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: The paper identifies the features of Polish sports clubs
in the particular organizational forms: profit and nonprofit.
Identification and description of these features is carried out in terms
of financial efficiency of the given organizational form. Under the
terms of the efficiency the research allows you to specify the
advantages of particular organizational sports club form and the
following limitations. Paper considers features of sports clubs in
range of Polish conditions as legal regulations. The sources of the
functioning efficiency of sports clubs may lie in the organizational
forms in which they operate. Each of the available forms can be
considered either a for-profit or nonprofit enterprise. Depending on
this classification there are different capabilities of increasing
organizational and financial efficiency of a given sports club. Authors
start with general classification and difference between for-profit and
non-profit sport clubs. Next identifies specific financial and
organizational conditions of both organizational form and then show
examples of mixed activity forms and their efficiency effect.
Abstract: As a by-product of the biodiesel industries, glycerol
has been vastly generated which surpasses the market demand. It is
imperative to develop an efficient glycerol valorization processes in
minimizing the net energy requirement and intensifying the biodiesel
production. In this study, base-catalyzed transesterification of
glycerol with dimethyl carbonate using microwave irradiation as
heating method to produce glycerol carbonate was conducted by
varying grades of glycerol, i.e. 70%, 86% and 99% purity, that is
obtained from biodiesel plant. Metal oxide catalysts were used with
varying operating parameters including reaction time, DMC/glycerol
molar ratio, catalyst weight %, temperature and stirring speed. From
the study on the effect of different operating parameters it was found
that the type of catalyst used has the most significant effect on the
transesterification reaction. Amidst the metal oxide catalysts
examined, CaO gave the best performance. This study indicates the
feasibility of producing glycerol carbonate using different grade of
glycerol in both conventional thermal activation and microwave
irradiation with CaO as catalyst. Microwave assisted
transesterification (MAT) of glycerol into glycerol carbonate has
demonstrated itself as an energy efficient route by achieving 94.2%
yield of GC at 65°C, 5 minutes reaction time, 1 wt% CaO and
DMC/glycerol molar ratio of 2. The advantages of MAT
transesterification route has made the direct utilization of bioglycerol
from biodiesel production without the need of purification. This has
marked a more economical and less-energy intensive glycerol
carbonate synthesis route.
Abstract: Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of external carbon sources. The present study investigated the feasibility of Anammox Hybrid Reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. Experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.
Abstract: Objective: Sharing devastating news with patients is
often considered the most difficult task of doctors. This study aimed
to explore patients’ perceptions of receiving bad news including
which features improve the experience and which areas need refining. Methods: A questionnaire was written based on the steps of the
SPIKES model for breaking bad new. 20 patients receiving treatment
for a hematological malignancy completed the questionnaire. Results: Overall, the results are promising as most patients praised
their consultation. ‘Poor’ was more commonly rated by women and
participants aged 45-64. The main differences between the ‘excellent’
and ‘poor’ consultations include the doctor’s sensitivity and checking
the patients’ understanding. Only 35% of patients were asked their
existing knowledge and 85% of consultations failed to discuss the
impact of the diagnosis on daily life. Conclusion: This study agreed with the consensus of existing
literature. The commended aspects include consultation set-up and
information given. Areas patients felt needed improvement include
doctors determining the patient’s existing knowledge and checking
new information has been understood. Doctors should also explore
how the diagnosis will affect the patient’s life. With a poorer
prognosis, doctors should work on conveying appropriate hope. The
study was limited by a small sample size and potential recall bias.
Abstract: It is the patient compliance and stability in
combination with controlled drug delivery and biocompatibility that
forms the core feature in present research and development of
sustained biodegradable patch formulation intended for wound
healing. The aim was to impart sustained degradation, sterile
formulation, significant folding endurance, elasticity,
biodegradability, bio-acceptability and strength. The optimized
formulation comprised of polymers including Hydroxypropyl methyl
cellulose, Ethylcellulose, and Gelatin, and Citric Acid PEG Citric
acid (CPEGC) triblock dendrimers and active Curcumin. Polymeric
mixture dissolved in geometric order in suitable medium through
continuous stirring under ambient conditions. With continued stirring
Curcumin was added with aid of DCM and Methanol in optimized
ratio to get homogenous dispersion. The dispersion was sonicated
with optimum frequency and for given time and later casted to form a
patch form. All steps were carried out under strict aseptic conditions.
