Search results for: machine learning techniques

Authors: K. Paradkar, S. N. Mudliar, A. Sharma, A. B. Pandit, R. A. Pandey

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The study explores the hybrid combination of Hydrodynamic Cavitation (HC) and Subcritical Wet Air Oxidation-based pretreatment of complex industrial effluent to enhance the biodegradability selectively (without major COD destruction) to facilitate subsequent enhanced downstream processing via anaerobic or aerobic biological treatment. Advanced oxidation based techniques can be less efficient as standalone options and a hybrid approach by combining Hydrodynamic Cavitation (HC), and Wet Air Oxidation (WAO) can lead to a synergistic effect since both the options are based on common free radical mechanism. The HC can be used for initial turbulence and generation of hotspots which can begin the free radical attack and this agitating mixture then can be subjected to less intense WAO since initial heat (to raise the activation energy) can be taken care by HC alone. Lab-scale venturi-based hydrodynamic cavitation and wet air oxidation reactor with biomethanated distillery wastewater (BMDWW) as a model effluent was examined for establishing the proof-of-concept. The results indicated that for a desirable biodegradability index (BOD: COD - BI) enhancement (up to 0.4), the Cavitation (standalone) pretreatment condition was: 5 bar and 88 min reaction time with a COD reduction of 36 % and BI enhancement of up to 0.27 (initial BI - 0.17). The optimum WAO condition (standalone) was: 150oC, 6 bar and 30 minutes with 31% COD reduction and 0.33 BI. The hybrid pretreatment (combined Cavitation + WAO) worked out to be 23.18 min HC (at 5 bar) followed by 30 min WAO at 150oC, 6 bar, at which around 50% COD was retained yielding a BI of 0.55. FTIR & NMR analysis of pretreated effluent indicated dissociation and/or reorientation of complex organic compounds in untreated effluent to simpler organic compounds post-pretreatment.

Keywords: BI, hybrid, hydrodynamic cavitation, wet air oxidation.

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: Diabetes, glucose level, linear, near-infrared (NIR), non-invasive, prediction system.

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Authors: Gaurav

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Sexuality remains a personal or a private matter of discussion in the Indian society and generally discussed among the same age group or gender. Complete absence of the sex education has caused serious implications for the students with disabilities in Indian society. There are widespread perceptions that student with disabilities are ‘asexual’, ‘unattractive’ and therefore cannot be considered sexually desirable. Such perceptions continue to reinforce the other perceptions that student with disabilities are somehow incapable of being in an intimate relationship in the life and therefore they do not need any learning related to the sex education. We need to understand that if a student has a disability, it does not mean that student have no emotional feelings, hormones and sexual desires like any other student without disability. Sexuality is an integral part of every human life and should not be seen as matter of shame and guilt. Unfortunately, the concept of the sex education is misunderstood in itself. Instead of realizing the crucial importance of sex education for the students with disabilities or non-disabilities, it is often considered mainly as an education about ‘how to have sexual intercourse’. One needs to understand that it is not just about sexual conduct but also about the gender and sexual identity, self-esteem, self protection and acceptance of self. This research paper examined issues and debates around the sex education, particularly in context of the students with disabilities in India and focuses on how students with disabilities themselves see the need of sex (health) education. To understand their perceptions, descriptive survey method was used. It was found that most of the students among respondent were comfortable and felt it as a strong need for such orientation during their schooling. The paper emphasizes that sex education is a need of the time and further a necessity. Hence it is important for our education system to implement it for the complete well being of the students with disabilities.

Keywords: Disabilities, identity, sexuality, sex education.

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Authors: Kjersti Engan, Thor Ole Gulsrud, Karl Fredrik Fretheim, Barbro Furebotten Iversen, Liv Eriksen

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Clusters of microcalcifications in mammograms are an important sign of breast cancer. This paper presents a complete Computer Aided Detection (CAD) scheme for automatic detection of clustered microcalcifications in digital mammograms. The proposed system, MammoScan μCaD, consists of three main steps. Firstly all potential microcalcifications are detected using a a method for feature extraction, VarMet, and adaptive thresholding. This will also give a number of false detections. The goal of the second step, Classifier level 1, is to remove everything but microcalcifications. The last step, Classifier level 2, uses learned dictionaries and sparse representations as a texture classification technique to distinguish single, benign microcalcifications from clustered microcalcifications, in addition to remove some remaining false detections. The system is trained and tested on true digital data from Stavanger University Hospital, and the results are evaluated by radiologists. The overall results are promising, with a sensitivity > 90 % and a low false detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).

