Abstract: In this paper, we present a model-based regression test
suite reducing approach that uses EFSM model dependence analysis
and probability-driven greedy algorithm to reduce software regression
test suites. The approach automatically identifies the difference
between the original model and the modified model as a set of
elementary model modifications. The EFSM dependence analysis is
performed for each elementary modification to reduce the regression
test suite, and then the probability-driven greedy algorithm is adopted
to select the minimum set of test cases from the reduced regression test
suite that cover all interaction patterns. Our initial experience shows
that the approach may significantly reduce the size of regression test
suites.
Abstract: This paper focuses on a critical component of the
situational awareness (SA), the control of autonomous vertical flight
for vectored thrust aerial vehicle (VTAV). With the SA strategy, we
proposed a neural network motion control procedure to address the
dynamics variation and performance requirement difference of flight
trajectory for a VTAV. This control strategy with using of NARMAL2
neurocontroller for chosen model of VTAV has been verified by
simulation of take-off and forward maneuvers using software
package Simulink and demonstrated good performance for fast
stabilization of motors, consequently, fast SA with economy in
energy can be asserted during search-and-rescue operations.
Abstract: Academicians at the Arab Open University have
always voiced their concern about the efficacy of the blended
learning process. Based on 75% independent study and 25% face-toface
tutorial, it poses the challenge of the predisposition to
adjustment. Being used to the psychology of traditional educational
systems, AOU students cannot be easily weaned from being spoonfed.
Hence they lack the motivation to plunge into self-study. For
better involvement of AOU students into the learning practices, it is
imperative to diagnose the factors that impede or increase their
motivation. This is conducted through an empirical study grounded
upon observations and tested hypothesis and aimed at monitoring and
optimizing the students’ learning outcome. Recommendations of the
research will follow the findings.
Abstract: To construct the lumped spring-mass model
considering the occupants for the offset frontal crash, the SISAME
software and the NHTSA test data were used. The data on 56 kph 40%
offset frontal vehicle to deformable barrier crash test of a MY2007
Mazda 6 4-door sedan were obtained from NHTSA test database. The
overall behaviors of B-pillar and engine of simulation models agreed
very well with the test data. The trends of accelerations at the driver
and passenger head were similar but big differences in peak values.
The differences of peak values caused the large errors of the HIC36
and 3 ms chest g’s. To predict well the behaviors of dummies, the
spring-mass model for the offset frontal crash needs to be improved.
Abstract: Model transformation, as a pivotal aspect of Modeldriven
engineering, attracts more and more attentions both from
researchers and practitioners. Many domains (enterprise engineering,
software engineering, knowledge engineering, etc.) use model
transformation principles and practices to serve to their domain
specific problems; furthermore, model transformation could also be
used to fulfill the gap between different domains: by sharing and
exchanging knowledge. Since model transformation has been widely
used, there comes new requirement on it: effectively and efficiently
define the transformation process and reduce manual effort that
involved in. This paper presents an automatic model transformation
methodology based on semantic and syntactic comparisons, and
focuses particularly on granularity issue that existed in transformation
process. Comparing to the traditional model transformation
methodologies, this methodology serves to a general purpose: crossdomain
methodology. Semantic and syntactic checking
measurements are combined into a refined transformation process,
which solves the granularity issue. Moreover, semantic and syntactic
comparisons are supported by software tool; manual effort is replaced
in this way.
Abstract: Designing cost-efficient, secure network protocols for
Wireless Sensor Networks (WSNs) is a challenging problem because
sensors are resource-limited wireless devices. Security services such
as authentication and improved pairwise key establishment are
critical to high efficient networks with sensor nodes. For sensor
nodes to correspond securely with each other efficiently, usage of
cryptographic techniques is necessary. In this paper, two key
predistribution schemes that enable a mobile sink to establish a
secure data-communication link, on the fly, with any sensor nodes.
The intermediate nodes along the path to the sink are able to verify
the authenticity and integrity of the incoming packets using a
predicted value of the key generated by the sender’s essential power.
The proposed schemes are based on the pairwise key with the mobile
sink, our analytical results clearly show that our schemes perform
better in terms of network resilience to node capture than existing
schemes if used in wireless sensor networks with mobile sinks.
