Abstract: Major depressive disorder (MDD) is one of the most common mental illnesses today. It is believed to be caused by a combination of several factors, including stress. Stress can be quantitatively evaluated using the State-Trait Anxiety Inventory (STAI), one of the best indices to evaluate anxiety. Although STAI scores are widely used in applications ranging from clinical diagnosis to basic research, the scores are calculated based on a self-reported questionnaire. An objective evaluation is required because the subject may intentionally change his/her answers if multiple tests are carried out. In this article, we present a modified index called the “multi-channel Laterality Index at Rest (mc-LIR)” by recording the brain activity from a wider area of the frontal lobe using multi-channel functional near-infrared spectroscopy (fNIRS). The presented index aims to measure multiple positions near the Fpz defined by the international 10-20 system positioning. Using 24 subjects, the dependencies on the number of measuring points used to calculate the mc-LIR and its correlation coefficients with the STAI scores are reported. Furthermore, a simple linear regression was performed to estimate the STAI scores from mc-LIR. The cross-validation error is also reported. The experimental results show that using multiple positions near the Fpz will improve the correlation coefficients and estimation than those using only two positions.
Abstract: In this work, efficient directional coupler composed of
dielectric waveguides and metallic film has been analyzed in details
by simulations using finite element method (FEM). The structure
consists of a step-index fiber with dielectric core, silica cladding, and
a metal nanowire parallel to the core. The results show that an
efficient conversion of optical dielectric modes to long range
plasmonic is possible. Low insertion losses in conjunction with short
coupling length and a broadband operation can be achieved under
certain conditions. This kind of couplers has potential applications for
the design of photonic integrated circuits for signal routing between
dielectric/plasmonic waveguides, sensing, lithography, and optical
storage systems. A high efficient focusing of light in a very small
region can be obtained.
Abstract: With the development of HyperSpectral Imagery
(HSI) technology, the spectral resolution of HSI became denser,
which resulted in large number of spectral bands, high correlation
between neighboring, and high data redundancy. However, the
semantic interpretation is a challenging task for HSI analysis
due to the high dimensionality and the high correlation of the
different spectral bands. In fact, this work presents a dimensionality
reduction approach that allows to overcome the different issues
improving the semantic interpretation of HSI. Therefore, in order
to preserve the spatial information, the Tensor Locality Preserving
Projection (TLPP) has been applied to transform the original HSI.
In the second step, knowledge has been extracted based on the
adjacency graph to describe the different pixels. Based on the
transformation matrix using TLPP, a weighted matrix has been
constructed to rank the different spectral bands based on their
contribution score. Thus, the relevant bands have been adaptively
selected based on the weighted matrix. The performance of the
presented approach has been validated by implementing several
experiments, and the obtained results demonstrate the efficiency
of this approach compared to various existing dimensionality
reduction techniques. Also, according to the experimental results,
we can conclude that this approach can adaptively select the
relevant spectral improving the semantic interpretation of HSI.
Abstract: This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.
Abstract: Air pollution both from point and non-point sources is difficult to control once released in to the atmosphere. There is no engineering method known available to ameliorate the dispersed pollutants. The only suitable approach is the ecological method of constructing green belts in and around the pollution sources. Air pollution in Muscat, Oman is a serious concern due to ever increasing vehicles on roads. Identifying the air pollution tolerance levels of species is important for implementing pollution control strategies in the urban areas of Muscat. Hence, in the present study, Air Pollution Tolerance Index (APTI) for ten avenue tree species was evaluated by analyzing four bio-chemical parameters, plus their Anticipated Performance Index (API) in field conditions. Based on the two indices, Ficus benghalensis was the most suitable one with the highest performance score. Conocarpus erectuse, Phoenix dactylifera, and Pithcellobium dulce were found to be good performers and are recommended for extensive planting. Azadirachta indica which is preferred for its dense canopy is qualified in the moderate category. The rest of the tree species expressed lower API score of less than 51, hence cannot be considered as suitable species for pollution mitigation plantation projects.
Abstract: Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.