The formulations obtained in the acceptable working range were
decided based on thickness, uniformity of drug content, smooth
texture and flexibility and brittleness. The patch kept on stability
using butter paper in sterile pack displayed folding endurance in
range of 20 to 23 times without any evidence of crack in an
optimized formulation at room temperature (RT) (24 ± 2°C). The
patch displayed acceptable parameters after stability study conducted
in refrigerated conditions (8±0.2°C) and at RT (24 ± 2°C) up to 90
days. Further, no significant changes were observed in critical
parameters such as elasticity, biodegradability, drug release and drug
content during stability study conducted at RT 24±2°C for 45 and 90
days. The drug content was in range 95 to 102%, moisture content
didn’t exceeded 19.2% and patch passed the content uniformity test.
Percentage cumulative drug release was found to be 80% in 12h and
matched the biodegradation rate as drug release with correlation
factor R2>0.9. The biodegradable patch based formulation developed
shows promising results in terms of stability and release profiles.
Abstract: This paper introduces a method to optimal design of a
hybrid Wind/Photovoltaic/Fuel cell generation system for a typical
domestic load that is not located near the electricity grid. In this
configuration the combination of a battery, an electrolyser, and a
hydrogen storage tank are used as the energy storage system. The aim
of this design is minimization of overall cost of generation scheme
over 20 years of operation. The Matlab/Simulink is applied for
choosing the appropriate structure and the optimization of system
sizing. A teaching learning based optimization is used to optimize the
cost function. An overall power management strategy is designed for
the proposed system to manage power flows among the different
energy sources and the storage unit in the system. The results have
been analyzed in terms of technical and economic. The simulation
results indicate that the proposed hybrid system would be a feasible
solution for stand-alone applications at remote locations.
Abstract: In this paper numerical studies have been carried out
to examine the pre-ignition flow features of high-performance solid
propellant rocket motors with two different port geometries but with
same propellant loading density. Numerical computations have been
carried out using a validated 3D, unsteady, 2nd-order implicit, SST k-
ω turbulence model. In the numerical study, a fully implicit finite
volume scheme of the compressible, Reynolds-Averaged, Navier-
Stokes equations is employed. We have observed from the numerical
results that in solid rocket motors with highly loaded propellants
having divergent port geometry the hot igniter gases can create preignition
pressure oscillations leading to thrust oscillations due to the
flow unsteadiness and recirculation. We have also observed that the
igniter temperature fluctuations are diminished rapidly thereby
reaching the steady state value faster in the case of solid propellant
rocket motors with convergent port than the divergent port
irrespective of the igniter total pressure. We have concluded that the
prudent selection of the port geometry, without altering the propellant
loading density, for damping the total temperature fluctuations within
the motor is a meaningful objective for the suppression and control of
instability and/or thrust oscillations often observed in solid propellant
rocket motors with non-uniform port geometry.
Abstract: The aim of study was to analyze the functioning the
new model of criminal corporate responsibility in Poland. The need
to introduce into the Polish legal system liability of corporate
(collective entities) has resulted, among others, from the Polish
Republic's international commitments, in particular related to
membership in the European Union. The study showed that responsibility of collective entities under
the Act has a criminal nature. The main question concerns the ability
of the collective entity to be brought to guilt under criminal law
sense. Polish criminal law knows only the responsibility of individual
persons. So far, guilt as a personal feature of action, based on the
ability of the offender to feel in his psyche, could be considered only
in relation to the individual person, while the said Act destroyed this
conviction. Guilt of collective entity must be proven under at least
one of the three possible forms: the guilt in the selection or
supervision and so called organizational guilt. In addition, research in
article has resolved the issue how the principle of proportionality in
relation to criminal measures in response of collective entities should
be considered. It should be remembered that the legal subjectivity of
collective entities, including their rights and freedoms, is an
emanation of the rights and freedoms of individual persons which
create collective entities and through these entities implement their
rights and freedoms. The whole study was proved that the adopted Act largely reflects
the international legal regulations but also contains the unknown and
original legislative solutions.
Abstract: As smartphones are equipped with various sensors,
there have been many studies focused on using these sensors to create
valuable applications. Human activity recognition is one such
application motivated by various welfare applications, such as the
support for the elderly, measurement of calorie consumption, lifestyle
and exercise patterns analyses, and so on. One of the challenges one
faces when using smartphone sensors for activity recognition is that
the number of sensors should be minimized to save battery power. In
this paper, we show that a fairly accurate classifier can be built that
can distinguish ten different activities by using only a single sensor
data, i.e., the smartphone accelerometer data. The approach that we
adopt to deal with this twelve-class problem uses various methods.