Keywords: mammogram, microcalcifications, detection, CAD, MammoScan μCaD, VarMet, dictionary learning, texture, FTCM, classification, adaptive thresholding

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Authors: S. Visetpotjanakit, N. Nakkaew

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Determination of ⁹⁰Sr in environmental samples has been widely developed with several radioanlytical methods and radiation measurement techniques since ⁹⁰Sr is one of the most hazardous radionuclides produced from nuclear reactors. Liquid extraction technique using di-(2-ethylhexyl) phosphoric acid (HDEHP) to separate and purify ⁹⁰Y and Cherenkov counting using liquid scintillation counter to determine ⁹⁰Y in secular equilibrium to ⁹⁰Sr was developed and performed at our institute, the Office of Atoms for Peace. The approach is inexpensive, non-laborious, and fast to analyse ⁹⁰Sr in environmental samples. To validate our analytical performance for the accurate and precise criteria, determination of ⁹⁰Sr using the IAEA-TEL-2016-04 ALMERA proficiency test samples were performed for statistical evaluation. The experiment used two spiked tap water samples and one naturally contaminated spruce needles sample from Austria collected shortly after the Chernobyl accident. Results showed that all three analyses were successfully passed in terms of both accuracy and precision criteria, obtaining “Accepted” statuses. The two water samples obtained the measured results of 15.54 Bq/kg and 19.76 Bq/kg, which had relative bias 5.68% and -3.63% for the Maximum Acceptable Relative Bias (MARB) 15% and 20%, respectively. And the spruce needles sample obtained the measured results of 21.04 Bq/kg, which had relative bias 23.78% for the MARB 30%. These results confirm our analytical performance of ⁹⁰Sr determination in water and spruce needles samples using the same developed method.

Keywords: ALMERA proficiency test, Cherenkov counting, determination of 90Sr, environmental samples.

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Authors: Luminiţa Duţică

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For the music composer Myriam Marbe the musical time and memory represent 2 (complementary) phenomena with conclusive impact on the settlement of new musical ontologies. Summarizing the most important achievements of the contemporary techniques of composition, her vision on the microform presented in The Concert for Daniel Kientzy, saxophone and orchestra transcends the linear and unidirectional time in favour of a flexible, multivectorial speech with spiral developments, where the sound substance is auto(re)generated by analogy with the fundamental processes of the memory. The conceptual model is of an archetypal essence, the music composer being concerned with identifying the mechanisms of the creation process, especially of those specific to the collective creation (of oral tradition). Hence the spontaneity of expression, improvisation tint, free rhythm, micro-interval intonation, coloristictimbral universe dominated by multiphonics and unique sound effects, hence the atmosphere of ritual, however purged by the primary connotations and reprojected into a wonderful spectacular space. The Concert is a work of artistic maturity and enforces respect, among others, by the timbral diversity of the three species of saxophone required by the music composer (baritone, sopranino and alt), in Part III Daniel Kientzy shows the performance of playing two saxophones concomitantly. The score of the music composer Myriam Marbe contains a deeply spiritualized music, full or archetypal symbols, a music whose drama suggests a real cinematographic movement.

Keywords: Archetype, chronogenesis, concert, multiphonics.

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Authors: Sanjay Singh, M Sathish Kumar, H. S Mruthyunjaya

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Multicarrier transmission system such as Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high bit rate transmission in wireless communication system. OFDM is a spectrally efficient modulation technique that can achieve high speed data transmission over multipath fading channels without the need for powerful equalization techniques. However the price paid for this high spectral efficiency and less intensive equalization is low power efficiency. OFDM signals are very sensitive to nonlinear effects due to the high Peak-to-Average Power Ratio (PAPR), which leads to the power inefficiency in the RF section of the transmitter. This paper investigates the effect of PAPR reduction on the performance parameter of multicarrier communication system. Performance parameters considered are power consumption of Power Amplifier (PA) and Digital-to-Analog Converter (DAC), power amplifier efficiency, SNR of DAC and BER performance of the system. From our analysis it is found that irrespective of PAPR reduction technique being employed, the power consumption of PA and DAC reduces and power amplifier efficiency increases due to reduction in PAPR. Moreover, it has been shown that for a given BER performance the requirement of Input-Backoff (IBO) reduces with reduction in PAPR.