Abstract: This work investigates upsetting of the tri-metallic cylindrical billets both experimentally and analytically with a reduction ratio 30%. Steel, brass, and copper are used for the outer and outmost rings and aluminum for the inner core. Two different models have been designed to show material flow and the cavity took place over the two interfaces during forming after this reduction ratio. Each model has an outmost ring material as steel. Model 1 has an outer ring between the outmost ring and the solid core material as copper and Model 2 has a material as brass. Solid core is aluminum for each model. Billets were upset in press machine by using parallel flat dies. Upsetting load was recorded and compared for models and single billets. To extend the tests and compare with experimental procedure to a wider range of inner core and outer ring geometries, finite element model was performed. ABAQUS software was used for the simulations. The aim is to show how contact between outmost ring, outer ring and the inner core are carried on throughout the upsetting process. Results have shown that, with changing in height, between outmost ring, outer ring and inner core, the Model 1 and Model 2 had very good interaction, and the contact surfaces of models had various interface behaviour. It is also observed that tri-metallic materials have lower weight but better mechanical properties than single materials. This can give an idea for using and producing these new materials for different purposes.
Abstract: By the development of World Wide Web, the usage rate of Internet has rapidly grown globally; and provided a basis for the emergence of electronic business. As well as other sectors, the banking sector has adopted the use of internet with the developments in information and communication technologies. Due to the public disclosure and transparency principle of Corporate Governance, the importance of information disclosure of banks on their web sites has increased significantly. For the purpose of this study, a Bank Disclosure Attribute Index (BDAI) in Turkey has been constructed through classifying the information disclosure on banks’ web sites into general, financial, investors and corporate governance attributes. All 47 banks in Turkish Banking System have been evaluated according to the index with the aim of providing a comparison between banks. By Chi Square Test, Pearson Correlation, T-Test, and ANOVA statistical tools, it has been concluded that the majority of banks in Turkey have shared information on their web sites adequately with respect to their total index score. Although there is a positive correlation between various types of information on banks’ web sites, there is no uniformity among them. Also, no significant difference between various types of information disclosure and bank types has been observed. Compared with the total index score averages of the five largest banks in Turkey, there are some banks that need to improve the content of their web sites.
Abstract: With advancements in science and technology, the concept of the Internet of Things (IoT) has gradually developed. The development of the intelligent environment adds intelligence to objects in the living space by using the IoT. In the smart environment, when multiple users share the living space, if different service requirements from different users arise, then the context-aware system will have conflicting situations for making decisions about providing services. Therefore, the purpose of establishing a communication and negotiation mechanism among objects in the intelligent environment is to resolve those service conflicts among users. This study proposes developing a decision-making methodology that uses “Event Agents” as its core. When the sensor system receives information, it evaluates a user’s current events and conditions; analyses object, location, time, and environmental information; calculates the priority of the object; and provides the user services based on the event. Moreover, when the event is not single but overlaps with another, conflicts arise. This study adopts the “Multiple Events Correlation Matrix” in order to calculate the degree values of incidents and support values for each object. The matrix uses these values as the basis for making inferences for system service, and to further determine appropriate services when there is a conflict.
Abstract: Glass Fiber Reinforced Polymer (GFRP) is a major evolution for energy dissipation when used as infill material for seismic retrofitting of steel frame, a basic PMC infill wall system consists of two GFRP laminates surrounding an infill of foam core. This paper presents numerical analysis in terms of buckling resistance of GFRP sandwich infill panels system under the influence of environment temperature and stacking sequence of laminate skin. Mode of failure under in-plane compression is studied by means of numerical analysis with ABAQUS platform. Parameters considered in this study are contact length between infill and frame, laminate stacking sequence of GFRP skin and variation of mechanical properties due to increment of temperature. The analysis is done with four cases of simple stacking sequence over a range of temperature. The result showed that both the effect of temperature and stacking sequence alter the performance of entire panel system. The rises of temperature resulted in the decrements of the panel’s strength. This is due to the polymeric nature of this material. Additionally, the contact length also displays the effect on the performance of infill panel. Furthermore, the laminate stiffness can be modified by orientation of laminate, which can increase the infill panel strength. Hence, optimal performance of the entire panel system can be obtained by comparing different cases of stacking sequence.
