Abstract: Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.
Abstract: Leishmaniasis is the collective name for a number of
diseases caused by protozoan flagellates of the genus Leishmania,
which is transmitted by Phlebotomine sandfly, the disease has diverse
clinical manifestations and found in many areas of the world,
particularly in Africa, Latin America, South and Central Asia, the
Mediterranean basin and the Middle East. This study was done to
assess primary health care physicians’ knowledge (PHP) and attitude
about leishmaniasis and to assess awareness of local inhabitants
about the disease and its vector in four areas in west Alexandria,
Egypt. It is a cross sectional survey that was conducted in four PHC
units in west Alexandria. All physicians currently working in these
units during the study period were invited to participate in the study;
only 20 PHP completed the questionnaire. 60 local inhabitants were
selected randomly from the four areas of the study, 15 from each
area; Data was collected through two different specially designed
questionnaires. Results showed that 11 (55%) percent of the
physicians had satisfactory knowledge; they answered more than 9
(60%) questions out of a total 14 questions about leishmaniasis and
sandfly. On the other hand when attitude of the primary health care
physicians about leishmaniasis was measured, results showed that 17
(85%) had good attitude and 3 (15%) had poor attitude. The second
questionnaire showed that the awareness of local inhabitants about
leishmaniasis and sandfly as a vector of the disease is poor and needs
to be corrected. (90%) of the interviewed inhabitants had not heard
about leishmaniasis, Only 3 (5%) of them said they know sandfly and
its role in transmission of leishmaniasis. Thus we conclude that
knowledge and attitudes of physicians are acceptable. However, there
is, room for improvement and could be done through formal training
courses and distribution of guidelines. In addition to raising the
awareness of primary health care physicians about the importance of
early detection and notification of cases of leishmaniasis, health
education for raising awareness of the public regarding the vector and
the disease is necessary because related studies have demonstrated
that for inhabitants to take enough protective measures against the
vector, they should perceive that it is responsible for causing a
disease.
Abstract: The current paper presents the results of a conducted
case study. During the past few years the number of children
diagnosed with Learning Difficulties has drastically augmented and
especially the cases of ADHD (Attention Deficit Hyperactivity
Disorder). One of the core characteristics of ADHD is a deficit in
working memory functions. The review of the literature indicates a
plethora of educational software that aim at training and enhancing
the working memory. Nevertheless, in the current paper, the
possibility of using for the same purpose free, online games will be
explored. Another issue of interest is the potential effect of the
working memory training to the core symptoms of ADHD. In order
to explore the abovementioned research questions, three digital tests
are employed, all of which are developed on the E-slate platform by
the author, in order to check the levels of ADHD’s symptoms and to
be used as diagnostic tools, both in the beginning and in the end of
the case study. The tools used during the main intervention of the
research are free online games for the training of working memory.
The research and the data analysis focus on the following axes: a) the
presence and the possible change in two of the core symptoms of
ADHD, attention and impulsivity and b) a possible change in the
general cognitive abilities of the individual. The case study was
conducted with the participation of a thirteen year-old, female
student, diagnosed with ADHD, during after-school hours. The
results of the study indicate positive changes both in the levels of
attention and impulsivity. Therefore, we conclude that the training of
working memory through the use of free, online games has a positive
impact on the characteristics of ADHD. Finally, concerning the
second research question, the change in general cognitive abilities, no
significant changes were noted.
Abstract: The main objective of MEAL is to develop a
pedagogical tool aimed to help teachers and nutritionists (students
and professionals) to acquire, train, promote and deliver to children
basic nutritional education and healthy eating behaviours
competencies. MEAL is focused on eating behaviours and not only in
nutritional literacy, and will use new technologies like Information
and Communication Technologies (ICTs) and serious games (SG)
platforms to consolidate the nutritional competences and habits.
Abstract: The aim of this work was to characterize a potential
target group of people interested in participating into a training
program in organic farming in the context of mobile-learning. The
information sought addressed in particular, but not exclusively,
possible contents, formats and forms of evaluation that will
contribute to define the course objectives and curriculum, as well as
to ensure that the course meets the needs of the learners and their
preferences. The sample was selected among different European
countries. The questionnaires were delivered electronically for
answering on-line and in the end 135 consented valid questionnaires
were obtained. The results allowed characterizing the target group
and identifying their training needs and preferences towards m-learning
formats, giving valuable tools to design the training offer.