Keywords: BER, Crest Factor (CF), Digital-to-Analog Converter(DAC), Input-Backoff (IBO), Orthogonal Frequency Division Multiplexing(OFDM), Peak-to-Average Power Ratio (PAPR), PowerAmplifier efficiency, SNR

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: Object detection, histopathology, breast cancer, mitotic count, deep learning, computer vision.

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Authors: Seksan Chunothaisawat, Pongchanun Luangpaiboon

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There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.

Keywords: Ant colony optimisation, metaheuristics, modified simplex, non-linear, rigid simplex.

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Authors: M. Analoui, M. Fadavi Amiri

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The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced.

Keywords: Feature reduction, genetic algorithm, pattern classification, nearest neighbor rule classifiers (k-NNR).

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Authors: Hsien-Chou Liao, Yu-Shiang Wang

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Surveillance system is widely used in the traffic monitoring. The deployment of cameras is moving toward a ubiquitous camera (UbiCam) environment. In our previous study, a novel service, called GPS-VT, was firstly proposed by incorporating global positioning system (GPS) and visual tracking techniques for the UbiCam environment. The first prototype is called GODTA (GPS-based Moving Object Detection and Tracking Approach). For a moving person carried GPS-enabled mobile device, he can be tracking when he enters the field-of-view (FOV) of a camera according to his real-time GPS coordinate. In this paper, GPS-VT service is applied to the tracking of vehicles. The moving speed of a vehicle is much faster than a person. It means that the time passing through the FOV is much shorter than that of a person. Besides, the update interval of GPS coordinate is once per second, it is asynchronous with the frame rate of the real-time image. The above asynchronous is worsen by the network transmission delay. These factors are the main challenging to fulfill GPS-VT service on a vehicle.In order to overcome the influence of the above factors, a back-propagation neural network (BPNN) is used to predict the possible lane before the vehicle enters the FOV of a camera. Then, a template matching technique is used for the visual tracking of a target vehicle. The experimental result shows that the target vehicle can be located and tracking successfully. The success location rate of the implemented prototype is higher than that of the previous GODTA.

Keywords: visual surveillance, visual tracking, globalpositioning system, intelligent transportation system

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Authors: K. P. K. S. Lahirushan, W. G. V. Gunasekara

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Main purpose of this study is to identify the impact of government expenditure on economic growth in Asian Countries. Consequently, main objective is to analyze whether government expenditure causes economic growth in Asian countries vice versa and then scrutinizing long-run equilibrium relationship exists between them. The study completely based on secondary data. The methodology being quantitative that includes econometrical techniques of cointegration, panel fixed effects model and granger causality in the context of panel data of Asian countries; Singapore, Malaysia, Thailand, South Korea, Japan, China, Sri Lanka, India and Bhutan with 44 observations in each country, totaling to 396 observations from 1970 to 2013. The model used is the random effects panel OLS model. As with the above methodology, the study found the fascinating outcome. At first, empirical findings exhibit a momentous positive impact of government expenditure on Gross Domestic Production in Asian region. Secondly, government expenditure and economic growth indicate a long-run relationship in Asian countries. In conclusion, there is a unidirectional causality from economic growth to government expenditure and government expenditure to economic growth in Asian countries. Hence the study is validated that it is in line with the Keynesian theory and Wagner’s law as well. Consequently, it can be concluded that role of government would play a vital role in economic growth of Asian Countries. However; if government expenditure did not figure out with the economy’s needs it might be considerably inspiration the economy in a negative way so that society bears the costs.

Keywords: Asian Countries, Government Expenditure, Keynesian theory, Wagner’s theory, Random effects panel OLS model.