Abstract: As DNA microarray data contain relatively small
sample size compared to the number of genes, high dimensional
models are often employed. In high dimensional models, the selection
of tuning parameter (or, penalty parameter) is often one of the crucial
parts of the modeling. Cross-validation is one of the most common
methods for the tuning parameter selection, which selects a parameter
value with the smallest cross-validated score. However, selecting a
single value as an ‘optimal’ value for the parameter can be very
unstable due to the sampling variation since the sample sizes of
microarray data are often small. Our approach is to choose multiple candidates of tuning parameter
first, then average the candidates with different weights depending
on their performance. The additional step of estimating the weights
and averaging the candidates rarely increase the computational cost,
while it can considerably improve the traditional cross-validation. We
show that the selected value from the suggested methods often lead to
stable parameter selection as well as improved detection of significant
genetic variables compared to the tradition cross-validation via real
data and simulated data sets.
Abstract: Due to its high computational cost, mutation testing has been neglected by researchers. Recently, many cost and mutants’ reduction techniques have been developed, improved, and experimented, but few of them has relied the possibility of reducing the cost of mutation testing on the program type of the application under test. This paper is a comparative study between four operators’ selection techniques (mutants sampling, class level operators, method level operators, and all operators’ selection) based on the program code type of each application under test. It aims at finding an alternative approach to reveal the effect of code type on mutation testing score. The result of our experiment shows that the program code type can affect the mutation score and that the programs using polymorphism are best suited to be tested with mutation testing.
Abstract: At present, application of the extension of soft set theory in decision making problems in day to day life is progressing rapidly. The concepts of fuzzy soft set and its properties have been evolved as an area of interest for the researchers. The generalization of the concepts recently got importance and a rapid growth in the research in this area witnessed its vital-ness. In this paper, an application of the concept of generalized fuzzy soft set to make decision in a social problem is presented. Further, this paper also highlights some of the key issues of the related areas.
Abstract: Multiple Sclerosis (MS) is a disease which affects the
central nervous system and causes balance problem. In clinical, this
disorder is usually evaluated using static posturography. Some linear
or nonlinear measures, extracted from the posturographic data (i.e.
center of pressure, COP) recorded during a balance test, has been
used to analyze postural control of MS patients. In this study, the
trend (TREND) and the sample entropy (SampEn), two nonlinear
parameters were chosen to investigate their relationships with the
expanded disability status scale (EDSS) score. 40 volunteers with
different EDSS scores participated in our experiments with eyes open
(EO) and closed (EC). TREND and 2 types of SampEn (SampEn1
and SampEn2) were calculated for each combined COP’s position
signal. The results have shown that TREND had a weak negative
correlation to EDSS while SampEn2 had a strong positive correlation
to EDSS. Compared to TREND and SampEn1, SampEn2 showed a
better significant correlation to EDSS and an ability to discriminate
the MS patients in the EC case. In addition, the outcome of the study
suggests that the multi-dimensional nonlinear analysis could provide
some information about the impact of disability progression in MS on
dynamics of the COP data.
Abstract: This paper presents numerical analysis in terms of
buckling resistance of GFRP sandwich infill panels system under the
influence of increased temperature on the foam core. Failure mode
under in-plane compression is studied by means of numerical analysis
with ABAQUS platform. Parameters considered in this study are
contact length and both the type of foam for core and the variation of
its module elastic under the thermal influence. Increment of
temperature is considered in static cases and only applied to core.
Indeed, it is proven that the effect of temperature alters the mechanical
properties of the entire panel system. Moreover, the rises of
temperature result in a decrease in strength of the panel. This is due to
the polymeric nature of this material. Additionally, the contact length
also displays the effect on performance of infill panel. Their
significance factors are based on type of polymer for core. Therefore,
by comparing difference type of core material, the variation can be
reducing.
Abstract: Current study established for EEG signal analysis in
patients with language disorder. Language disorder can be defined as
meaningful delay in the use or understanding of spoken or written
language. The disorder can include the content or meaning of
language, its form, or its use. Here we applied Z-score, power
spectrum, and coherence methods to discriminate the language
disorder data from healthy ones. Power spectrum of each channel in
alpha, beta, gamma, delta, and theta frequency bands was measured.
In addition, intra hemispheric Z-score obtained by scoring algorithm.
