Abstract: A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.
Abstract: Mechanical design of the thin-film solar framed
module and mounting system is important to enhance module
reliability and to increase areas of applications. The stress induced by
different mounting positions played a main role controlling the
stability of the whole mechanical structure. From the finite element
method, under the pressure from the back of module, the stress at Lc
(center point of the Long frame) increased and the stresses at Center,
Corner and Sc (center point of the Short frame) decreased while the
mounting position was away from the center of the module. In addition,
not only the stress of the glass but also the stress of the frame
decreased. Accordingly it was safer to mount in the position away
from the center of the module. The emphasis of designing frame
system of the module was on the upper support of the Short frame.
Strength of the overall structure and design of the corner were also
important due to the complexity of the stress in the Long frame.
Abstract: In this study, we investigated the effects of ginger and
L-carnitine on the reproductive performance of male rats with respect
to semen parameters, male sex hormones and the testicular
antioxidant system. A total of sixty mature male albino rats were
divided into four groups of fifteen rats. The control group received
saline, whereas the other three groups received ginger (100 mg kg-1 d-
1.), L-carnitine (150 mg kg-1 d-1.) or a combination of both ginger
(100 mg kg-1 d-1.) and L-carnitine (150 mg kg-1 d-1.) via a stomach
tube daily for one month. At the end of the treatment period, the rats
were sacrificed, and their sperm characteristics (count, motility and
viability), antioxidant enzyme factors levels (reduced glutathione,
catalase, superoxide dismutase and total antioxidant capacity) and sex
hormone levels (testosterone, Follicle stimulating hormone(FSH) and
luteinizing hormone (LH) were analysed. Our results showed that the
three experimental treatments improved sperm parameters,
antioxidant enzyme activity and testosterone hormone levels; the
most pronounced positive effects were observed in the group that
received a combination of both ginger and L-carnitine. Therefore, the
administration of a combination of ginger and L-carnitine may be
beneficial for improving male sexual performance.
Abstract: ECG analysis method was developed using ROC
analysis of PVC detecting algorithm. ECG signal of MIT-BIH
arrhythmia database was analyzed by MATLAB. First of all, the
baseline was removed by median filter to preprocess the ECG signal.
R peaks were detected for ECG analysis method, and normal VCG
was extracted for VCG analysis method. Four PVC detecting
algorithm was analyzed by ROC curve, which parameters are
maximum amplitude of QRS complex, width of QRS complex, r-r
interval and geometric mean of VCG. To set cut-off value of
parameters, ROC curve was estimated by true-positive rate
(sensitivity) and false-positive rate. sensitivity and false negative rate
(specificity) of ROC curve calculated, and ECG was analyzed using
cut-off value which was estimated from ROC curve. As a result, PVC
detecting algorithm of VCG geometric mean have high availability,
and PVC could be detected more accurately with amplitude and width
of QRS complex.
Abstract: Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.
Abstract: In this article an evolutionary technique has been used
for the solution of nonlinear Riccati differential equations of fractional order. In this method, genetic algorithm is used as a tool for
the competent global search method hybridized with active-set algorithm for efficient local search. The proposed method has been
successfully applied to solve the different forms of Riccati
differential equations. The strength of proposed method has in its
equal applicability for the integer order case, as well as, fractional
order case. Comparison of the method has been made with standard
numerical techniques as well as the analytic solutions. It is found
that the designed method can provide the solution to the equation
with better accuracy than its counterpart deterministic approaches.
Another advantage of the given approach is to provide results on
entire finite continuous domain unlike other numerical methods
which provide solutions only on discrete grid of points.
Abstract: We present on the method of inverse coherence matrix for the estimation of network connectivity from multivariate time series of a complex system. In a model system of coupled chaotic oscillators, it is shown that the inverse coherence matrix defined as the inverse of cross coherence matrix is proportional to the network connectivity. Therefore the inverse coherence matrix could be used for the distinction between the directly connected links from indirectly connected links in a complex network. We compare the result of network estimation using the method of the inverse coherence matrix with the results obtained from the coherence matrix and the partial coherence matrix.
