract: The pipe inspection operation is the difficult detective
performance. Almost applications are mainly relies on a manual
recognition of defective areas that have carried out detection by an
engineer. Therefore, an automation process task becomes a necessary
in order to avoid the cost incurred in such a manual process. An
automated monitoring method to obtain a complete picture of the
sewer condition is proposed in this work. The focus of the research is
the automated identification and classification of discontinuities in
the internal surface of the pipe. The methodology consists of several
processing stages including image segmentation into the potential
defect regions and geometrical characteristic features. Automatic
recognition and classification of pipe defects are carried out by means
of using an artificial neural network technique (ANN) based on
Radial Basic Function (RBF). Experiments in a realistic environment
have been conducted and results are presented.
Abstract: In this paper the problem of estimating the time delay
between two spatially separated noisy sinusoidal signals by system
identification modeling is addressed. The system is assumed to be
perturbed by both input and output additive white Gaussian noise. The
presence of input noise introduces bias in the time delay estimates.
Normally the solution requires a priori knowledge of the input-output
noise variance ratio. We utilize the cascade of a self-tuned filter with
the time delay estimator, thus making the delay estimates robust to
input noise. Simulation results are presented to confirm the superiority
of the proposed approach at low input signal-to-noise ratios.
Abstract: This paper makes an attempt to solve the problem of
searching and retrieving of similar MRI photos via Internet services
using morphological features which are sourced via the original
image. This study is aiming to be considered as an additional tool of
searching and retrieve methods. Until now the main way of the
searching mechanism is based on the syntactic way using keywords.
The technique it proposes aims to serve the new requirements of
libraries. One of these is the development of computational tools for
the control and preservation of the intellectual property of digital
objects, and especially of digital images. For this purpose, this paper
proposes the use of a serial number extracted by using a previously
tested semantic properties method. This method, with its center being
the multi-layers of a set of arithmetic points, assures the following
two properties: the uniqueness of the final extracted number and the
semantic dependence of this number on the image used as the
method-s input. The major advantage of this method is that it can
control the authentication of a published image or its partial
modification to a reliable degree. Also, it acquires the better of the
known Hash functions that the digital signature schemes use and
produces alphanumeric strings for cases of authentication checking,
and the degree of similarity between an unknown image and an
original image.
Abstract: New nondestructive technique, namely an inverse technique based on vibration tests, to characterize nonlinear mechanical properties of adhesive layers in sandwich composites is developed. An adhesive layer is described as a viscoelastic isotropic material with storage and loss moduli which are both frequency dependent values in wide frequency range. An optimization based on the planning of experiments and response surface technique to minimize the error functional is applied to decrease considerably the computational expenses. The developed identification technique has been tested on aluminum panels and successfully applied to characterize viscoelastic material properties of 3M damping polymer ISD-112 used as a core material in sandwich panels.
Abstract: Our Medicine-oriented research is based on a medical
data set of real patients. It is a security problem to share
patient private data with peoples other than clinician or hospital
staff. We have to remove person identification information
from medical data. The medical data without private data
are available after a de-identification process for any research
purposes. In this paper, we introduce an universal automatic
rule-based de-identification application to do all this stuff on an
heterogeneous medical data. A patient private identification is
replaced by an unique identification number, even in burnedin
annotation in pixel data. The identical identification is used
for all patient medical data, so it keeps relationships in a data.
Hospital can take an advantage of a research feedback based
on results.
Abstract: Fast development of technologies, economic globalization and many other external circumstances stimulate company’s competitiveness. One of the major trends in today’s business is the shift to the exploitation of the Internet and electronic environment for entrepreneurial needs. Latest researches confirm that e-environment provides a range of possibilities and opportunities for companies, especially for micro-, small- and medium-sized companies, which have limited resources. The usage of e-tools raises the effectiveness and the profitability of an organization, as well as its competitiveness.
In the electronic market, as in the classic one, there are factors, such as globalization, development of new technology, price sensitive consumers, Internet, new distribution and communication channels that influence entrepreneurship. As a result of eenvironment development, e-commerce and e-marketing grow as well.
Objective of the paper: To describe and identify factors influencing company’s competitiveness in e-environment.
Research methodology: The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistics method, factor analysis in SPSS 20 environment, etc. The theoretical and methodological background of the research is formed by using scientific researches and publications, such as that from mass media and professional literature; statistical information from legal institutions as well as information collected by the authors during the surveying process.
Research result: The authors detected and classified factors influencing competitiveness in e-environment.
In this paper, the authors presented their findings based on theoretical, scientific, and field research. Authors have conducted a research on e-environment utilization among Latvian enterprises.
Abstract: The paper presents the case study of hazard
identification and sensitivity of potential resource of emergency
water supply as part of the application of methodology classifying
the resources of drinking water for emergency supply of population.
The case study has been carried out on a selected resource of
emergency water supply in one region of the Czech Republic. The
hazard identification and sensitivity of potential resource of
emergency water supply is based on a unique procedure and
developed general registers of selected types of hazards and
sensitivities. The registers have been developed with the help of the
“Fault Tree Analysis” method in combination with the “What if
method”. The identified hazards for the assessed resource include
hailstorms and torrential rains, drought, soil erosion, accidents of
farm machinery, and agricultural production. The developed registers
of hazards and vulnerabilities and a semi-quantitative assessment of
hazards for individual parts of hydrological structure and
technological elements of presented drilled wells are the basis for a
semi-quantitative risk assessment of potential resource of emergency
supply of population and the subsequent classification of such
resource within the system of crisis planning.
Abstract: One of the most important parts of a cement factory is
the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral
movement of air and materials, together with chemical reactions take
place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only
in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was
presented instead. This issue caused many problems for designing a
cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using
nonlinear identification technique on the Locally Linear Neuro-
Fuzzy (LLNF) model. For the first time, a simulator model as well as
a predictor one with a precise fifteen minute prediction horizon for a
cement rotary kiln is presented. These models are trained by
LOLIMOT algorithm which is an incremental tree-structure
algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these
models. The data collected from White Saveh Cement Company is used for modeling.
Abstract: In this paper, a TSK-type Neuro-fuzzy Inference
System that combines the features of fuzzy sets and neural networks
has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled
Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate
the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on
Particle Swarm Optimization algorithm (PSO) and Genetic
Algorithm (GA).
Abstract: Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.
Abstract: In this paper, some problem formulations of dynamic object parameters recovery described by non-autonomous system of ordinary differential equations with multipoint unshared edge conditions are investigated. Depending on the number of additional conditions the problem is reduced to an algebraic equations system or to a problem of quadratic programming. With this purpose the paper offers a new scheme of the edge conditions transfer method called by conditions shift. The method permits to get rid from differential links and multipoint unshared initially-edge conditions. The advantage of the proposed approach is concluded by capabilities of reduction of a parametric identification problem to essential simple problems of the solution of an algebraic system or quadratic programming.