Abstract: The arm length, hand length, hand breadth and middle
finger length of 1540 right-handed industrial workers of Haryana
state was used to assess the relationship between the upper limb
dimensions and stature. Initially, the data were analyzed using basic
univariate analysis and independent t-tests; then simple and multiple
linear regression models were used to estimate stature using SPSS
(version 17). There was a positive correlation between upper limb
measurements (hand length, hand breadth, arm length and middle
finger length) and stature (p < 0.01), which was highest for hand
length. The accuracy of stature prediction ranged from ± 54.897 mm
to ± 58.307 mm. The use of multiple regression equations gave better
results than simple regression equations. This study provides new
forensic standards for stature estimation from the upper limb
measurements of male industrial workers of Haryana (India). The
results of this research indicate that stature can be determined using
hand dimensions with accuracy, when only upper limb is available
due to any reasons likewise explosions, train/plane crashes, mutilated
bodies, etc. The regression formula derived in this study will be
useful for anatomists, archaeologists, anthropologists, design
engineers and forensic scientists for fairly prediction of stature using
regression equations.
Abstract: In this paper, a new design of spherical robotic system
based on the concepts of gimbal structure and gyro dynamics is
presented. Robots equipped with multiple wheels and complex
steering mechanics may increase the weight and degrade the energy
transmission efficiency. In addition, the wheeled and legged robots are
relatively vulnerable to lateral impact and lack of lateral mobility.
Therefore, the proposed robotic design uses a spherical shell as the
main body for ground locomotion, instead of using wheel devices.
Three spherical shells are structured in a similar way to a gimbal
device and rotate like a gyro system. The design and mechanism of the
proposed robotic system is introduced. In addition, preliminary results
of the dynamic model based on the principles of planar rigid body
kinematics and Lagrangian equation are included. Simulation results
and rig construction are presented to verify the concepts.
Abstract: Two finite element (FEM) models are presented in
this paper to address the random nature of the response of glued
timber structures made of wood segments with variable elastic
moduli evaluated from 3600 indentation measurements. This total
database served to create the same number of ensembles as was the
number of segments in the tested beam. Statistics of these ensembles
were then assigned to given segments of beams and the Latin
Hypercube Sampling (LHS) method was called to perform 100
simulations resulting into the ensemble of 100 deflections subjected
to statistical evaluation. Here, a detailed geometrical arrangement of
individual segments in the laminated beam was considered in the
construction of two-dimensional FEM model subjected to in fourpoint
bending to comply with the laboratory tests. Since laboratory
measurements of local elastic moduli may in general suffer from a
significant experimental error, it appears advantageous to exploit the
full scale measurements of timber beams, i.e. deflections, to improve
their prior distributions with the help of the Bayesian statistical
method. This, however, requires an efficient computational model
when simulating the laboratory tests numerically. To this end, a
simplified model based on Mindlin’s beam theory was established.
The improved posterior distributions show that the most significant
change of the Young’s modulus distribution takes place in laminae in
the most strained zones, i.e. in the top and bottom layers within the
beam center region. Posterior distributions of moduli of elasticity
were subsequently utilized in the 2D FEM model and compared with
the original simulations.
Abstract: The aim of this work is to build a model based on
tissue characterization that is able to discriminate pathological and
non-pathological regions from three-phasic CT images. With our
research and based on a feature selection in different phases, we are
trying to design a neural network system with an optimal neuron
number in a hidden layer. Our approach consists of three steps:
feature selection, feature reduction, and classification. For each
region of interest (ROI), 6 distinct sets of texture features are
extracted such as: first order histogram parameters, absolute gradient,
run-length matrix, co-occurrence matrix, autoregressive model, and
wavelet, for a total of 270 texture features. When analyzing more
phases, we show that the injection of liquid cause changes to the high
relevant features in each region. Our results demonstrate that for
detecting HCC tumor phase 3 is the best one in most of the features
that we apply to the classification algorithm. The percentage of
detection between pathology and healthy classes, according to our
method, relates to first order histogram parameters with accuracy of
85% in phase 1, 95% in phase 2, and 95% in phase 3.
Abstract: Geometric and mechanical properties all influence the
resistance of RC structures and may, in certain combination of
property values, increase the risk of a brittle failure of the whole
system.