Abstract: Speaker Identification (SI) is the task of establishing
identity of an individual based on his/her voice characteristics. The SI
task is typically achieved by two-stage signal processing: training and
testing. The training process calculates speaker specific feature
parameters from the speech and generates speaker models
accordingly. In the testing phase, speech samples from unknown
speakers are compared with the models and classified. Even though
performance of speaker identification systems has improved due to
recent advances in speech processing techniques, there is still need of
improvement. In this paper, a Closed-Set Tex-Independent Speaker
Identification System (CISI) based on a Multiple Classifier System
(MCS) is proposed, using Mel Frequency Cepstrum Coefficient
(MFCC) as feature extraction and suitable combination of vector
quantization (VQ) and Gaussian Mixture Model (GMM) together
with Expectation Maximization algorithm (EM) for speaker
modeling. The use of Voice Activity Detector (VAD) with a hybrid
approach based on Short Time Energy (STE) and Statistical
Modeling of Background Noise in the pre-processing step of the
feature extraction yields a better and more robust automatic speaker
identification system. Also investigation of Linde-Buzo-Gray (LBG)
clustering algorithm for initialization of GMM, for estimating the
underlying parameters, in the EM step improved the convergence rate
and systems performance. It also uses relative index as confidence
measures in case of contradiction in identification process by GMM
and VQ as well. Simulation results carried out on voxforge.org
speech database using MATLAB highlight the efficacy of the
proposed method compared to earlier work.
Abstract: Over the past few years, a lot of research has been
conducted to bring Automatic Speech Recognition (ASR) into various
areas of Air Traffic Control (ATC), such as air traffic control
simulation and training, monitoring live operators for with the aim
of safety improvements, air traffic controller workload measurement
and conducting analysis on large quantities controller-pilot speech.
Due to the high accuracy requirements of the ATC context and its
unique challenges, automatic speech recognition has not been widely
adopted in this field. With the aim of providing a good starting
point for researchers who are interested bringing automatic speech
recognition into ATC, this paper gives an overview of possibilities
and challenges of applying automatic speech recognition in air traffic
control. To provide this overview, we present an updated literature
review of speech recognition technologies in general, as well as
specific approaches relevant to the ATC context. Based on this
literature review, criteria for selecting speech recognition approaches
for the ATC domain are presented, and remaining challenges and
possible solutions are discussed.
Abstract: In this article, we deal with a variant of the classical
course timetabling problem that has a practical application in many
areas of education. In particular, in this paper we are interested in
high schools remedial courses. The purpose of such courses is to
provide under-prepared students with the skills necessary to succeed
in their studies. In particular, a student might be under prepared in
an entire course, or only in a part of it. The limited availability
of funds, as well as the limited amount of time and teachers at
disposal, often requires schools to choose which courses and/or which
teaching units to activate. Thus, schools need to model the training
offer and the related timetabling, with the goal of ensuring the
highest possible teaching quality, by meeting the above-mentioned
financial, time and resources constraints. Moreover, there are some
prerequisites between the teaching units that must be satisfied. We
first present a Mixed-Integer Programming (MIP) model to solve
this problem to optimality. However, the presence of many peculiar
constraints contributes inevitably in increasing the complexity of
the mathematical model. Thus, solving it through a general-purpose
solver may be performed for small instances only, while solving
real-life-sized instances of such model requires specific techniques
or heuristic approaches. For this purpose, we also propose a heuristic
approach, in which we make use of a fast constructive procedure
to obtain a feasible solution. To assess our exact and heuristic
approaches we perform extensive computational results on both
real-life instances (obtained from a high school in Lecce, Italy) and
randomly generated instances. Our tests show that the MIP model is
never solved to optimality, with an average optimality gap of 57%.
On the other hand, the heuristic algorithm is much faster (in about the
50% of the considered instances it converges in approximately half of
the time limit) and in many cases allows achieving an improvement
on the objective function value obtained by the MIP model. Such an
improvement ranges between 18% and 66%.
Abstract: HR is a department that enhances the power of
employee performance in regard with their services, and to make the
organization strategic objectives. The main concern of HR
department is to organize people, focus on policies and their system.