Abstract: The present study was done primarily to address two major research gaps: firstly, development of an empirical measure of life meaningfulness for substance users and secondly, to determine the psychosocial determinants of life meaningfulness among the substance users. The study is classified into two phases: the first phase which dealt with development of Life Meaningfulness Scale and the second phase which examined the relationship between life meaningfulness and social support, abstinence self efficacy and depression. Both qualitative and quantitative approaches were used for framing items. A Principal Component Analysis yielded three components: Overall Goal Directedness, Striving for healthy lifestyle and Concern for loved ones which collectively accounted for 42.06% of the total variance. The scale and its subscales were also found to be highly reliable. Multiple regression analyses in the second phase of the study revealed that social support and abstinence self efficacy significantly predicted life meaningfulness among 48 recovering inmates of a de-addiction center while level of depression failed to predict life meaningfulness.
Abstract: Surface metrology with image processing is a challenging task having wide applications in industry. Surface roughness can be evaluated using texture classification approach. Important aspect here is appropriate selection of features that characterize the surface. We propose an effective combination of features for multi-scale and multi-directional analysis of engineering surfaces. The features include standard deviation, kurtosis and the Canny edge detector. We apply the method by analyzing the surfaces with Discrete Wavelet Transform (DWT) and Dual-Tree Complex Wavelet Transform (DT-CWT). We used Canberra distance metric for similarity comparison between the surface classes. Our database includes the surface textures manufactured by three machining processes namely Milling, Casting and Shaping. The comparative study shows that DT-CWT outperforms DWT giving correct classification performance of 91.27% with Canberra distance metric.
Abstract: To satisfy the need of outfield tests of star sensors, a
method is put forward to construct the reference attitude benchmark.
Firstly, its basic principle is introduced; Then, all the separate
conversion matrixes are deduced, which include: the conversion
matrix responsible for the transformation from the Earth Centered
Inertial frame i to the Earth-centered Earth-fixed frame w according to
the time of an atomic clock, the conversion matrix from frame w to the
geographic frame t, and the matrix from frame t to the platform frame
p, so the attitude matrix of the benchmark platform relative to the
frame i can be obtained using all the three matrixes as the
multiplicative factors; Next, the attitude matrix of the star sensor
relative to frame i is got when the mounting matrix from frame p to the
star sensor frame s is calibrated, and the reference attitude angles for
star sensor outfield tests can be calculated from the transformation
from frame i to frame s; Finally, the computer program is finished to
solve the reference attitudes, and the error curves are drawn about the
three axis attitude angles whose absolute maximum error is just 0.25ÔÇ│.
The analysis on each loop and the final simulating results manifest that
the method by precise timing to acquire the absolute reference attitude
is feasible for star sensor outfield tests.
Abstract: The photoluminescence (PL) at 1.55 μm from
semiconducting β-FeSi2 has attracted a noticeable interest for
silicon-based optoelectronic applications. Moreover, its high optical
absorption coefficient (higher than 105 cm-1 above 1.0 eV) allows this
semiconducting material to be used as photovoltanics devices.
A clear PL spectrum for β-FeSi2 was observed by Cu or Au coating
on Si(001). High-crystal-quality β-FeSi2 with a low-level nonradiative
center was formed on a Cu- or Au- reated Si layer. This method of
deposition can be applied to other materials requiring high crystal
quality.
