Abstract: Some extended rough set models in incomplete information system cannot distinguish the two objects that have few known attributes and more unknown attributes; some cannot make a flexible and accurate discrimination. In order to solve this problem, this paper suggests an improved limited tolerance rough set model using two thresholds to control what two objects have a relationship between them in limited tolerance relation and to classify objects. Our practical study case shows the model can get fine and reasonable decision results.
Abstract: The road environment information is needed accurately for applications such as road maintenance and virtual 3D city modeling. Mobile laser scanning (MLS) produces dense point clouds from huge areas efficiently from which the road and its environment can be modeled in detail. Objects such as buildings, cars and trees are an important part of road environments. Different methods have been developed for detection of above such objects, but still there is a lack of accuracy due to the problems of illumination, environmental changes, and multiple objects with same features. In this work the comparison between different classifiers such as Multiclass SVM, kNN and Multiclass LDA for the road environment detection is analyzed. Finally the classification accuracy for kNN with LBP feature improved the classification accuracy as 93.3% than the other classifiers.
Abstract: In general, state-of-the-art Data Acquisition Systems
(DAQ) in high energy physics experiments must satisfy high
requirements in terms of reliability, efficiency and data rate capability.
This paper presents the development and deployment of a debugging
tool named DAQ Debugger for the intelligent, FPGA-based Data
Acquisition System (iFDAQ) of the COMPASS experiment at CERN.
Utilizing a hardware event builder, the iFDAQ is designed to be
able to readout data at the average maximum rate of 1.5 GB/s of
the experiment. In complex softwares, such as the iFDAQ, having
thousands of lines of code, the debugging process is absolutely
essential to reveal all software issues. Unfortunately, conventional
debugging of the iFDAQ is not possible during the real data taking.
The DAQ Debugger is a tool for identifying a problem, isolating
the source of the problem, and then either correcting the problem
or determining a way to work around it. It provides the layer
for an easy integration to any process and has no impact on the
process performance. Based on handling of system signals, the
DAQ Debugger represents an alternative to conventional debuggers
provided by most integrated development environments. Whenever
problem occurs, it generates reports containing all necessary
information important for a deeper investigation and analysis. The
DAQ Debugger was fully incorporated to all processes in the iFDAQ
during the run 2016. It helped to reveal remaining software issues
and improved significantly the stability of the system in comparison
with the previous run. In the paper, we present the DAQ Debugger
from several insights and discuss it in a detailed way.
Abstract: Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.
Abstract: Fiber reinforced polymeric (FRP) composites are finding wide-spread industrial applications because of their exceptionally high specific strength and specific modulus of elasticity. Nevertheless, it is very seldom to get ready-for-use components or products made of FRP composites. Secondary processing by machining, particularly drilling, is almost always required to make holes for fastening components together to produce assemblies. That creates problems since the FRP composites are neither homogeneous nor isotropic. Some of the problems that are encountered include the subsequent damage in the region around the drilled hole and the drilling – induced delamination of the layer of ply, that occurs both at the entrance and the exit planes of the work piece. Evidently, the functionality of the work piece would be detrimentally affected. The current work was carried out with the aim of eliminating or at least minimizing the work piece damage associated with drilling of FPR composites. Each test specimen involves a woven reinforced graphite fiber/epoxy composite having a thickness of 12.5 mm (0.5 inch). A large number of test specimens were subjected to drilling operations with different combinations of feed rates and cutting speeds. The drilling induced damage was taken as the absolute value of the difference between the drilled hole diameter and the nominal one taken as a percentage of the nominal diameter. The later was determined for each combination of feed rate and cutting speed, and a matrix comprising those values was established, where the columns indicate varying feed rate while and rows indicate varying cutting speeds. Next, the analysis of variance (ANOVA) approach was employed using Minitab software, in order to obtain the combination that would improve the drilling induced damage. Experimental results show that low feed rates coupled with low cutting speeds yielded the best results.
Abstract: In this paper, we present a wavelet coefficients masking
based on Local Binary Patterns (WLBP) approach to enhance the
temporal spectra of the wavelet coefficients for speech enhancement.
This technique exploits the wavelet denoising scheme, which splits
the degraded speech into pyramidal subband components and extracts
frequency information without losing temporal information. Speech
enhancement in each high-frequency subband is performed by binary
labels through the local binary pattern masking that encodes the ratio
between the original value of each coefficient and the values of the
neighbour coefficients. This approach enhances the high-frequency
spectra of the wavelet transform instead of eliminating them through
a threshold. A comparative analysis is carried out with conventional
speech enhancement algorithms, demonstrating that the proposed
technique achieves significant improvements in terms of PESQ, an
international recommendation of objective measure for estimating
subjective speech quality. Informal listening tests also show that
the proposed method in an acoustic context improves the quality
of speech, avoiding the annoying musical noise present in other
speech enhancement techniques. Experimental results obtained with a
DNN based speech recognizer in noisy environments corroborate the
superiority of the proposed scheme in the robust speech recognition
scenario.