This paper presents a statistical and probabilistic investigation on
the resistance of RC beams designed according to Eurocodes 2 and 8,
and subjected to multiple failure modes, under both the natural
variation of material properties and the uncertainty associated with
cross-section and transverse reinforcement geometry. A full
probabilistic model based on JCSS Probabilistic Model Code is
derived. Different beams are studied through material nonlinear
analysis via Monte Carlo simulations. The resistance model is
consistent with Eurocode 2. Both a multivariate statistical evaluation
and the data clustering analysis of outcomes are then performed.
Results show that the ultimate load behaviour of RC beams
subjected to flexural and shear failure modes seems to be mainly
influenced by the combination of the mechanical properties of both
longitudinal reinforcement and stirrups, and the tensile strength of
concrete, of which the latter appears to affect the overall response of
the system in a nonlinear way. The model uncertainty of the
resistance model used in the analysis plays undoubtedly an important
role in interpreting results.
Abstract: This research focused on comparing the critical
thinking of the teacher students before and after using Miller’s Model
learning activities and investigating their opinions. The sampling
groups were (1) fourth year 33 student teachers majoring in Early
Childhood Education and enrolling in semester 1 of academic year
2013 (2) third year 28 student teachers majoring in English and
enrolling in semester 2 of academic year 2013 and (3) third year 22
student teachers majoring in Thai and enrolling in semester 2 of
academic year 2013. The research instruments were (1) lesson plans
where the learning activities were settled based on Miller’s Model (2)
critical thinking assessment criteria and (3) a questionnaire on
opinions towards Miller’s Model based learning activities. The
statistical treatment was mean, deviation, different scores and T-test.
The result unfolded that (1) the critical thinking of the students after
the assigned activities was better than before and (2) the students’
opinions towards the critical thinking improvement activities based
on Miller’s Model ranged from the level of high to highest.
Abstract: The western Tombolo of the Giens peninsula in
southern France, known as Almanarre beach, is subject to coastal
erosion. We are trying to use computer simulation in order to propose
solutions to stop this erosion. Our aim was first to determine the main
factors for this erosion and successfully apply a coupled hydrosedimentological
numerical model based on observations and
measurements that have been performed on the site for decades.
We have gathered all available information and data about waves,
winds, currents, tides, bathymetry, coastal line, and sediments
concerning the site. These have been divided into two sets: one
devoted to calibrating a numerical model using Mike 21 software, the
other to serve as a reference in order to numerically compare the
present situation to what it could be if we implemented different
types of underwater constructions.
This paper presents the first part of the study: selecting and
melting different sources into a coherent data basis, identifying the
main erosion factors, and calibrating the coupled software model
against the selected reference period.
Our results bring calibration of the numerical model with good
fitting coefficients. They also show that the winter South-Western
storm events conjugated to depressive weather conditions constitute a
major factor of erosion, mainly due to wave impact in the northern
part of the Almanarre beach. Together, current and wind impact is
shown negligible.
Abstract: Nowadays, the successful implementation of ICTs is
vital for almost any kind of organization. Good governance and ICT
management are essential for delivering value, managing
technological risks, managing resources and performance
measurement. In addition, outsourcing is a strategic IT service
solution which complements IT services provided internally in
organizations. This paper proposes the measurement tools of a new
holistic maturity model based on standards ISO/IEC 20000 and
ISO/IEC 38500, and the frameworks and best practices of ITIL and
COBIT, with a specific focus on IT outsourcing. These measurement
tools allow independent validation and practical application in the
field of higher education, using a questionnaire, metrics tables, and
continuous improvement plan tables as part of the measurement
process. Guidelines and standards are proposed in the model for
facilitating adaptation to universities and achieving excellence in the
outsourcing of IT services.
Abstract: In this paper, Fuzzy C-Means clustering with
Expectation Maximization-Gaussian Mixture Model based hybrid
modeling algorithm is proposed for Continuous Tamil Speech
Recognition. The speech sentences from various speakers are used
for training and testing phase and objective measures are between the
proposed and existing Continuous Speech Recognition algorithms.
From the simulated results, it is observed that the proposed algorithm
improves the recognition accuracy and F-measure up to 3% as
compared to that of the existing algorithms for the speech signal from
various speakers. In addition, it reduces the Word Error Rate, Error
Rate and Error up to 4% as compared to that of the existing
algorithms. In all aspects, the proposed hybrid modeling for Tamil
speech recognition provides the significant improvements for speechto-
text conversion in various applications.