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Authors: M. M. Rahman, Md. Ashikur Rahman Khan, K. Kadirgama M. M. Noor, Rosli A. Bakar

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This paper deals optimized model to investigate the effects of peak current, pulse on time and pulse off time in EDM performance on material removal rate of titanium alloy utilizing copper tungsten as electrode and positive polarity of the electrode. The experiments are carried out on Ti6Al4V. Experiments were conducted by varying the peak current, pulse on time and pulse off time. A mathematical model is developed to correlate the influences of these variables and material removal rate of workpiece. Design of experiments (DOE) method and response surface methodology (RSM) techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance (ANOVA). The obtained results evidence that as the material removal rate increases as peak current and pulse on time increases. The effect of pulse off time on MRR changes with peak ampere. The optimum machining conditions in favor of material removal rate are verified and compared. The optimum machining conditions in favor of material removal rate are estimated and verified with proposed optimized results. It is observed that the developed model is within the limits of the agreeable error (about 4%) when compared to experimental results. This result leads to desirable material removal rate and economical industrial machining to optimize the input parameters.

Keywords: Ti-6Al-4V, material removal rate, copper tungsten, positive polarity, RSM.

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Authors: E. M. Hassan, A. L. Kalamkarov

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Two micromechanical models for 3D smart composite with embedded periodic or nearly periodic network of generally orthotropic reinforcements and actuators are developed and applied to cubic structures with unidirectional orientation of constituents. Analytical formulas for the effective piezothermoelastic coefficients are derived using the Asymptotic Homogenization Method (AHM). Finite Element Analysis (FEA) is subsequently developed and used to examine the aforementioned periodic 3D network reinforced smart structures. The deformation responses from the FE simulations are used to extract effective coefficients. The results from both techniques are compared. This work considers piezoelectric materials that respond linearly to changes in electric field, electric displacement, mechanical stress and strain and thermal effects. This combination of electric fields and thermo-mechanical response in smart composite structures is characterized by piezoelectric and thermal expansion coefficients. The problem is represented by unitcell and the models are developed using the AHM and the FEA to determine the effective piezoelectric and thermal expansion coefficients. Each unit cell contains a number of orthotropic inclusions in the form of structural reinforcements and actuators. Using matrix representation of the coupled response of the unit cell, the effective piezoelectric and thermal expansion coefficients are calculated and compared with results of the asymptotic homogenization method. A very good agreement is shown between these two approaches.

Keywords: Asymptotic Homogenization Method, Effective Piezothermoelastic Coefficients, Finite Element Analysis, 3D Smart Network Composite Structures.

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Authors: Tomasz Dubiel, Tadeusz Balawender, Mirosław Osetek

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The paper presents the influence of non-metallic inclusions on the multi-stage forging process and the mechanical properties of the dodecagon socket bolt used in the automotive industry. The detected metallurgical defect was so large that it directly influenced the mechanical properties of the bolt and resulted in failure to meet the requirements of the mechanical property class. In order to assess the defect, an X-ray examination and metallographic examination of the defective bolt were performed, showing exogenous non-metallic inclusion. The size of the defect on the cross section was 0.531 mm in width and 1.523 mm in length; the defect was continuous along the entire axis of the bolt. In analysis, a finite element method (FEM) simulation of the multi-stage forging process was designed, taking into account a non-metallic inclusion parallel to the sample axis, reflecting the studied case. The process of defect propagation due to material upset in the head area was analyzed. The final forging stage in shaping the dodecagonal socket and filling the flange area was particularly studied. The effect of the defect was observed to significantly reduce the effective cross-section as a result of the expansion of the defect perpendicular to the axis of the bolt. The mechanical properties of products with and without the defect were analyzed. In the first step, the hardness test confirmed that the required value for the mechanical class 8.8 of both bolt types was obtained. In the second step, the bolts were subjected to a static tensile test. The bolts without the defect gave a positive result, while all 10 bolts with the defect gave a negative result, achieving a tensile strength below the requirements. Tensile strength tests were confirmed by metallographic tests and FEM simulation with perpendicular inclusion spread in the area of the head. The bolts were damaged directly under the bolt head, which is inconsistent with the requirements of ISO 898-1. It has been shown that non-metallic inclusions with orientation in accordance with the axis of the bolt can directly cause loss of functionality and these defects should be detected even before assembling in the machine element.

