Abstract: This paper introduces symbiotic organism search (SOS)
for solving capacitated vehicle routing problem (CVRP). SOS is a new
approach in metaheuristics fields and never been used to solve discrete
problems. A sophisticated decoding method to deal with a discrete
problem setting in CVRP is applied using the basic symbiotic
organism search (SOS) framework. The performance of the algorithm
was evaluated on a set of benchmark instances and compared results
with best known solution. The computational results show that the
proposed algorithm can produce good solution as a preliminary
testing. These results indicated that the proposed SOS can be applied
as an alternative to solve the capacitated vehicle routing problem.
Abstract: Fabric textures are very common in our daily life.
However, the representation of fabric textures has never been explored
from neuroscience view. Theoretical studies suggest that primary
visual cortex (V1) uses a sparse code to efficiently represent natural
images. However, how the simple cells in V1 encode the artificial
textures is still a mystery. So, here we will take fabric texture as
stimulus to study the response of independent component analysis that
is established to model the receptive field of simple cells in V1. We
choose 140 types of fabrics to get the classical fabric textures as
materials. Experiment results indicate that the receptive fields of
simple cells have obvious selectivity in orientation, frequency and
phase when drifting gratings are used to determine their tuning
properties. Additionally, the distribution of optimal orientation and
frequency shows that the patch size selected from each original fabric
image has a significant effect on the frequency selectivity.
Abstract: The growth in the volume of text data such as books
and articles in libraries for centuries has imposed to establish
effective mechanisms to locate them. Early techniques such as
abstraction, indexing and the use of classification categories have
marked the birth of a new field of research called "Information
Retrieval". Information Retrieval (IR) can be defined as the task of
defining models and systems whose purpose is to facilitate access to
a set of documents in electronic form (corpus) to allow a user to find
the relevant ones for him, that is to say, the contents which matches
with the information needs of the user. This paper presents a new
semantic indexing approach of a documentary corpus. The indexing
process starts first by a term weighting phase to determine the
importance of these terms in the documents. Then the use of a
thesaurus like Wordnet allows moving to the conceptual level.
Each candidate concept is evaluated by determining its level of
representation of the document, that is to say, the importance of the
concept in relation to other concepts of the document. Finally, the
semantic index is constructed by attaching to each concept of the
ontology, the documents of the corpus in which these concepts are
found.
Abstract: A central element of higher education today is the
“core” or “general education” curriculum: that configuration of
courses that often encompasses the essence of liberal arts education.
Ensuring that such offerings reflect the mission and values of the
institution is a challenge faced by most college and universities, often
more than once. This paper presents an action model of program
planning designed to structure the processes of developing,
implementing and revising core curricula in a manner consistent with
key institutional goals and objectives. Through presentation of a case
study from a university in the United States, the elements of needs
assessment, stakeholder investment and collaborative compromise
are shown as key components of a planning strategy that can produce
a general education program that is comprehensive, academically
rigorous, assessable, and mission consistent. The paper concludes
with recommendations for both the implementation and evaluation of
such programs in practice.
Abstract: Cortisol is essential to the regulation of the immune
system and yawning is a pathological symptom of multiple sclerosis
(MS). Electromyography activity (EMG) in the jaw muscles typically
rises when the muscles are moved and with yawning is highly
correlated with cortisol levels in healthy people. Saliva samples from
59 participants were collected at the start and after yawning, or at the
end of the presentation of yawning-provoking stimuli, in the absence
of a yawn, together with EMG data and questionnaire data: Hospital
Anxiety and Depression Scale, Yawning Susceptibility Scale,
General Health Questionnaire, demographic, health details. Exclusion
criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high
blood pressure, hormone replacement therapy, multiple sclerosis,
stroke. Significant differences were found between the saliva cortisol
samples for the yawners, t (23) = -4.263, p = 0.000, as compared with
the non-yawners between rest and post-stimuli, which was nonsignificant.