Abstract: Taro Scarab beetles (Papuana uninodis, Coleoptera:
Scarabaeidae) inflict severe damage on important root crops and
plants such as Taro or Cocoyam, yam, sweet potatoes, oil palm and
coffee tea plants across Africa and Asia resulting in economic
hardship and starvation in some nations. Scoliid wasps and
Metarhizium anisopliae fungus - bio-control agents; are shown to be
able to control the population of Scarab beetle adults and larvae using
a newly created simulation model based on non-linear ordinary
differential equations that track the populations of the beetle life
cycle stages: egg, larva, pupa, adult and the population of the scoliid
parasitoid wasps, which attack beetle larvae. In spite of the challenge
driven by the longevity of the scarab beetles, the combined effect of
the larval wasps and the fungal bio-control agent is able to control
and drive down the population of both the adult and the beetle eggs
below the environmental carrying capacity within an interval of 120
days, offering the long term prospect of a stable and eco-friendly
environment; where the population of scarab beetles is: regulated by
parasitoid wasps and beneficial soil saprophytes.
Abstract: The world wide web network is a network with a
complex topology, the main properties of which are the distribution
of degrees in power law, A low clustering coefficient and a weak
average distance. Modeling the web as a graph allows locating the
information in little time and consequently offering a help in the
construction of the research engine. Here, we present a model based
on the already existing probabilistic graphs with all the aforesaid
characteristics. This work will consist in studying the web in order to
know its structuring thus it will enable us to modelize it more easily
and propose a possible algorithm for its exploration.
Abstract: In this study, we develop a performance evaluation
model based on a multi-attribute utility approach aiming at reaching
the sustainable banking (SB) status. This model is built accounting
for various banks’ stakeholders in a win-win paradigm. In addition, it
offers the opportunity for adopting a global measure of performance
as an indication of a bank’s sustainability degree. This measure is
referred to as banking sustainability performance index (BSPI). This
index may constitute a basis for ranking banks. Moreover, it may
constitute a bridge between the assessment types of financial and
extra-financial rating agencies. A real application is performed on
three French banks.
Abstract: Most flexible rotors can be considered as beam-like
structures. In many cases, rotors are modeled as one-dimensional
bodies, made basically of beam-like shafts with rigid bodies attached
to them. This approach is typical of rotor dynamics, both analytical
and numerical, and several rotor dynamic codes, based on the finite
element method, follow this trend. In this paper, a finite element
model based on Timoshenko beam elements is utilized to analyze the
lateral dynamic behavior of a certain rotor-bearing system in
operating conditions.
Abstract: The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.
Abstract: This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in VerilogHDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.
Abstract: In the implementation of Carbon Nanotube Reinforced Polymer matrix Composites in structural applications, deflection and stress analysis are important considerations. In the present study, a multi scale analysis of deflection and stress analysis of carbon nanotube (CNT) reinforced polymer composite plates is presented. A micromechanics model based on the Mori-Tanaka method is developed by introducing straight CNTs aligned in one direction. The effect of volume fraction and diameter of CNTs on plate deflection and the stresses are investigated using classical laminate plate theory (CLPT). The study is primarily conducted with the intention of observing the suitability of CNT reinforced polymer composite plates under static loading for structural applications.
Abstract: Narrow bandwidth and high loss performance limits the use of reflectarray antennas in some applications. This article reports on the feasibility of employing strategic reflectarray resonant elements to characterize the reflectivity performance of reflectarrays in X-band frequency range. Strategic reflectarray resonant elements incorporating variable substrate thicknesses ranging from 0.016λ to 0.052λ have been analyzed in terms of reflection loss and reflection phase performance. The effect of substrate thickness has been validated by using waveguide scattering parameter technique. It has been demonstrated that as the substrate thickness is increased from 0.508mm to 1.57mm the measured reflection loss of dipole element decreased from 5.66dB to 3.70dB with increment in 10% bandwidth of 39MHz to 64MHz. Similarly the measured reflection loss of triangular loop element is decreased from 20.25dB to 7.02dB with an increment in 10% bandwidth of 12MHz to 23MHz. The results also show a significant decrease in the slope of reflection phase curve as well. A Figure of Merit (FoM) has also been defined for the comparison of static phase range of resonant elements under consideration. Moreover, a novel numerical model based on analytical equations has been established incorporating the material properties of dielectric substrate and electrical properties of different reflectarray resonant elements to obtain the progressive phase distribution for each individual reflectarray resonant element.
Abstract: Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies economic order quantity (EOQ), just in time (JIT), vendor managed inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.
Abstract: Today is widely understood that global energy consumption patterns are directly related to the urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals.
In this paper a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities and economic development and the local and global environment while safeguarding fairness in the energy sector.
Abstract: In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.