Keywords: continuous casting, multi-stage forging, non-metallic inclusion, upset bolt head

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Authors: Naoto Suzuki

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Japanese are affected by the most common causes of eyesight loss such as glaucoma, diabetic retinopathy, pigmentary retinal degeneration, and age-related macular degeneration. We developed an ophthalmological examination apparatus with a fundus camera, precisely fundus-related perimetry (microperimetry), and electroretinogram (ERG) functions to diagnose a variety of diseases that cause eyesight loss. The experimental apparatus was constructed with the same optical system as a fundus camera. The microperimetry optical system was calculated and added to the experimental apparatus using the German company Optenso's optical engineering software (OpTaliX-LT 10.8). We also added an Edmund infrared camera (EO-0413), a lens with a 25 mm focal length, a 45° cold mirror, a 12 V/50 W halogen lamp, and an 8-inch monitor. We made the artificial eye of a plane-convex lens, a black spacer, and a hemispherical cup. The hemispherical cup had a small section of the paper at the bottom. The artificial eye was photographed five times using the experimental apparatus. The software was created to display the examination target on the monitor and save examination data using C++Builder 10.2. The retinal fundus was displayed on the monitor at a length and width of 1 mm and a resolution of 70.4 ± 4.1 and 74.7 ± 6.8 pixels, respectively. The microperimetry and ERG functions were successfully added to the experimental ophthalmological apparatus. A moving machine was developed to measure the artificial eye's movement. The artificial eye's rear part was painted black and white in the central area. It was rotated 10 degrees from one side to the other. The movement was captured five times as motion videos. Three static images were extracted from one of the motion videos captured. The images display the artificial eye facing the center, right, and left directions. The three images were processed using Scilab 6.1.0 and Image Processing and Computer Vision Toolbox 4.1.2, including trimming, binarization, making a window, deleting peripheral area, and morphological operations. To calculate the artificial eye's fundus center, we added a gravity method to the program to calculate the gravity position of connected components. From the three images, the image processing could calculate the center position.

Keywords: Ophthalmological examination apparatus, microperimetry, electroretinogram, eye movement.

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Authors: Amira Mabrouk, Chokri Abdennadher

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The reduction of road congestion which is inherent to the use of vehicles is an obvious priority to public authority. Therefore, assessing the willingness to pay of an individual in order to save trip-time is akin to estimating the change in price which was the result of setting up a new transport policy to increase the networks fluidity and improving the level of social welfare. This study holds an innovative perspective. In fact, it initiates an economic calculation that has the objective of giving an estimation of the monetized time value during the trips made in Sfax. This research is founded on a double-objective approach. The aim of this study is to i) give an estimation of the monetized value of time; an hour dedicated to trips, ii) determine whether or not the consumer considers the environmental variables to be significant, iii) analyze the impact of applying a public management of the congestion via imposing taxation of city tolls on urban dwellers. This article is built upon a rich field survey led in the city of Sfax. With the use of the contingent valuation method, we analyze the “declared time preferences” of 450 drivers during rush hours. Based on the fond consideration of attributed bias of the applied method, we bring to light the delicacy of this approach with regards to the revelation mode and the interrogative techniques by following the NOAA panel recommendations bearing the exception of the valorization point and other similar studies about the estimation of transportation externality.

Keywords: Willingness to pay, value of time, contingent valuation, time value, city toll, transport.

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Authors: Robert H. Crawford, André Stephan

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Certifications such as the Passive House Standard aim to reduce the final space heating energy demand of residential buildings. Space conditioning, notably heating, is responsible for nearly 70% of final residential energy consumption in Europe. There is therefore significant scope for the reduction of energy consumption through improvements to the energy efficiency of residential buildings. However, these certifications totally overlook the energy embodied in the building materials used to achieve this greater operational energy efficiency. The large amount of insulation and the triple-glazed high efficiency windows require a significant amount of energy to manufacture. While some previous studies have assessed the life cycle energy demand of passive houses, including their embodied energy, these rely on incomplete assessment techniques which greatly underestimate embodied energy and can lead to misleading conclusions. This paper analyses the embodied and operational energy demands of a case study passive house using a comprehensive hybrid analysis technique to quantify embodied energy. Results show that the embodied energy is much more significant than previously thought. Also, compared to a standard house with the same geometry, structure, finishes and number of people, a passive house can use more energy over 80 years, mainly due to the additional materials required. Current building energy efficiency certifications should widen their system boundaries to include embodied energy in order to reduce the life cycle energy demand of residential buildings.