Abstract: Under active stress conditions, a rigid cantilever
retaining wall tends to rotate about a pivot point located within the
embedded depth of the wall. For purely granular and cohesive soils, a
methodology was previously reported called minimization of moment
ratio to determine the location of the pivot point of rotation. The
usage of this new methodology is to estimate the rotational stability
safety factor. Moreover, the degree of improvement required in a
backfill to get a desired safety factor can be estimated by the concept
of the shear strength demand. In this article, the accuracy of this
method for another type of cantilever walls called Contiguous Bored
Pile (CBP) retaining wall is evaluated by using physical modeling
technique. Based on observations, the results of moment ratio
minimization method are in good agreement with the results of the
carried out physical modeling.
Abstract: This paper presents an approach for the classification of
an unstructured format description for identification of file formats.
The main contribution of this work is the employment of data mining
techniques to support file format selection with just the unstructured
text description that comprises the most important format features for
a particular organisation. Subsequently, the file format indentification
method employs file format classifier and associated configurations to
support digital preservation experts with an estimation of required file
format. Our goal is to make use of a format specification knowledge
base aggregated from a different Web sources in order to select file
format for a particular institution. Using the naive Bayes method,
the decision support system recommends to an expert, the file format
for his institution. The proposed methods facilitate the selection of
file format and the quality of a digital preservation process. The
presented approach is meant to facilitate decision making for the
preservation of digital content in libraries and archives using domain
expert knowledge and specifications of file formats. To facilitate
decision-making, the aggregated information about the file formats is
presented as a file format vocabulary that comprises most common
terms that are characteristic for all researched formats. The goal is to
suggest a particular file format based on this vocabulary for analysis
by an expert. The sample file format calculation and the calculation
results including probabilities are presented in the evaluation section.
Abstract: This research aims to develop an algorithm to
generate a schedule of multiple cranes that will maximize load
throughputs in anodizing operation. The algorithm proposed utilizes
an enumerative strategy to search for constant time between
successive loads and crane covering range over baths. The computer
program developed is able to generate a near-optimal crane schedule
within reasonable times, i.e. within 10 minutes. Its results are
compared with existing solutions from an aluminum extrusion
industry. The program can be used to generate crane schedules for
mixed products, thus allowing mixed-model line balancing to
improve overall cycle times.
Abstract: This paper presents a computational study of steady
state three dimensional very high turbulent flow and heat transfer
characteristics in a constant temperature-surfaced circular duct fitted
with 900 hemispherical inline baffles. The computations are based on
realizable k-ɛ model with standard wall function considering the
finite volume method, and the SIMPLE algorithm has been
implemented. Computational Study are carried out for Reynolds
number, Re ranging from 80000 to 120000, Prandtl Number, Pr of
0.73, Pitch Ratios, PR of 1,2,3,4,5 based on the hydraulic diameter of
the channel, hydrodynamic entry length, thermal entry length and the
test section. Ansys Fluent 15.0 software has been used to solve the
flow field. Study reveals that circular pipe having baffles has a higher
Nusselt number and friction factor compared to the smooth circular
pipe without baffles. Maximum Nusselt number and friction factor
are obtained for the PR=5 and PR=1 respectively. Nusselt number
increases while pitch ratio increases in the range of study; however,
friction factor also decreases up to PR 3 and after which it becomes
almost constant up to PR 5. Thermal enhancement factor increases
with increasing pitch ratio but with slightly decreasing Reynolds
number in the range of study and becomes almost constant at higher
Reynolds number. The computational results reveal that optimum
thermal enhancement factor of 900 inline hemispherical baffle is
about 1.23 for pitch ratio 5 at Reynolds number 120000.It also shows
that the optimum pitch ratio for which the baffles can be installed in
such very high turbulent flows should be 5. Results show that pitch
ratio and Reynolds number play an important role on both fluid flow
and heat transfer characteristics.
Abstract: The aim of this investigation is to elaborate nearinfrared
methods for testing and recognition of chemical components
and quality in “Pannon wheat” allied (i.e. true to variety or variety
identified) milling fractions as well as to develop spectroscopic
methods following the milling processes and evaluate the stability of
the milling technology by different types of milling products and
according to sampling times, respectively. These wheat categories
produced under industrial conditions where samples were collected
versus sampling time and maximum or minimum yields. The changes
of the main chemical components (such as starch, protein, lipid) and
physical properties of fractions (particle size) were analysed by
dispersive spectrophotometers using visible (VIS) and near-infrared
(NIR) regions of the electromagnetic radiation. Close correlation
were obtained between the data of spectroscopic measurement
techniques processed by various chemometric methods (e.g. principal
component analysis [PCA], cluster analysis [CA]) and operation
condition of milling technology. It is obvious that NIR methods are
able to detect the deviation of the yield parameters and differences of
the sampling times by a wide variety of fractions, respectively. NIR
technology can be used in the sensitive monitoring of milling
technology.