Significant evidence was found to support the Thompson
Cortisol Hypothesis suggesting that rises in cortisol levels are
associated with yawning. Further research is exploring the use of
cortisol as an early diagnostic tool for MS. Ethics approval granted
and professional code of conduct, confidentiality, and safety issues
are approved therein.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: In our research we aimed to test a managerial
approach for the fuzzy front end (FFE) of innovation by creating
controlled experiment/ business case in a breakthrough innovation
development. The experiment was in the sport industry and covered
all aspects of the customer discovery stage from ideation to
prototyping followed by patent application. In the paper we describe
and analyze mile stones, tasks, management challenges, decisions
made to create the break through innovation, evaluate overall
managerial efficiency that was at the considered FFE stage.
We set managerial outcome of the FFE stage as a valid product
concept in hand. In our paper we introduce hypothetical construct
“Q-factor” that helps us in the experiment to distinguish quality of
FFE outcomes.
The experiment simulated for entrepreneur the FFE of innovation
and put on his shoulders responsibility for the outcome of valid
product concept. While developing managerial approach to reach the
outcome there was a decision to look on product concept from the
cognitive psychology and cognitive science point of view. This view
helped us to develop the profile of a person whose projection (mental
representation) of a new product could optimize for a manager or
entrepreneur FFE activities. In the experiment this profile was tested
to develop breakthrough innovation for swimmers. Following the
managerial approach the product concept was created to help
swimmers to feel/sense water. The working prototype was developed
to estimate the product concept validity and value added effect for
customers.
Based on feedback from coachers and swimmers there were strong
positive effect that gave high value for customers, and for the
experiment – the valid product concept being developed by proposed
managerial approach for the FFE.
In conclusions there is a suggestion of managerial approach that
was derived from experiment.
Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: An innovative concept called “Flexy-Energy” is developing at 2iE. This concept aims to produce electricity at lower cost by smartly mix different available energy sources in accordance to the load profile of the region. With a higher solar irradiation and due to the fact that Diesel generator are massively used in sub-Saharan rural areas, PV/Diesel hybrid systems could be a good application of this concept and a good solution to electrify this region, provided they are reliable, cost effective and economically attractive to investors. Presentation of the developed approach is the aims of this paper. The PV/Diesel hybrid system designed consists to produce electricity and/or heat from a coupling between Diesel Diesel generators and PV panels without batteries storage, while ensuring the substitution of gasoil by bio-fuels available in the area where the system will be installed. The optimal design of this system is based on his technical performances; the Life Cycle Cost (LCC) and Levelized Cost of Energy are developed and use as economic criteria. The Net Present Value (NPV), the internal rate of return (IRR) and the discounted payback (DPB) are also evaluated according to dual electricity pricing (in sunny and unsunny hours). The PV/Diesel hybrid system obtained is compared to the standalone Diesel Diesel generators. The approach carried out in this paper has been applied to Siby village in Mali (Latitude 12 ° 23'N 8 ° 20'W) with 295 kWh as daily demand.This approach provides optimal physical characteristics (size of the components, number of component) and dynamical characteristics in real time (number of Diesel generator on, their load rate, fuel specific consumptions, and PV penetration rate) of the system. The system obtained is slightly cost effective; but could be improved with optimized tariffing strategies.
Abstract: This study aimed to examine the management and
development of forest tourism Kamchanoad. Ban Dung, Udon Thani
sustainability. Data were collected by means of qualitative research
including in-depth interviews, semi- structured, and then the data
were summarized and discussed in accordance with the objectives.
And make a presentation in the form of lectures. The target
population for the study consisted of 16 people, including
representatives from government agencies, community leaders and
the community. The results showed that Guidelines for the
Management and Development of Forest Tourism Kamchanoad
include management of buildings and infrastructure such as roads,
water, electricity, toilets. Other developments are the establishment
of a service center that provides information and resources to
facilitate tourists.; nature trails and informative signage to educate
visitors on the path to the jungle Kamchanoad; forest activities for
tourists who are interested only in occasional educational activities
such as vegetation, etc.; disseminating information on various aspects
of tourism through various channels in both Thailand and English, as
well as a web site to encourage community involvement in the
planning and management of tourism together with the care and
preservation of natural resources and preserving the local cultural
tourist area of Kamchanoad.