Keywords: Embodied energy, Hybrid analysis, Life cycle energy analysis, Passive house.

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Authors: Erika Martinez Ramirez, Rene V. Mayorga

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Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.

Keywords: Artificial Intelligence, Fuzzy Logic, Fuzzy InferenceSystems, Nonlinear Optimization.

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: Data mining, digital libraries, digital preservation, file format.

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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Bangpoo, Samu tPrakan province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows:

1. The identity of Bangpoo, Samut Prakan province. This establishment was near the Mouth of the Gulf of Thailand for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Banpoo seaside resort and mangrove trees. Bangpoo seaside resort is characterized by muddy beacheswhere the greatest number of seagulls can be seen from March to May each year.
2. The communication of the identity of Bangpoo, Samut Prakan province which the researcher could find and design to present in English materials can be summed up in 3 items: 1) The history of Bangpoo, Samut Prakan province 2) The Learning center of Ecotourism: Seagulls and Mangrove forest 3) How to keep Banpoo, Samut Prakran province for ecotourism.

Keywords: Foreigner tourists, signified, semiotics, ecotourism.

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Authors: A. Alshebani, Y. Swesi, S. Mrayed, F. Altaher

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This paper present some preliminary work on the preparation and physicochemical caracterization of nanocomposite MFI-alumina structures based on alumina hollow fibres. The fibers are manufactured by a wet spinning process. α-alumina particles were dispersed in a solution of polysulfone in NMP. The resulting slurry is pressed through the annular gap of a spinneret into a precipitation bath. The resulting green fibres are sintered. The mechanical strength of the alumina hollow fibres is determined by a three-point-bending test while the pore size is characterized by bubble-point testing. The bending strength is in the range of 110 MPa while the average pore size is 450 nm for an internal diameter of 1 mm and external diameter of 1.7 mm. To characterize the MFI membranes various techniques were used for physicochemical characterization of MFI–ceramic hollow fibres membranes: The nitrogen adsorption, X-ray diffractometry, scanning electron microscopy combined with X emission microanalysis. Scanning Electron Microscopy (SEM) and Energy Dispersive Microanalysis by the X-ray were used to observe the morphology of the hollow fibre membranes (thickness, infiltration into the carrier, defects, homogeneity). No surface film, has been obtained, as observed by SEM and EDX analysis and confirmed by high temperature variation of N2 and CO2 gas permeances before cation exchange. Local analysis and characterise (SEM and EDX) and overall (by ICP elemental analysis) were conducted on two samples exchanged to determine the quantity and distribution of the cation of cesium on the cross section fibre of the zeolite between the cavities.

Keywords: Physicochemical characterization of MFI, Ceramic hollow fibre, CO2, Ion-exchange.

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Authors: Soukaina Motia, Nadia El Alami El Hassani, Alassane Diouf, Benachir Bouchikhi, Nezha El Bari

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Parabens are the antimicrobial molecules largely used in cosmetic products as a preservative agent. Among them, the methylparaben (MP) is the most frequently used ingredient in cosmetic preparations. Nevertheless, their potential dangers led to the development of sensible and reliable methods for their determination in environmental samples. Firstly, a sensitive and selective molecular imprinted polymer (MIP) based on screen-printed gold electrode (Au-SPE), assembled on a polymeric layer of carboxylated poly(vinyl-chloride) (PVC-COOH), was developed. After the template removal, the obtained material was able to rebind MP and discriminate it among other interfering species such as glucose, sucrose, and citric acid. The behavior of molecular imprinted sensor was characterized by Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS) techniques. Then, the biosensor was found to have a linear detection range from 0.1 pg.mL^-1 to 1 ng.mL^-1 and a low limit of detection of 0.12 fg.mL^-1 and 5.18 pg.mL^-1 by DPV and EIS, respectively. For applications, this biosensor was employed to determine MP content in four wastewaters in Meknes city and two cosmetic products (shower gel and shampoo). The operational reproducibility and stability of this biosensor were also studied. Secondly, another MIP biosensor based on tungsten trioxide (WO₃) functionalized by gold nanoparticles (Au-NPs) assembled on a polymeric layer of PVC-COOH was developed. The main goal was to increase the sensitivity of the biosensor. The developed MIP biosensor was successfully applied for the MP determination in wastewater samples and cosmetic products.