The features used for classifying these activities include not only the
magnitude of acceleration vector at each time point, but also the
maximum, the minimum, and the standard deviation of vector
magnitude within a time window. The experiments compared the
performance of four kinds of basic multi-class classifiers and the
performance of four kinds of ensemble learning methods based on
three kinds of basic multi-class classifiers. The results show that
while the method with the highest accuracy is ECOC based on
Random forest.
Abstract: In this paper, monitoring and control of tap changer
mechanism of a transformer implementation in an Intelligent
Electronic Device (IED) is discussed. It has been a custom for
decades to provide a separate panel for on load tap changer control
for monitoring the tap position. However, this facility cannot either
record or transfer the information to remote control centers. As there
is a technology shift towards the smart grid protection and control
standards, the need for implementing remote control and monitoring
has necessitated the implementation of this feature in numerical
relays. This paper deals with the programming, settings and logic
implementation which is applicable to both IEC 61850 compatible
and non-compatible IEDs thereby eliminating the need for separate
tap changer control equipment. The monitoring mechanism has been
implemented in a 28MVA, 110 /6.9kV transformer with 16 tap
position with GE make T60 IED at Ultratech cement limited
Gulbarga, Karnataka and is in successful service.
Abstract: This work is on decision tree-based classification for
the disbursement of scholarship. Tree-based data mining
classification technique is used in other to determine the generic rule
to be used to disburse the scholarship. The system based on the
defined rules from the tree is able to determine the class (status) to
which an applicant shall belong whether Granted or Not Granted. The
applicants that fall to the class of granted denote a successful
acquirement of scholarship while those in not granted class are
unsuccessful in the scheme. An algorithm that can be used to classify
the applicants based on the rules from tree-based classification was
also developed. The tree-based classification is adopted because of its
efficiency, effectiveness, and easy to comprehend features. The
system was tested with the data of National Information Technology
Development Agency (NITDA) Abuja, a Parastatal of Federal
Ministry of Communication Technology that is mandated to develop
and regulate information technology in Nigeria. The system was
found working according to the specification. It is therefore
recommended for all scholarship disbursement organizations.
Abstract: Computer aided diagnosis systems provide vital
opinion to radiologists in the detection of early signs of breast cancer
from mammogram images. Architectural distortions, masses and
microcalcifications are the major abnormalities. In this paper, a
computer aided diagnosis system has been proposed for
distinguishing abnormal mammograms with architectural distortion
from normal mammogram. Four types of texture features GLCM
texture, GLRLM texture, fractal texture and spectral texture features
for the regions of suspicion are extracted. Support vector machine
has been used as classifier in this study. The proposed system yielded
an overall sensitivity of 96.47% and an accuracy of 96% for
mammogram images collected from digital database for screening
mammography database.
Abstract: Batch production plants provide a wide range of
scheduling problems. In pharmaceutical industries a batch process
is usually described by a recipe, consisting of an ordering of tasks
to produce the desired product. In this research work we focused
on pharmaceutical production processes requiring the culture of
a microorganism population (i.e. bacteria, yeasts or antibiotics).
Several sources of uncertainty may influence the yield of the culture
processes, including (i) low performance and quality of the cultured
microorganism population or (ii) microbial contamination. For
these reasons, robustness is a valuable property for the considered
application context. In particular, a robust schedule will not collapse
immediately when a cell of microorganisms has to be thrown away
due to a microbial contamination. Indeed, a robust schedule should
change locally in small proportions and the overall performance
measure (i.e. makespan, lateness) should change a little if at all.
In this research work we formulated a constraint programming
optimization (COP) model for the robust planning of antibiotics
production. We developed a discrete-time model with a multi-criteria
objective, ordering the different criteria and performing a
lexicographic optimization. A feasible solution of the proposed
COP model is a schedule of a given set of tasks onto available
resources. The schedule has to satisfy tasks precedence constraints,
resource capacity constraints and time constraints. In particular
time constraints model tasks duedates and resource availability
time windows constraints. To improve the schedule robustness, we
modeled the concept of (a, b) super-solutions, where (a, b) are input
parameters of the COP model. An (a, b) super-solution is one in
which if a variables (i.e. the completion times of a culture tasks)
lose their values (i.e. cultures are contaminated), the solution can be
repaired by assigning these variables values with a new values (i.e.
the completion times of a backup culture tasks) and at most b other
variables (i.e. delaying the completion of at most b other tasks).