Obtained results showed high Z-score and power spectrum in
posterior regions. Therefore, we can conclude that peoples with
language disorder have high brain activity in frontal region of brain
in comparison with healthy peoples. Results showed that high coherence correlates with irregularities
in the ERP and is often found during complex task, whereas low
coherence is often found in pathological conditions. The results of the
Z-score analysis of the brain dynamics showed higher Z-score peak
frequency in delta, theta and beta sub bands of Language Disorder
patients. In this analysis there were activity signs in both hemispheres
and the left-dominant hemisphere was more active than the right.
Abstract: In recent years, honeycomb fiber reinforced plastic
(FRP) sandwich panels have been increasingly used in various
industries. Low weight, low price and high mechanical strength are
the benefits of these structures. However, their mechanical properties
and behavior have not been fully explored. The objective of this
study is to conduct a combined numerical-statistical investigation of
honeycomb FRP sandwich beams subject to torsion load. In this
paper, the effect of geometric parameters of sandwich panel on
maximum shear strain in both face and core and angle of torsion in a
honeycomb FRP sandwich structures in torsion is investigated. The
effect of Parameters including core thickness, face skin thickness,
cell shape, cell size, and cell thickness on mechanical behavior of the
structure were numerically investigated. Main effects of factors were
considered in this paper and regression equations were derived.
Taguchi method was employed as experimental design and an
optimum parameter combination for the maximum structure stiffness
has been obtained. The results showed that cell size and face skin
thickness have the most significant impacts on torsion angle,
maximum shear strain in face and core.
Abstract: Adopting Most Advantageous Tender (MAT) for the
government procurement projects has become popular in Taiwan. As
time pass by, the problems of MAT has appeared gradually. People
condemn two points that are the result might be manipulated by a
single committee member’s partiality and how to make a fair decision
when the winner has two or more. Arrow’s Impossibility Theorem
proposed that the best scoring method should meet the four reasonable
criteria. According to these four criteria this paper constructed an
“Illegitimate Scores Checking Scheme” for a scoring method and used
the scheme to find out the illegitimate of the current evaluation method
of MAT. This paper also proposed a new scoring method that is called
the “Standardizing Overall Evaluated Score Method”. This method
makes each committee member’s influence tend to be identical. Thus,
the committee members can scoring freely according to their partiality
without losing the fairness. Finally, it was examined by a large-scale
simulation, and the experiment revealed that the it improved the
problem of dictatorship and perfectly avoided the situation of cyclical
majorities, simultaneously. This result verified that the Standardizing
Overall Evaluated Score Method is better than any current evaluation
method of MAT.
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.
Abstract: Background: The objectives of this study were to
assess patient’s knowledge of appropriate sublingual glyceryl
trinitrate (GTN) use as well as to investigate how patients commonly
store and carry their sublingual GTN tablets. Methodology: This was
a cross-sectional survey, using a validated researcher-administered
questionnaire. The study involved cardiac patients receiving
sublingual GTN attending the outpatient and inpatient departments of
Taiping Hospital, a non-academic public care hospital. The minimum
calculated sample size was 92, but 100 patients were conveniently
sampled. Respondents were interviewed on 3 areas, including
demographic data, knowledge and use of sublingual GTN. Eight
items were used to calculate each subject’s knowledge score and six
items were used to calculate use score. Results: Of the 96 patients
who consented to participate, majority (96.9%) were well aware of
the indication of sublingual GTN. With regards to the mechanism of
action of sublingual GTN, 73 (76%) patients did not know how the
medication works. Majority of the patients (66.7%) knew about the
proper storage of the tablet. In relation to the maximum number of
sublingual GTN tablets that can be taken during each angina episode,
36.5% did not know that up to 3 tablets of sublingual GTN can be
taken during each episode of angina. Fifty four (56.2%) patients were
not aware that they need to replace sublingual GTN every 8 weeks
after receiving the tablets. Majority (69.8%) of the patients
demonstrated lack of knowledge with regards to the use of sublingual
GTN as prevention of chest pain. Conclusion: Overall, patients’
knowledge regarding the self-administration of sublingual GTN is
still inadequate. The findings support the need for more frequent
reinforcement of patient education, especially in the areas of
preventive use, storage and drug stability.