Abstract: By the evolvement in technology, the way of
expressing opinions switched direction to the digital world. The
domain of politics, as one of the hottest topics of opinion mining
research, merged together with the behavior analysis for affiliation
determination in texts, which constitutes the subject of this paper.
This study aims to classify the text in news/blogs either as
Republican or Democrat with the minimum number of features. As
an initial set, 68 features which 64 were constituted by Linguistic
Inquiry and Word Count (LIWC) features were tested against 14
benchmark classification algorithms. In the later experiments, the
dimensions of the feature vector reduced based on the 7 feature
selection algorithms. The results show that the “Decision Tree”,
“Rule Induction” and “M5 Rule” classifiers when used with “SVM”
and “IGR” feature selection algorithms performed the best up to
82.5% accuracy on a given dataset. Further tests on a single feature
and the linguistic based feature sets showed the similar results. The
feature “Function”, as an aggregate feature of the linguistic category,
was found as the most differentiating feature among the 68 features
with the accuracy of 81% in classifying articles either as Republican
or Democrat.
Abstract: In this work, the Ictalurus punctatus species estimated
available physical habitat is compared with the estimated physical
habitat for the same but modified river reach, with the aim of creating
a linear park, along a length of 5 500 m.
To determine the effect of ecological park construction, on
physical habitat of the Lerma river stretch of study, first, the available
habitat for the Ictalurus punctatus species was estimated through the
simulation of the physical habitat, by using surveying, hydraulics,
and habitat information gotten at the river reach in its actual situation.
Second, it was estimated the available habitat for the above species,
upon the simulation of the physical habitat through the proposed
modification for the ecological park creation. Third, it is presented a
comparison between both scenarios in terms of available habitat
estimated for Ictalurus punctatus species, concluding that in cases of
adult and spawning life stages, changes in the channel to create an
ecological park would produce a considerable loss of potentially
usable habitat (PUH), while in the case of the juvenile life stage PUH
remains virtually unchanged, and in the case of life stage fry the PUH
would increase due to the presence of velocities and depths of lesser
magnitude, due to the presence of minor flow rates and lower volume
of the wet channel.
It is expected that habitat modification for linear park construction
may produce the lack of Ictalurus punktatus species conservation at
the river reach of the study.
Abstract: A pilot field study was conducted at the Jagjeetpur
Municipal Sewage treatment plant situated in the Haridwar town in
Uttarakhand state, India. The objectives of the present study were to
study the effect of treated wastewater on the production of various
paddy varieties (Sharbati, PR-114, PB-1, Menaka, PB1121 and PB
1509) and the emission of GHG gases (CO2, CH4 and N2O) as
compared to the same varieties grown in the control plots irrigated
with fresh water. Of late, the concept of water footprint assessment
has emerged, which explains enumeration of various types of water
footprints of an agricultural entity from its production to processing
stages. Paddy, the most water demanding staple crop of Uttarakhand
state, displayed a high green water footprint value of 2474.12 m3/
Ton. Most of the wastewater irrigated varieties displayed up to 6%
increase in production, except Menaka and PB-1121, which showed a
reduction in production (6% and 3% respectively), due to pest and
insect infestation. The treated wastewater was observed to be rich in
Nitrogen (55.94 mg/ml Nitrate), Phosphorus (54.24 mg/ml) and
Potassium (9.78 mg/ml), thus rejuvenating the soil quality and not
requiring any external nutritional supplements. A Percentage increase
of GHG gases of irrigation with treated municipal wastewater as
compared to control plots was observed as 0.4% - 8.6% (CH4), 1.1%
- 9.2% (CO2), and 0.07% - 5.8% (N2O). The variety, Sharbati,
displayed maximum production (5.5 ton/ha) and emerged as the most
resistant variety against pests and insects. The emission values of
CH4, CO2 and N2O were 729.31 mg/m2/d, 322.10 mg/m2/d and
400.21 mg/m2/d in water stagnant condition.
This study highlighted a successful possibility of reuse of
wastewater for non-potable purposes offering the potential for
exploiting this resource that can replace or reduce the existing use of
fresh water sources in agriculture sector.
Abstract: Submerged arc welding is a very complex process. It
is a very efficient and high performance welding process. In this
present study an attempt have been done to reduce the welding
distortion by increased amount of oxide flux through TiO2 in
submerged arc welding process. Care has been taken to avoid the
excessiveness of the adding agent for attainment of significant
results. Data Envelopment Analysis (DEA) based BAT algorithm is
used for the parametric optimization purpose in which DEA is used
to convert multi response parameters into a single response
parameter. The present study also helps to know the effectiveness of
the addition of TiO2 in active flux during submerged arc welding
process.