Abstract: In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.
Abstract: The ceramic yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) has been used as a dental biomaterial for several decades. The strength and toughness of this material can be accounted for by its toughening mechanisms, which include transformation toughening, crack deflection, zone shielding, contact shielding, and crack bridging. Prevention of crack propagation is of critical importance in high-fatigue situations, such as those encountered in mastication and para-function. However, the poor translucence of Y-TZP in polycrystalline form is such that it may not meet the aesthetic requirements due to its white/grey appearance. To improve the optical properties of Y-TZP, more detailed study of the optical properties is required; in particular, precise evaluation of the refractive index, absorption coefficient, and scattering coefficient are necessary. The measurement of the optical parameters has been based on the assumption that light scattered from biological media is isotropically distributed over all angles. In fact, the optical behavior of real biological materials depends on the angular scattering of light due to the anisotropic nature of the materials. The purpose of the present work is to evaluate the optical properties (including color, opacity/translucence, scattering, and fluorescence) of zirconia dental ceramics and their control through modification of the chemical composition, phase composition, and surface microstructure.
Abstract: Internal supply chain management benchmarking practice is necessary to overcome manufacturing industrial performance gap. The main purpose of this research work is to combine the benchmarking and internal supply chain practices to improve the performance of Indian manufacturing industries. In this paper, the main aim is to discuss the components of internal supply chain between suppliers and customers after that explain the scope of ISCM benchmarking in manufacturing industries.
Abstract: Enhanching English vocabulary in early childhood is the main problem often faced by teachers. Thus, the purpose of this study was to determine the enhancement of children’s English vocabulary acquisition by using digital storytelling. This type of research was an action research. It consisted of a series of four activities done in repeated cycles: planning, implementation, observation, and reflection. The subject of the study consisted of 30 students of B group (5-6 years old) attending Happy Kids Kindergarten Palembang, Indonesia. This research was conducted in three cycles. The methods used for data collection were observation and documentation. Descriptive qualitative and quantitative methods were also used to analyse the data. The research showed that the digital storytelling learning activities could enhance the children’s English vocabulary acquisition. It is based on the data in which the enhancement in pre-cycle was 37% and 51% in Cycle I. In Cycle II it was 71% and in Cycle III it was 89.3%. The results showed an enhancement of about 14% from the pre-cycle to Cycle I, 20% from Cycle I to Cycle II, and enhancement of about 18.3% from Cycle II to Cycle III. The conclusion of this study suggests that digital storytelling learning method could enhance the English vocabulary acquisition of B group children at the Happy Kids Kindergarten Palembang. Therefore, digital storytelling can be considered as an alternative to improve English language learning in the classroom.
Abstract: Safe drinking water is needed for survival. Households have to pay the water bill monthly. However, lower income households are sometimes unable to afford the cost. This study examines water access and affordability among households in Malaysia and the determinants of water affordability using cross-sectional data and multiple regression. The paper expects that the bill for basic water consumption is inversely related to average income. This means that policy makers need to redesign the water tariff to improve the quality of life of lower income households.
Abstract: Clinical education is one of the most important components of a nursing curriculum as it develops the students’ cognitive, psychomotor and affective skills. Clinical teaching ensures the integration of knowledge into practice. As the numbers of students increase in the field of nursing coupled with the faculty shortage, clinical preceptors are the best choice to ensure student learning in the clinical settings. The clinical preceptor role has been introduced in the undergraduate nursing programme. In Pakistan, this role emerged due to a faculty shortage. Initially, two clinical preceptors were hired. This study will explore clinical preceptors views and experiences of precepting Bachelor of Science in Nursing (BScN) students in an undergraduate program. A case study design was used. As case studies explore a single unit of study such as a person or very small number of subjects; the two clinical preceptors were fundamental to the study and served as a single case. Qualitative data were obtained through an iterative process using in depth interviews and written accounts from reflective journals that were kept by the clinical preceptors. The findings revealed that the clinical preceptors were dedicated to their roles and responsibilities. Another, key finding was that clinical preceptors’ prior knowledge and clinical experience were valuable assets to perform their role effectively. The clinical preceptors found their new role innovative and challenging; it was stressful at the same time. Findings also revealed that in the clinical agencies there were unclear expectations and role ambiguity. Furthermore, clinical preceptors had difficulty integrating theory into practice in the clinical area and they had difficulty in giving feedback to the students. Although this study is localized to one university, generalizations can be drawn from the results. The key findings indicate that the role of a clinical preceptor is demanding and stressful. Clinical preceptors need preparation prior to precepting students on clinicals. Also, institutional support is fundamental for their acceptance. This paper focuses on the views and experiences of clinical preceptors undertaking a newly established role and resonates with the literature. The following recommendations are drawn to strengthen the role of the clinical preceptors: A structured program for clinical preceptors is needed along with mentorship. Clinical preceptors should be provided with formal training in teaching and learning with emphasis on clinical teaching and giving feedback to students. Additionally, for improving integration of theory into practice, clinical modules should be provided ahead of the clinical. In spite of all the challenges, ten more clinical preceptors have been hired as the faculty shortage continues to persist.