The empirical study shows the relationship between HRM (Human
Resource Management practices) and their Job Satisfaction. The
Hypothesis is testing on a sample of overall 320 employees of 5
different Pharmaceutical departments of different organizations in
Pakistan. The important thing as Relationship of Job satisfaction with
HR Practices, Impact on Job Satisfaction with HR Practices,
Participation of Staff of Different Departments, HR Practices effects
the Job satisfaction, Recruitment or Hiring and Selection effects the
Job satisfaction, Training and Development, Performance and
Appraisals, Compensation affects the Job satisfaction , and Industrial
Relationships affects the Job satisfaction. After finishing all data
analysis, the conclusion is that lots of Job related activities raise the
confidence of Job satisfaction of employees with their salary and
other benefits.
Abstract: Nowadays, several research studies point up that an
active lifestyle is essential for physical and mental health benefits.
Mobile phones have greatly influenced people’s habits and attitudes
also in the way they exercise. Our research work is mainly focused on
investigating how to exploit mobile technologies to favour people’s
exertion experience. To this end, we developed an exertion framework
users can exploit through a real world mobile application, called
EverywhereSport Run (EWRun), designed to act as a virtual personal
trainer to support runners during their trainings. In this work, inspired
by both previous findings in the field of interaction design for people
with visual impairments, feedback gathered from real users of our
framework, and positive results obtained from two experimentations,
we present some new interaction facilities we designed to enhance
the interaction experience during a training. The positive obtained
results helped us to derive some interaction design recommendations
we believe will be a valid support for designers of future mobile
systems conceived to be used in circumstances where there are limited
possibilities of interaction.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: This study compares the intensity of game load among
player positions and between the 1st and the 2nd half of the games.
Two guards, three forwards, and three centers (female basketball
players) participated in this study. The heart rate (HR) and its
development were monitored during two competitive games.
Statistically insignificant differences in the intensity of game load
were recorded between guards, forwards, and centers below and
above 85% of the maximal heart rate (HRmax) and in the mean HR as
% of HRmax (87.81±3.79%, 87.02±4.37%, and 88.76±3.54%,
respectively). Moreover, when the 1st and the 2nd half of the games
were compared in the mean HR (87.89±4.18% vs. 88.14±3.63% of
HRmax), no statistical significance was recorded. This information can
be useful for coaching staff, to manage and to precisely plan the
training process.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: This paper presents results of compressive strength,
capillary water absorption, and density tests conducted on concrete
containing recycled aggregate (RCA) which is obtained from
structural waste generated by the construction industry in Turkey. In
the experiments, 0%, 15%, 30%, 45% and 60% of the normal
(natural) coarse aggregate was replaced by the recycled aggregate.
Maximum aggregate particle sizes were selected as 16 mm, 22,4 mm
and 31,5 mm; and 0,06%, 0,13% and 0,20% of air-entraining agent
(AEA) were used in mixtures. Fly ash and superplasticizer were used
as a mineral and chemical admixture, respectively. The same type
(CEM I 42.5) and constant dosage of cement were used in the study.
Water/cement ratio was kept constant as 0.53 for all mixture. It was
concluded that capillary water absorption, compressive strength, and
density of concrete decreased with increasing RCA ratio. Increasing
in maximum aggregate particle size and amount of AEA also affect
the properties of concrete significantly.
Abstract: This paper presents an application of Artificial Neural
Network (ANN) algorithm for improving power system voltage
stability. The training data is obtained by solving several normal and
abnormal conditions using the Linear Programming technique. The
selected objective function gives minimum deviation of the reactive
power control variables, which leads to the maximization of
minimum Eigen value of load flow Jacobian. The considered reactive
power control variables are switchable VAR compensators, OLTC
transformers and excitation of generators. The method has been
implemented on a modified IEEE 30-bus test system. The results
obtain from the test clearly show that the trained neural network is
capable of improving the voltage stability in power system with a
high level of precision and speed.
Abstract: Total Quality Management (TQM) refers to management methods used to enhance quality and productivity in business organizations. Total Quality Management (TQM) has become a frequently used term in discussions concerning quality. Total Quality management has brought rise in demands on the organizations policy and the customers have gained more importance in the organizations focus. TQM is considered as an important management tool, which helps the organizations to satisfy their customers. In present research critical success factors includes management commitment, customer satisfaction, continuous improvement, work culture and environment, supplier quality management, training and development, employee satisfaction and product/process design are studied. A questionnaire is developed to implement these critical success factors in implementation of total quality management in Indian industry. Questionnaires filled by consulting different industrial organizations. Data collected from questionnaires is analyzed by descriptive and importance indexes.
