Search results for: fisher scoring method
Commenced in January 2007
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Edition: International
Paper Count: 18910

Search results for: fisher scoring method

17380 Beam, Column Joints Concrete in Seismic Zone

Authors: Khalifa Kherafa

Abstract:

This east project consists in studying beam–column joints concrete subjected to seismic loads. A bibliographical study was introduced to clarify the work undertaken by the researchers in the field during the three last decades and especially the two last year’s results which were to study for the determination of the method of calculating of transverse reinforcement in the various nodes of a structure. For application, the efforts in the posts el the beams of a building in R+4 in zone 3 were calculate according to the finite element method through the software .

Keywords: beam–column joints, cyclic loading, shearing force, damaged joint

Procedia PDF Downloads 410
17379 Item-Trait Pattern Recognition of Replenished Items in Multidimensional Computerized Adaptive Testing

Authors: Jianan Sun, Ziwen Ye

Abstract:

Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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17378 Optimization of Electrical Discharge Machining Parameters in Machining AISI D3 Tool Steel by Grey Relational Analysis

Authors: Othman Mohamed Altheni, Abdurrahman Abusaada

Abstract:

This study presents optimization of multiple performance characteristics [material removal rate (MRR), surface roughness (Ra), and overcut (OC)] of hardened AISI D3 tool steel in electrical discharge machining (EDM) using Taguchi method and Grey relational analysis. Machining process parameters selected were pulsed current Ip, pulse-on time Ton, pulse-off time Toff and gap voltage Vg. Based on ANOVA, pulse current is found to be the most significant factor affecting EDM process. Optimized process parameters are simultaneously leading to a higher MRR, lower Ra, and lower OC are then verified through a confirmation experiment. Validation experiment shows an improved MRR, Ra and OC when Taguchi method and grey relational analysis were used

Keywords: edm parameters, grey relational analysis, Taguchi method, ANOVA

Procedia PDF Downloads 283
17377 Parametric Study of Underground Opening Stability under Uncertainty Conditions

Authors: Aram Yakoby, Yossef H. Hatzor, Shmulik Pinkert

Abstract:

This work presents an applied engineering method for evaluating the stability of underground openings under conditions of uncertainty. The developed method is demonstrated by a comprehensive parametric study on a case of large-diameter vertical borehole stability analysis, with uncertainties regarding the in-situ stress distribution. To this aim, a safety factor analysis is performed for the stability of both supported and unsupported boreholes. In the analysis, we used analytic geomechanical calculations and advanced numerical modeling to evaluate the estimated stress field. In addition, the work presents the development of a boundary condition for the numerical model that fits the nature of the problem and yields excellent accuracy. The borehole stability analysis is studied in terms of (1) the stress ratio in the vertical and horizontal directions, (2) the mechanical properties and geometry of the support system, and (3) the parametric sensitivity. The method's results are studied in light of a real case study of an underground waste disposal site. The conclusions of this study focus on the developed method for capturing the parametric uncertainty, the definition of critical geological depths, the criteria for implementing structural support, and the effectiveness of further in-situ investigations.

Keywords: borehole stability, in-situ stress, parametric study, factor of safety

Procedia PDF Downloads 49
17376 E-learning: An Effective Approach for Enhancing Social and Behavior Change Communication Capacity in Bangladesh

Authors: Mohammad K. Abedin, Mohammad Shahjahan, Zeenat Sultana, Tawfique Jahan, Jesmin Akter

Abstract:

To strengthen social and behavior change communication (SBCC) capacity of Ministry of Health and Family Welfare (MoHFW) of the Government of Bangladesh, BCCP/BKMI developed two eLearning courses providing opportunities for professional development of SBCC Program Managers who have no access to training or refreshers training. The two eLearning courses – Message and Material Development (MMD) and Monitoring and Evaluation (MandE) of SBCC programs – went online in September 2015, where all users could register their participation so results could be monitored. Methodology: To assess the uses of these courses a randomly selected sample was collected to run a pre and post-test analyses and a phone survey were conducted. Systematic random sampling was used to select a sample of 75 MandE and 25 MMD course participants from a sampling frame of 179 and 51 respectively. Results: As of September 2016, more than 179 learners have completed the MandE course, and 49 learners have completed the MMD course. The users of these courses are program managers, university faculty members, and students. Encouraging results were revealed from the analysis of pre and post-test scores and a phone survey three months after course completion. Test scores suggested a substantial increase in knowledge. The pre-test scores findings suggested that about 19% learners scored high on the MandE. The post-test scores finding indicated a high score (92%) of the sample across 4 modules of MandE. For MMD course in pre-test scoring, 30% of the learners scored high, and 100% scored high at the post-test. It was found that all the learners in the phone survey have discussed the courses. Most of the sharing occurred with colleagues and friends, usually through face to face (70%) interaction. The learners reported that they did recommend the two courses to concerned people. About 67% MandE and 76% MMD learners stated that the concepts that they had to learn during the course were put into practice in their work settings. The respondents for both MandE and MMD courses have provided a valuable set of suggestions that would further strengthen the courses. Conclusions: The study showed that the initiative offered ample opportunities to build capacity in various ways in which the eLearning courses were used. It also highlighted the importance of scaling up these efforts to further strengthen the outcomes.

Keywords: e-learning course, message & material development, monitoring & evaluation, social and behavior change communication

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17375 Self-Supervised Learning for Hate-Speech Identification

Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

Procedia PDF Downloads 95
17374 Lane Detection Using Labeling Based RANSAC Algorithm

Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

Abstract:

In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

Procedia PDF Downloads 226
17373 An Improved Total Variation Regularization Method for Denoising Magnetocardiography

Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

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17372 The Impact of the Method of Extraction on 'Chemchali' Olive Oil Composition in Terms of Oxidation Index, and Chemical Quality

Authors: Om Kalthoum Sallem, Saidakilani, Kamiliya Ounaissa, Abdelmajid Abid

Abstract:

Introduction and purposes: Olive oil is the main oil used in the Mediterranean diet. Virgin olive oil is valued for its organoleptic and nutritional characteristics and is resistant to oxidation due to its high monounsaturated fatty acid content (MUFAs), and low polyunsaturates (PUFAs) and the presence of natural antioxidants such as phenols, tocopherols and carotenoids. The fatty acid composition, especially the MUFA content, and the natural antioxidants provide advantages for health. The aim of the present study was to examine the impact of method of extraction on the chemical profiles of ‘Chemchali’ olive oil variety, which is cultivated in the city of Gafsa, and to compare it with chetoui and chemchali varieties. Methods: Our study is a qualitative prospective study that deals with ‘Chemchali’ olive oil variety. Analyses were conducted during three months (from December to February) in different oil mills in the city of Gafsa. We have compared ‘Chemchali’ olive oil obtained by continuous method to this obtained by superpress method. Then we have analyzed quality index parameters, including free fatty acid content (FFA), acidity, and UV spectrophotometric characteristics and other physico-chemical data [oxidative stability, ß-carotene, and chlorophyll pigment composition]. Results: Olive oil resulting from super press method compared with continuous method is less acid(0,6120 vs. 0,9760), less oxydazible(K232:2,478 vs. 2,592)(k270:0,216 vs. 0,228), more rich in oleic acid(61,61% vs. 66.99%), less rich in linoleic acid(13,38% vs. 13,98 %), more rich in total chlorophylls pigments (6,22 ppm vs. 3,18 ppm ) and ß-carotene (3,128 mg/kg vs. 1,73 mg/kg). ‘Chemchali’ olive oil showed more equilibrated total content in fatty acids compared with the varieties ’Chemleli’ and ‘Chetoui’. Gafsa’s variety ’Chemlali’ have significantly less saturated and polyunsaturated fatty acids. Whereas it has a higher content in monounsaturated fatty acid C18:2, compared with the two other varieties. Conclusion: The use of super press method had benefic effects on general chemical characteristics of ‘Chemchali’ olive oil, maintaining the highest quality according to the ecocert legal standards. In light of the results obtained in this study, a more detailed study is required to establish whether the differences in the chemical properties of oils are mainly due to agronomic and climate variables or, to the processing employed in oil mills.