Abstract: In this paper, we present the comparative subjective analysis of Improved Minima Controlled Recursive Averaging (IMCRA) Algorithm, the Kalman filter and the cascading of IMCRA and Kalman filter algorithms. Performance of speech enhancement algorithms can be predicted in two different ways. One is the objective method of evaluation in which the speech quality parameters are predicted computationally. The second is a subjective listening test in which the processed speech signal is subjected to the listeners who judge the quality of speech on certain parameters. The comparative objective evaluation of these algorithms was analyzed in terms of Global SNR, Segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) by the authors and it was reported that with cascaded algorithms there is a substantial increase in objective parameters. Since subjective evaluation is the real test to judge the quality of speech enhancement algorithms, the authenticity of superiority of cascaded algorithms over individual IMCRA and Kalman algorithms is tested through subjective analysis in this paper. The results of subjective listening tests have confirmed that the cascaded algorithms perform better under all types of noise conditions.
Abstract: The present research reports the investigation of fast etching of silicon for the fabrication of microelectromechanical systems (MEMS) structures using silicon wet bulk micromachining. Low concentration tetramethyl-ammonium hydroxide (TMAH) and hydroxylamine (NH2OH) are used as main etchant and additive, respectively. The concentration of NH2OH is varied to optimize the composition to achieve best etching characteristics such as high etch rate, significantly high undercutting at convex corner for the fast release of the microstructures from the substrate, and improved etched surface morphology. These etching characteristics are studied on Si{100} and Si{110} wafers as they are most widely used in the fabrication of MEMS structures as wells diode, transistors and integrated circuits.
Abstract: This paper investigates MIMO (Multiple-Input
Multiple-Output) adaptive filtering techniques for the application
of supervised source separation in the context of convolutive
mixtures. From the observation that there is correlation among the
signals of the different mixtures, an improvement in the NSAF
(Normalized Subband Adaptive Filter) algorithm is proposed in
order to accelerate its convergence rate. Simulation results with
mixtures of speech signals in reverberant environments show the
superior performance of the proposed algorithm with respect to the
performances of the NLMS (Normalized Least-Mean-Square) and
conventional NSAF, considering both the convergence speed and
SIR (Signal-to-Interference Ratio) after convergence.
Abstract: The study aims to assess efficient specific-location soybean farming technology assembly by assisting the farmers in applying the suggested technology. Superimposed trial was conducted to know NPK fertilizer effect toward soybean growth and yield and soybean improved variety test for the dissemination of improved variety. The assessment was conducted at the farmers group of Sumber Rejeki, Kepulungan Village, Gempol Sub-district, Pasuruan Regency as the soybean central at Pasuruan area. The number of farmers involved in the study was 38 people with 25 ha soybean area. This study was held from July to October 2012. The recommended technology package agreed at the socialization time and used in this research were: using Argomulyo variety seeds of 40 kg/ha, planting by drilling, planting by distance of 40x10 cm, deciding the seeds amount of 2-3 seeds per hole, and giving fertilization based on recommendation of East Java AIAT of 50 kg Urea, 100 kg SP-36 and 50 kg KCl. Farmers around the research location were used as control group. Assessment on soybean farming system was considered effective because it could increase the production up to 38%. The farming analysis showed that the result collaborator farmers gained were positively higher than non-collaborator farmers with RC ratio of 2.03 and 1.54, respectively. Argomulyo variety has the prospect to be developed due to the high yield of about 2 tons/ha and the larger seeds. The NPK fertilization test at the soybean plants showed that the fertilization had minor effect on the yield.