Abstract: Optimal reactive power flow is an optimization problem
with one or more objective of minimizing the active power losses for
fixed generation schedule. The control variables are generator bus
voltages, transformer tap settings and reactive power output of the
compensating devices placed on different bus bars. Biogeography-
Based Optimization (BBO) technique has been applied to solve
different kinds of optimal reactive power flow problems subject
to operational constraints like power balance constraint, line flow
and bus voltages limits etc. BBO searches for the global optimum
mainly through two steps: Migration and Mutation. In the present
work, BBO has been applied to solve the optimal reactive power
flow problems on IEEE 30-bus and standard IEEE 57-bus power
systems for minimization of active power loss. The superiority of the
proposed method has been demonstrated. Considering the quality of
the solution obtained, the proposed method seems to be a promising
one for solving these problems.
Abstract: This research is aimed to compare the percentages of correct classification of Empirical Bayes method (EB) to Classical method when data are constructed as near normal, short-tailed and long-tailed symmetric, short-tailed and long-tailed asymmetric. The study is performed using conjugate prior, normal distribution with known mean and unknown variance. The estimated hyper-parameters obtained from EB method are replaced in the posterior predictive probability and used to predict new observations. Data are generated, consisting of training set and test set with the sample sizes 100, 200 and 500 for the binary classification. The results showed that EB method exhibited an improved performance over Classical method in all situations under study.
Abstract: Planning community has been long discussing emerging paradigms within the planning theory in the face of the changing conditions of the world order. The paradigm shift concept was introduced by Thomas Kuhn, in 1960, who claimed the necessity of shifting within scientific knowledge boundaries; and following him in 1970 Imre Loktas also gave priority to the emergence of multi-paradigm societies [24]. Multi-paradigm is changing our predetermined lifeworld through uncertainties. Those uncertainties are reflected in two sides, the first one is uncertainty as a concept of possibility and creativity in public sphere and the second one is uncertainty as a risk. Therefore, it is necessary to apply a resilience planning approach to be more dynamic in controlling uncertainties which have the potential to transfigure present time and space definitions. In this way, stability of system can be achieved. Uncertainty is not only an outcome of worldwide changes but also a place-specific issue, i.e. it changes from continent to continent, a country to country; a region to region. Therefore, applying strategic spatial planning with respect to resilience principle contributes to: control, grasp and internalize uncertainties through place-specific strategies. In today-s fast changing world, planning system should follow strategic spatial projects to control multi-paradigm societies with adaptability capacities. Here, we have selected two alternatives to demonstrate; these are; 1.Tehran (Iran) from the Middle East 2.Bath (United Kingdom) from Europe. The study elaborates uncertainties and particularities in their strategic spatial planning processes in a comparative manner. Through the comparison, the study aims at assessing place-specific priorities in strategic planning. The approach is to a two-way stream, where the case cities from the extreme end of the spectrum can learn from each other. The structure of this paper is to firstly compare semi-periphery (Tehran) and coreperiphery (Bath) cities, with the focus to reveal how they equip to face with uncertainties according to their geographical locations and local particularities. Secondly, the key message to address is “Each locality requires its own strategic planning approach to be resilient.--
Abstract: In recent years, rapid advances in software and hardware in the field of information technology along with a digital imaging revolution in the medical domain facilitate the generation and storage of large collections of images by hospitals and clinics. To search these large image collections effectively and efficiently poses significant technical challenges, and it raises the necessity of constructing intelligent retrieval systems. Content-based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images[5]. Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes.
Abstract: Electromagnetic interference (EMI) is one of the
serious problems in most electrical and electronic appliances
including fluorescent lamps. The electronic ballast used to regulate
the power flow through the lamp is the major cause for EMI. The
interference is because of the high frequency switching operation of
the ballast. Formerly, some EMI mitigation techniques were in
practice, but they were not satisfactory because of the hardware
complexity in the circuit design, increased parasitic components and
power consumption and so on. The majority of the researchers have
their spotlight only on EMI mitigation without considering the other
constraints such as cost, effective operation of the equipment etc. In
this paper, we propose a technique for EMI mitigation in fluorescent
lamps by integrating Frequency Modulation and Evolutionary
Programming. By the Frequency Modulation technique, the
switching at a single central frequency is extended to a range of
frequencies, and so, the power is distributed throughout the range of
frequencies leading to EMI mitigation. But in order to meet the
operating frequency of the ballast and the operating power of the
fluorescent lamps, an optimal modulation index is necessary for
Frequency Modulation. The optimal modulation index is determined
using Evolutionary Programming. Thereby, the proposed technique
mitigates the EMI to a satisfactory level without disturbing the
operation of the fluorescent lamp.