The efficiency and applicability of the proposed model is
demonstrated by solving instances taken from a real-life
pharmaceutical company. Computational results showed that
the determined super-solutions are near-optimal.
Abstract: One of the most critical decision points in the design of a
face recognition system is the choice of an appropriate face representation.
Effective feature descriptors are expected to convey sufficient, invariant
and non-redundant facial information. In this work we propose a set of
Hahn moments as a new approach for feature description. Hahn moments
have been widely used in image analysis due to their invariance, nonredundancy
and the ability to extract features either globally and locally.
To assess the applicability of Hahn moments to Face Recognition we
conduct two experiments on the Olivetti Research Laboratory (ORL)
database and University of Notre-Dame (UND) X1 biometric collection.
Fusion of the global features along with the features from local facial
regions are used as an input for the conventional k-NN classifier. The
method reaches an accuracy of 93% of correctly recognized subjects for
the ORL database and 94% for the UND database.
Abstract: This study integrates a larger research empirical
project that examines second language (SL) learners’ profiles and
valid procedures to perform complete and diagnostic assessment in
schools. 102 learners of Portuguese as a SL aged 7 and 17 years
speakers of distinct home languages were assessed in several
linguistic tasks. In this article, we focused on writing performance in
the specific task of narrative essay composition. The written outputs
were measured using the score in six components adapted from an
English SL assessment context (Alberta Education): linguistic
vocabulary, grammar, syntax, strategy, socio-linguistic, and
discourse. The writing processes and strategies in Portuguese
language used by different immigrant students were analysed to
determine features and diversity of deficits on authentic texts
performed by SL writers. Differentiated performance was based on
the diversity of the following variables: grades, previous schooling,
home language, instruction in first language, and exposure to
Portuguese as Second Language. Indo-Aryan languages speakers
showed low writing scores compared to their peers and the type of
language and respective cognitive mapping (such as Mandarin and
Arabic) was the predictor, not linguistic distance. Home language
instruction should also be prominently considered in further research
to understand specificities of cognitive academic profile in a
Romance languages learning context. Additionally, this study also
examined the teachers’ representations that will be here addressed to
understand educational implications of second language teaching in
psychological distress of different minorities in schools of specific
host countries.
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: This paper deals with nonlinear vibration analysis
using finite element method for frame structures consisting of elastic
and viscoelastic damping layers supported by multiple nonlinear
concentrated springs with hysteresis damping. The frame is supported
by four nonlinear concentrated springs near the four corners. The
restoring forces of the springs have cubic non-linearity and linear
component of the nonlinear springs has complex quantity to represent
linear hysteresis damping. The damping layer of the frame structures
has complex modulus of elasticity. Further, the discretized equations in
physical coordinate are transformed into the nonlinear ordinary
coupled differential equations using normal coordinate corresponding
to linear natural modes. Comparing shares of strain energy of the
elastic frame, the damping layer and the springs, we evaluate the
influences of the damping couplings on the linear and nonlinear impact
responses. We also investigate influences of damping changed by
stiffness of the elastic frame on the nonlinear coupling in the damped
impact responses.
Abstract: A large amount of software products offer a wide
range and number of features. This is called featuritis or creeping
featurism and tends to rise with each release of the product. Feautiris
often adds unnecessary complexity to software, leading to longer
learning curves and overall confusing the users and degrading their
experience. We take a look to a new design approach tendency that
has been coming up, the so-called “What You Get is What You
Need” concept that argues that products should be very focused,
simple and with minimalistic interfaces in order to help users conduct
their tasks in distraction-free ambiences. This isn’t as simple to
implement as it might sound and the developers need to cut down
features. Our contribution illustrates and evaluates this design method
through a novel distraction-free diagramming tool named Delineato
Pro for Mac OS X in which the user is confronted with an empty
canvas when launching the software and where tools only show up
when really needed.
Abstract: In this paper, the problem of stability and stabilization
for neutral delay-differential systems with infinite delay is
investigated. Using Lyapunov method, new delay-independent
sufficient condition for the stability of neutral systems with infinite
delay is obtained in terms of linear matrix inequality (LMI).
Memory-less state feedback controllers are then designed for the
stabilization of the system using the feasible solution of the resulting
LMI, which are easily solved using any optimization algorithms.
Numerical examples are given to illustrate the results of the proposed
methods.