Abstract: The aim of this study is to conduct an experimental investigation on the influence of complete replacement of natural coarse aggregate with spherically-shape and crushed waste cathode ray tube (CRT) glass to the aspect of workability, density, and compressive strength of the concrete. After characterizing the glass, a group of concrete mixes was prepared to contain a 40% spherical CRT glass and 60% crushed CRT glass as a complete (100%) replacement of natural coarse aggregates. From a total of 16 types of concrete mixes, the optimum proportion was selected based on its best performance. The test results showed that the use of spherical and crushed glass that possesses a smooth surface, rounded, irregular and elongated shape, and low water absorption affects the workability of concrete. Due to a higher specific gravity of crushed glass, concrete mixes containing CRT glass had a higher density compared to ordinary concrete. Despite the spherical and crushed CRT glass being stronger than gravel, the results revealed a reduction in compressive strength of the concrete. However, using a lower water to binder (w/b) ratio and a higher superplasticizer (SP) dosage, it is found to enhance the compressive strength of 60.97 MPa at 28 days that is lower by 13% than the control specimen. These findings indicate that waste CRT glass in the form of spherical and crushed could be used as an alternative of coarse aggregate that may pave the way for the disposal of hazardous e-waste.
Abstract: Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.
Abstract: Traditional medicine has been part of the Algerian culture for decades. In particular, the city of Tlemcen still retains practices based on phytotherapy to the present day, as this kind of medicine fulfills the needs of its followers among the local population. The toxic plants contain diverse natural substances which supplied a lot of medicine in the pharmaceutical industry. In order to explore new medicinal sources among toxic plants, an ethnobotanical study was carried out on the use of these plants by the population, at Emir Abdelkader Square of the city of Tlemcen, a rather busy place with a high number of traditional health practitioners and herbalists. This is a descriptive and transversal study aimed at estimating the frequency of using toxic plants among the studied population, for a period of 4 months. The information was collected, using self-anonymous questionnaires, and analyzed by the IBM SPSS Statistics software used for statistical analysis. A sample of 200 people, including 120 women and 80 men, were interviewed. The mean age was 41 ± 16 years. Among those questioned, 83.5% used plants; 8% of them used toxic plants and 35% used plants that can be toxic under certain conditions. Some improvements were observed in 88% of the cases where toxic plants were used. 80 medicinal plants, belonging to 36 botanical families, were listed, identified and classified. The most frequent indications for these plants were for respiratory diseases in 64.7% of cases, and for digestive disorders in 51.5% of cases. 11% of these plants are toxic, 26% could be toxic under certain conditions. Among toxics plants, the most common ones are Berberis vulgaris with 5.4%, indicated in the treatment of uterine fibroids and thyroid, Rhamnus alaternus with 4.8% for hepatic jaundice, Nerium oleander with 3% for hemorrhoids, Ruta chalepensis with 1.2%, indicated for digestive disorders and dysmenorrhea, and Viscum album with 1.2%, indicated for respiratory diseases. The most common plants that could be toxic are Mentha pulegium (15.6%), Eucalyptus globulus (11.4%), and Pimpinella anisum (10.2%). This study revealed interesting results on the use of toxic plants, which are likely to serve as a basis for further ethno-pharmacological investigations in order to get new drug sources.
Abstract: To obtain the high quality and essential workability of mortar, different types of superplasticizers are used. The superplasticizers are the chemical admixture used in the mix to improve the fluidity of mortar. Many factors influenced the superplasticizer to disperse the cement particle in the mortar. Nature and amount of replaced cement by slag, mixing procedure, delayed addition time, and heat stimulation technique of superplasticizer cause the varied effect on the fluidity of the cementitious material. In this experiment, the superplasticizers were heated for 1 hour under 60 °C in a thermostatic chamber. Furthermore, the effect of delayed addition time of heat stimulated superplasticizers (SP) was also analyzed. This method was applied to two types of polycarboxylic acid based ether SP (precast type superplasticizer (SP2) and ready-mix type superplasticizer (SP1)) in combination with a partial replacement of normal Portland cement with blast furnace slag (BFS) with 30% w/c ratio. On the other hands, the fluidity, air content, fresh density, and compressive strength for 7 and 28 days were studied. The results indicate that the addition time and heat stimulation technique improved the flow and air content, decreased the density, and slightly decreased the compressive strength of mortar. Moreover, the slag improved the flow of mortar by increasing the amount of slag, and the effect of external temperature of SP on the flow of mortar was decreased. In comparison, the flow of mortar was improved on 5-minute delay for both kinds of SP, but SP1 has improved the flow in all conditions. Most importantly, the transition points in both types of SP appear to be the same, at about 5±1 min. In addition, the optimum addition time of SP to mortar should be in this period.