Abstract: In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.
Abstract: The purpose of the study was to find out the effects of
Aquatic and Land plyometric training on selected physical variables
in intercollegiate male handball players. To achieve this purpose of
the study, forty five handball players of Sardar Vallabhbhai National
Institute of Technology, Surat, Gujarat were selected as players at
random and their age ranged between 18 to 21 years. The selected
players were divided into three equal groups of fifteen players each.
Group I underwent Aquatic plyometric training, Group II underwent
Land plyometric training and Group III Control group for three days
per week for twelve weeks. Control Group did not participate in any
special training programme apart from their regular activities as per
their curriculum. The following physical fitness variables namely
speed; leg explosive power and agility were selected as dependent
variables. All the players of three groups were tested on selected
dependent variables prior to and immediately after the training
programme. The analysis of covariance was used to analyze the
significant difference, if any among the groups. Since, three groups
were compared, whenever the obtained ‘F’ ratio for adjusted posttest
was found to be significant, the Scheffe’s test to find out the paired
mean differences, if any. The 0.05 level of confidence was fixed as
the level of significance to test the ‘F’ ratio obtained by the analysis
of covariance, which was considered as an appropriate. The result of
the study indicates due to Aquatic and Land plyometric training on
speed, explosive power, and agility has been improved significantly.
Abstract: Stress of slaughter animals starting long before until at the time of process of slaughtering which cause misery and decrease of meat quality. Meanwhile, determination of animal stress using hormonal such as cortisol is expensive and less practical so that portable stress indicator for cows based on Fourier Transform Infrared Spectroscopy (FTIR) must be provided. The aims of this research are to find out the comparison process of slaughter between Rope Casting Local (RCL) and Restraining Box Method (RBM) by measuring of cortisol and wavelength in FTIR methods. Thirty two of male Ongole crossbred cattle were used in this experiment. Blood sampling was taken from jugular vein when they were rested and repeated when slaughtered. All of blood samples were centrifuged at 3000 rpm for 20 minutes to get serum, and then divided into two parts for cortisol assayed using ELISA and for measuring the wavelength using FTIR. The serum then measured at the wavelength between 4000-400 cm-1 using MB3000 FTIR. Band data absorption in wavelength of FTIR is analyzed descriptively by using FTIR Horizon MBTM. For RCL, average of serum cortisol when the animals rested were 11.47 ± 4.88 ng/mL, when the time of slaughter were 23.27 ± 7.84 ng/mL. For RBM, level of cortisol when rested animals were 13.67 ± 3.41 ng/mL and 53.47 ± 20.25 ng/mL during the slaughter. Based on student t-Test, there were significantly different between RBM and RCL methods when beef cattle were slaughtered (P0.05). Result of FTIR with the various of wavelength such as methyl group (=CH3 ) 2986cm-1, methylene (=CH2 ) 2827 cm-1, hydroxyl (- OH) 3371 cm-1, carbonyl (ketones) (C=O) 1636 cm-1, carboxyl (COO-1) 1408 cm-1, glucosa 1057 cm-1, urea 1011 cm-1have been obtained. It can be concluded that the RCL slaughtered method is better than the RBM method based on the increase of cortisol as an indicator of stress in beef cattle (P
Abstract: The research was conducted in order to determine the
organizational socialization levels of nurses working in hospitals in
the form of a descriptive study.
The research population was composed of nurses employed in
public and private sector hospitals in the province of Konya with 0-3
years of professional experience in the hospitals (N=1200); and the
sample was composed of 495 nurses that accepted to take part in the
study voluntarily. Statistical evaluation of data was conducted in
SPSS.16 software.
The results of the study revealed that the total score taken by
nurses at the organizational socialization scale was 262.95; and this
was close to the maximum score. Particularly the departmental
socialization sub-dimension proved to be higher in comparison to the
other two dimensions (organization socialization and task
socialization). Statistically meaningful differences were found in the
levels of organization socialization in relation to the status of
organizational orientation training, level of education and age group.