Keywords: Cosmetic products, methylparaben, molecularly imprinted polymer, wastewater.

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Authors: H. M. Côrtes, J. I. Da Silva Filho, M. F. Blos, B. S. Zanon

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In a modern society the factor corresponding to the increase in the level of quality in industrial production demand new techniques of control and machinery automation. In this context, this work presents the implementation of a Paraconsistent-Fuzzy Digital PID controller. The controller is based on the treatment of inconsistencies both in the Paraconsistent Logic and in the Fuzzy Logic. Paraconsistent analysis is performed on the signals applied to the system inputs using concepts from the Paraconsistent Annotated Logic with annotation of two values (PAL2v). The signals resulting from the paraconsistent analysis are two values defined as Dc - Degree of Certainty and Dct - Degree of Contradiction, which receive a treatment according to the Fuzzy Logic theory, and the resulting output of the logic actions is a single value called the crisp value, which is used to control dynamic system. Through an example, it was demonstrated the application of the proposed model. Initially, the Paraconsistent-Fuzzy Digital PID controller was built and tested in an isolated MATLAB environment and then compared to the equivalent Digital PID function of this software for standard step excitation. After this step, a level control plant was modeled to execute the controller function on a physical model, making the tests closer to the actual. For this, the control parameters (proportional, integral and derivative) were determined for the configuration of the conventional Digital PID controller and of the Paraconsistent-Fuzzy Digital PID, and the control meshes in MATLAB were assembled with the respective transfer function of the plant. Finally, the results of the comparison of the level control process between the Paraconsistent-Fuzzy Digital PID controller and the conventional Digital PID controller were presented.

Keywords: Fuzzy logic, paraconsistent annotated logic, level control, digital PID.

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Authors: A. Bajit, M. Nahid, A. Tamtaoui, E. H. Bouyakhf

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In this paper, we propose a Perceptually Optimized Embedded ZeroTree Image Coder (POEZIC) that introduces a perceptual weighting to wavelet transform coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to the coding quality obtained using the SPIHT algorithm only. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEZIC quality assessment. Our POEZIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) luminance masking and Contrast masking, 2) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting, 3) the Wavelet Error Sensitivity WES used to reduce the perceptual quantization errors. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.

Keywords: DWT, linear-phase 9/7 filter, 9/7 Wavelets Error Sensitivity WES, CSF implementation approaches, JND Just Noticeable Difference, Luminance masking, Contrast masking, standard SPIHT, Objective Quality Measure, Probability Score PS.

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Authors: Raja Singh Khela, R. K. Bansal, K. S. Sandhu, A. K. Goel

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Self-Excited Induction Generator (SEIG) builds up voltage while it enters in its magnetic saturation region. Due to non-linear magnetic characteristics, the performance analysis of SEIG involves cumbersome mathematical computations. The dependence of air-gap voltage on saturated magnetizing reactance can only be established at rated frequency by conducting a laboratory test commonly known as synchronous run test. But, there is no laboratory method to determine saturated magnetizing reactance and air-gap voltage of SEIG at varying speed, terminal capacitance and other loading conditions. For overall analysis of SEIG, prior information of magnetizing reactance, generated frequency and air-gap voltage is essentially required. Thus, analytical methods are the only alternative to determine these variables. Non-existence of direct mathematical relationship of these variables for different terminal conditions has forced the researchers to evolve new computational techniques. Artificial Neural Networks (ANNs) are very useful for solution of such complex problems, as they do not require any a priori information about the system. In this paper, an attempt is made to use cascaded neural networks to first determine the generated frequency and magnetizing reactance with varying terminal conditions and then air-gap voltage of SEIG. The results obtained from the ANN model are used to evaluate the overall performance of SEIG and are found to be in good agreement with experimental results. Hence, it is concluded that analysis of SEIG can be carried out effectively using ANNs.

Keywords: Self-Excited Induction Generator, Artificial NeuralNetworks, Exciting Capacitance and Saturated magnetizingreactance.