Abstract: In this work, we begin with the presentation of the
Tθ family of usual similarity measures concerning multidimensional
binary data. Subsequently, some properties of these measures are
proposed. Finally the impact of the use of different inter-elements
measures on the results of the Agglomerative Hierarchical Clustering
Methods is studied.
Abstract: Over the past four decades, the fatigue behavior of
nickel-based alloys has been widely studied. However, in recent
years, significant advances in the fabrication process leading to grain
size reduction have been made in order to improve fatigue properties
of aircraft turbine discs. Indeed, a change in particle size affects the
initiation mode of fatigue cracks as well as the fatigue life of the
material. The present study aims to investigate the fatigue behavior of
a newly developed nickel-based superalloy under biaxial-planar
loading. Low Cycle Fatigue (LCF) tests are performed at different
stress ratios so as to study the influence of the multiaxial stress state
on the fatigue life of the material. Full-field displacement and strain
measurements as well as crack initiation detection are obtained using
Digital Image Correlation (DIC) techniques. The aim of this
presentation is first to provide an in-depth description of both the
experimental set-up and protocol: the multiaxial testing machine, the
specific design of the cruciform specimen and performances of the
DIC code are introduced. Second, results for sixteen specimens
related to different load ratios are presented. Crack detection, strain
amplitude and number of cycles to crack initiation vs. triaxial stress
ratio for each loading case are given. Third, from fractographic
investigations by scanning electron microscopy it is found that the
mechanism of fatigue crack initiation does not depend on the triaxial
stress ratio and that most fatigue cracks initiate from subsurface
carbides.
Abstract: This paper presents two techniques, local feature
extraction using image spectrum and low frequency spectrum
modelling using GMM to capture the underlying statistical
information to improve the performance of face recognition
system. Local spectrum features are extracted using overlap sub
block window that are mapped on the face image. For each of this
block, spatial domain is transformed to frequency domain using
DFT. A low frequency coefficient is preserved by discarding high
frequency coefficients by applying rectangular mask on the
spectrum of the facial image. Low frequency information is non-
Gaussian in the feature space and by using combination of several
Gaussian functions that has different statistical properties, the best
feature representation can be modelled using probability density
function. The recognition process is performed using maximum
likelihood value computed using pre-calculated GMM components.
The method is tested using FERET datasets and is able to achieved
92% recognition rates.
Abstract: This paper describes the problem of building secure
computational services for encrypted information in the Cloud
Computing without decrypting the encrypted data; therefore, it meets
the yearning of computational encryption algorithmic aspiration
model that could enhance the security of big data for privacy,
confidentiality, availability of the users. The cryptographic model
applied for the computational process of the encrypted data is the
Fully Homomorphic Encryption Scheme. We contribute a theoretical
presentations in a high-level computational processes that are based
on number theory and algebra that can easily be integrated and
leveraged in the Cloud computing with detail theoretic mathematical
concepts to the fully homomorphic encryption models. This
contribution enhances the full implementation of big data analytics
based cryptographic security algorithm.
Abstract: The Cone Penetration Test (CPT) is a common in-situ
test which generally investigates a much greater volume of soil more
quickly than possible from sampling and laboratory tests. Therefore,
it has the potential to realize both cost savings and assessment of soil
properties rapidly and continuously. The principle objective of this
paper is to demonstrate the feasibility and efficiency of using
artificial neural networks (ANNs) to predict the soil angle of internal
friction (Φ) and the soil modulus of elasticity (E) from CPT results
considering the uncertainties and non-linearities of the soil. In
addition, ANNs are used to study the influence of different
parameters and recommend which parameters should be included as
input parameters to improve the prediction. Neural networks discover
relationships in the input data sets through the iterative presentation
of the data and intrinsic mapping characteristics of neural topologies.