Abstract: Nonlinear finite element method with eight noded
isoparametric quadrilateral element is used for prediction of loaddeformation
behavior including bearing capacity of foundations.
Modified generalized plasticity model with non-associated flow rule
is applied for analysis of soil-footing system. Also Von Mises and
Tresca criterions are used for simulation of soil behavior. Modified
generalized plasticity model is able to simulate load-deformation
including softening behavior. Localization phenomena are considered
by different meshes. Localization phenomena have not been seen in
the examples. Predictions by modified generalized plasticity model
show good agreement with laboratory data and theoretical prediction
in comparison the other models.
Abstract: The analysis of Acoustic Emission (AE) signal
generated from metal cutting processes has often approached
statistically. This is due to the stochastic nature of the emission
signal as a result of factors effecting the signal from its generation
through transmission and sensing. Different techniques are applied in
this manner, each of which is suitable for certain processes. In metal
cutting where the emission generated by the deformation process is
rather continuous, an appropriate method for analysing the AE signal
based on the root mean square (RMS) of the signal is often used and
is suitable for use with the conventional signal processing systems.
The aim of this paper is to set a strategy in tool failure detection in
turning processes via the statistic analysis of the AE generated from
the cutting zone. The strategy is based on the investigation of the
distribution moments of the AE signal at predetermined sampling.
The skews and kurtosis of these distributions are the key elements in
the detection. A normal (Gaussian) distribution has first been
suggested then this was eliminated due to insufficiency. The so
called Beta distribution was then considered, this has been used with
an assumed β density function and has given promising results with
regard to chipping and tool breakage detection.
Abstract: Erroneous computer entry problems [here: 'e'errors] in hospital labs threaten the patients-–health carers- relationship, undermining the health system credibility. Are e-errors random, and do lab professionals make them accidentally, or may they be traced through meaningful determinants? Theories on internal causality of mistakes compel to seek specific causal ascriptions of hospital lab eerrors instead of accepting some inescapability. Undeniably, 'To Err is Human'. But in view of rapid global health organizational changes, e-errors are too expensive to lack in-depth considerations. Yet, that efunction might supposedly be entrenched in the health carers- job description remains under dispute – at least for Hellenic labs, where e-use falls behind generalized(able) appreciation and application. In this study: i) an empirical basis of a truly high annual cost of e-errors at about €498,000.00 per rural Hellenic hospital was established, hence interest in exploring the issue was sufficiently substantiated; ii) a sample of 270 lab-expert nurses, technicians and doctors were assessed on several personality, burnout and e-error measures, and iii) the hypothesis that the Hardiness vs Alienation personality construct disposition explains resistance vs proclivity to e-errors was tested and verified: Hardiness operates as a resilience source in the encounter of high pressures experienced in the hospital lab, whereas its 'opposite', i.e., Alienation, functions as a predictor, not only of making e-errors, but also of leading to burn-out. Implications for apt interventions are discussed.
Abstract: The adsorption of simulated aqueous solution containing textile remazol reactive dye, namely Red 3BS by palm shell activated carbon (PSAC) as adsorbent was carried out using Response Surface Methodology (RSM). A Box-Behnken design in three most important operating variables; initial dye concentration, dosage of adsorbent and speed of impeller was employed for experimental design and optimization of results. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95% confidence limits. Model indicated that with the increasing of dosage and speed give the result of removal up to 90% with the capacity uptake more than 7 mg/g. High regression coefficient between the variables and the response (R-Sq = 93.9%) showed of good evaluation of experimental data by polynomial regression model.