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Authors: Teh Raihana Nazirah Roslan, Siti Zulaiha Ibrahim, Sharmila Karim

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A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Keywords: Cox-Ingersoll-Ross model, equity warrants, Heston model, hybrid models, stochastic.

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Authors: Pankaj Chandna, Surinder Deswal, Arunesh Chandra, SK Sharma

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Noise has adverse effect on human health and comfort. Noise not only cause hearing impairment, but it also acts as a causal factor for stress and raising systolic pressure. Additionally it can be a causal factor in work accidents, both by marking hazards and warning signals and by impeding concentration. Industry workers also suffer psychological and physical stress as well as hearing loss due to industrial noise. This paper proposes an approach to enable engineers to point out quantitatively the noisiest source for modification, while multiple machines are operating simultaneously. The model with the point source and spherical radiation in a free field was adopted to formulate the problem. The procedure works very well in ideal cases (point source and free field). However, most of the industrial noise problems are complicated by the fact that the noise is confined in a room. Reflections from the walls, floor, ceiling, and equipment in a room create a reverberant sound field that alters the sound wave characteristics from those for the free field. So the model was validated for relatively low absorption room at NIT Kurukshetra Central Workshop. The results of validation pointed out that the estimated sound power of noise sources under simultaneous conditions were on lower side, within the error limits 3.56 - 6.35 %. Thus suggesting the use of this methodology for practical implementation in industry. To demonstrate the application of the above analytical procedure for estimating the sound power of noise sources under simultaneous operating conditions, a manufacturing facility (Railway Workshop at Yamunanagar, India) having five sound sources (machines) on its workshop floor is considered in this study. The findings of the case study had identified the two most effective candidates (noise sources) for noise control in the Railway Workshop Yamunanagar, India. The study suggests that the modification in the design and/or replacement of these two identified noisiest sources (machine) would be necessary so as to achieve an effective reduction in noise levels. Further, the estimated data allows engineers to better understand the noise situations of the workplace and to revise the map when changes occur in noise level due to a workplace re-layout.

Keywords: Industrial noise, sound power level, multiple noise sources, sources contribution.

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Authors: Hazem M. El-Bakry

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Neural processors have shown good results for detecting a certain character in a given input matrix. In this paper, a new idead to speed up the operation of neural processors for character detection is presented. Such processors are designed based on cross correlation in the frequency domain between the input matrix and the weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the searching process. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single faster neural processor. Furthermore, faster character detection is obtained by using parallel processing techniques to test the resulting sub-images at the same time using the same number of faster neural networks. In contrast to using only faster neural processors, the speed up ratio is increased with the size of the input image when using faster neural processors and image decomposition. Moreover, the problem of local subimage normalization in the frequency domain is solved. The effect of image normalization on the speed up ratio of character detection is discussed. Simulation results show that local subimage normalization through weight normalization is faster than subimage normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.

Keywords: Fast Character Detection, Neural Processors, Cross Correlation, Image Normalization, Parallel Processing.

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Authors: K. Biswas, U. H. Armin, S. M. J. Prodhan, J. A. Prithul, S. Sarker, F. Afrin

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Alzheimer’s disease (AD) (a progressive neurodegenerative disorder) is mostly predominant cause of dementia in the elderly. Prolonging the function of acetylcholine by inhibiting both acetylcholinesterase and butyrylcholinesterase is most effective treatment therapy of AD. Traditionally Pterocarpus santalinus L. is widely known for its medicinal use. In this study, in vitro acetylcholinesterase inhibitory activity was investigated and methanolic extract of the plant showed significant activity. To confirm this activity (in vivo), learning and memory enhancing effects were tested in mice. For the test, memory impairment was induced by scopolamine (cholinergic muscarinic receptor antagonist). Anti-amnesic effect of the extract was investigated by the passive avoidance task in mice. The study also includes brain acetylcholinesterase activity. Results proved that scopolamine induced cognitive dysfunction was significantly decreased by administration of the extract solution, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that bark extract of Pterocarpus santalinus can be better option for further studies on AD via their acetylcholinesterase inhibitory actions.

Keywords: Pterocarpus santalinus, cholinesterase inhibitor, passive avoidance, Alzheimer’s disease.

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