General Regression Neural Network (GRNN) is one of the powerful
neural network architectures which is utilized in this study. A large
amount of field and experimental data including CPT results, plate
load tests, direct shear box, grain size distribution and calculated data
of overburden pressure was obtained from a large project in the
United Arab Emirates. This data was used for the training and the
validation of the neural network. A comparison was made between
the obtained results from the ANN's approach, and some common
traditional correlations that predict Φ and E from CPT results with
respect to the actual results of the collected data. The results show
that the ANN is a very powerful tool. Very good agreement was
obtained between estimated results from ANN and actual measured
results with comparison to other correlations available in the
literature. The study recommends some easily available parameters
that should be included in the estimation of the soil properties to
improve the prediction models. It is shown that the use of friction
ration in the estimation of Φ and the use of fines content in the
estimation of E considerable improve the prediction models.
Abstract: The purpose of this presentation is to describe an interdisciplinary teaching program that integrates physical education concepts using a philosophical approach. The presentation includes a review of: a) the philosophy of American education, b) the philosophy of sports and physical education, c) the interdisciplinary physical education program, d) professional development programs, (e) the Success of this physical education program, f) future of physical education. This unique interdisciplinary program has been implemented in an urban school physical education discipline in East Orange, New Jersey for over 10 years.
During the program the students realize that the bodies go through different experiences. The body becomes a place where a child can recognize in an enjoyable way to express and perceive particular feelings or mental states. Children may distinguish themselves to have high abilities in the social or other domains but low abilities in the field of athletics.
The goal of this program for the individuals is to discover new skills, develop and demonstrate age appropriate mastery level at different tasks, therefore the program consists of 9 to 12 sports, including many game. Each successful experience increases the awareness ability. Engaging in sports and physical activities are social movements involving groups of children in situations such as teams, friends, and recreational settings, which serve as a primary socializing agent for teaching interpersonal skills. As a result of this presentation the audience will reflect and explore how to structure a physical education program to integrate interdisciplinary subjects with philosophical concepts.
Abstract: Since “Hello Kitty” was manufactured in the market in
1974, the manufacturer, Sanrio Co., Ltd. gains high profits not only
Kitty’s products but also Kitty license, which gives us a picture of
Sanrio’s sales strategy in the global market. Kitty’s history, its
products, and Sanrio’s sales strategy are researched in this paper.
Comparing it to American Girl, and focusing on KITTYLAB, a type of
attraction where you can enjoy games with Kitty, and choose its parts
to build your own Kitty, the image of the cultural icon can be altered.
Abstract: The Blue Nile Basin is the most important tributary of
the Nile River. Egypt and Sudan are almost dependent on water
originated from the Blue Nile. This multi-dependency creates
conflicts among the three countries Egypt, Sudan, and Ethiopia
making the management of these conflicts as an international issue.
Good assessment of the water resources of the Blue Nile is an
important to help in managing such conflicts. Hydrological models
are good tool for such assessment. This paper presents a critical
review of the nature and variability of the climate and hydrology of
the Blue Nile Basin as a first step of using hydrological modeling to
assess the water resources of the Blue Nile. Many several attempts
are done to develop basin-scale hydrological modeling on the Blue
Nile. Lumped and semi distributed models used averages of
meteorological inputs and watershed characteristics in hydrological
simulation, to analyze runoff for flood control and water resource
management. Distributed models include the temporal and spatial
variability of catchment conditions and meteorological inputs to
allow better representation of the hydrological process. The main
challenge of all used models was to assess the water resources of the
basin is the shortage of the data needed for models calibration and
validation. It is recommended to use distributed model for their
higher accuracy to cope with the great variability and complexity of
the Blue Nile basin and to collect sufficient data to have more
sophisticated and accurate hydrological modeling.
Abstract: A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.