Abstract: Experimental economics is subject to criticism with
regards to frequently discussed the trade-off between internal and
external validity requirements, which seems to be critically flawed.
This paper evaluates incompatibility of trade-off condition and
condition of internal validity as a prerequisite for external validity. In
addition, it outlines the imprecise concept of artificiality, which is
found to be rather improving the external validity and seems to
strengthen the illusory status of external versus internal validity
tension. Internal validity is further analyzed with regards to Duhem-
Quine problem, where unpredictability argument is significantly
weakened trough application of inductivism within the illustrative
hypothetical-deductive model. Our discussion partially weakens
critical arguments related to the robustness of results in experimental
economics, if the perfectly controlled experimental environment is
secured.
Abstract: The security of cloud services is the concern of cloud
service providers. In this paper, we will mention different
classifications of cloud attacks referred by specialized organizations.
Each agency has its classification of well-defined properties. The
purpose is to present a high-level classification of current research in
cloud computing security. This classification is organized around
attack strategies and corresponding defenses.
Abstract: As technology-based service industries grow
drastically worldwide; companies are recognizing the importance of
market preoccupancy and have made an effort to capture a large
market to gain the upper hand. To this end, a focus on patents can be
used to determine the properties of a technology, as well as to capture
advantages in technical skills, in comparison with the firm’s
competitors. However, technology-based services largely depend not
only on their technological value but also their economic value, due
to the recognized worth that is passed to a plurality of users. Thus, it
is important to determine whether there are any competitors in the
target areas and what services they provide in any field. Despite this
importance, little effort has been made to systematically benchmark
competitors in order to identify business opportunities. Thus, this
study aims to not only identify each position of technology-centered
service companies in complex market dynamics, but also to discover
new business opportunities. For this, we try to consider both
technology and market environments simultaneously by utilizing
patent data as a representative proxy for technology and trademark
dates as an index for a firm’s target goods and services. Theoretically,
this is one of the earliest attempts to combine patent data and
trademark data to analyze corporate strategies. In practice, the
research results are expected to be used as a decision criterion to
diagnose the economic value that companies can obtain by entering
the market, as well as the technological value to be passed onto their
customers. Thus, the proposed approach can be useful to support
effective technology and business strategies in a firm.
Abstract: Any signal transmitted over a channel is corrupted by noise and interference. A host of channel coding techniques has been proposed to alleviate the effect of such noise and interference. Among these Turbo codes are recommended, because of increased capacity at higher transmission rates and superior performance over convolutional codes. The multimedia elements which are associated with ample amount of data are best protected by Turbo codes. Turbo decoder employs Maximum A-posteriori Probability (MAP) and Soft Output Viterbi Decoding (SOVA) algorithms. Conventional Turbo coded systems employ Equal Error Protection (EEP) in which the protection of all the data in an information message is uniform. Some applications involve Unequal Error Protection (UEP) in which the level of protection is higher for important information bits than that of other bits. In this work, enhancement to the traditional Log MAP decoding algorithm is being done by using optimized scaling factors for both the decoders. The error correcting performance in presence of UEP in Additive White Gaussian Noise channel (AWGN) and Rayleigh fading are analyzed for the transmission of image with Discrete Cosine Transform (DCT) as source coding technique. This paper compares the performance of log MAP, Modified log MAP (MlogMAP) and Enhanced log MAP (ElogMAP) algorithms used for image transmission. The MlogMAP algorithm is found to be best for lower Eb/N0 values but for higher Eb/N0 ElogMAP performs better with optimized scaling factors. The performance comparison of AWGN with fading channel indicates the robustness of the proposed algorithm. According to the performance of three different message classes, class3 would be more protected than other two classes. From the performance analysis, it is observed that ElogMAP algorithm with UEP is best for transmission of an image compared to Log MAP and MlogMAP decoding algorithms.
Abstract: Using the quantum hydrodynamic (QHD) model the
nonlinear properties of ion-acoustic waves in are lativistically
degenerate quantum plasma is investigated by deriving a nonlinear
Spherical Kadomtsev–Petviashvili (SKP) equation using the
standard reductive perturbation method equation. It was found that
the electron degeneracy parameter significantly affects the linear
and nonlinear properties of ion-acoustic waves in quantum plasma.