Keywords: olive oil, extraction method, fatty acids, chemchali olive oil

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17371 Obtaining of Nanocrystalline Ferrites and Other Complex Oxides by Sol-Gel Method with Participation of Auto-Combustion

Authors: V. S. Bushkova

Abstract:

It is well known that in recent years magnetic materials have received increased attention due to their properties. For this reason a significant number of patents that were published during the last decade are oriented towards synthesis and study of such materials. The aim of this work is to create and study ferrite nanocrystalline materials with spinel structure, using sol-gel technology with participation of auto-combustion. This method is perspective in that it is a cheap and low-temperature technique that allows for the fine control on the product’s chemical composition.

Keywords: magnetic materials, ferrites, sol-gel technology, nanocrystalline powders

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17370 Settlement Prediction for Tehran Subway Line-3 via FLAC3D and ANFIS

Authors: S. A. Naeini, A. Khalili

Abstract:

Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

Procedia PDF Downloads 216
17369 A Method of Drilling a Ground Using a Robotic Arm

Authors: Lotfi Beji, Laredj Benchikh

Abstract:

Underground tunnel face bolting and pipe umbrella reinforcement are one of the most challenging tasks in construction whether industrial or not, and infrastructures such as roads or pipelines. It is one of the first sectors of economic activity in the world. Through a variety of soil and rock, a cyclic Conventional Tunneling Method (CTM) remains the best one for projects with highly variable ground conditions or shapes. CTM is the only alternative for the renovation of existing tunnels and creating emergency exit. During the drilling process, a wide variety of non-desired vibrations may arise, and a method using a robot arm is proposed. The main kinds of drilling through vibration here is the bit-bouncing phenomenon (resonant axial vibration). Hence, assisting the task by a robot arm may play an important role on drilling performances and security. We propose to control the axial-vibration phenomenon along the drillstring at a practical resonant frequency, and embed a Resonant Sonic Drilling Head (RSDH) as a robot end effector for drilling. Many questionable industry drilling criteria and stability are discussed in this paper.

Keywords: drilling, resonant vibration, robot arm, control

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17368 Fast Tumor Extraction Method Based on Nl-Means Filter and Expectation Maximization

Authors: Sandabad Sara, Sayd Tahri Yassine, Hammouch Ahmed

Abstract:

The development of science has allowed computer scientists to touch the medicine and bring aid to radiologists as we are presenting it in our article. Our work focuses on the detection and localization of tumors areas in the human brain; this will be a completely automatic without any human intervention. In front of the huge volume of MRI to be treated per day, the radiologist can spend hours and hours providing a tremendous effort. This burden has become less heavy with the automation of this step. In this article we present an automatic and effective tumor detection, this work consists of two steps: the first is the image filtering using the filter Nl-means, then applying the expectation maximization algorithm (EM) for retrieving the tumor mask from the brain MRI and extracting the tumor area using the mask obtained from the second step. To prove the effectiveness of this method multiple evaluation criteria will be used, so that we can compare our method to frequently extraction methods used in the literature.

Keywords: MRI, Em algorithm, brain, tumor, Nl-means

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17367 New Off-Line SPE-GC-MS/MS Method for Determination of Mineral Oil Saturated Hydrocarbons/Mineral Oil Hydrocarbons in Animal Feed, Foods, Infant Formula and Vegetable Oils

Authors: Ovanes Chakoyan

Abstract:

MOH (mineral oil hydrocarbons), which consist of mineral oil saturated hydrocarbons(MOSH) and mineral oil aromatic hydrocarbons(MOAH), are present in various products such as vegetable oils, animal feed, foods, and infant formula. Contamination of foods with mineral oil hydrocarbons, particularly mineral oil aromatic hydrocarbons(MOAH), exhibiting carcinogenic, mutagenic, and hormone-disruptive effects. Identifying toxic substances among the many thousands comprising mineral oils in food samples is a difficult analytical challenge. A method based on an offline-solid phase extraction approach coupled with gas chromatography-triple quadrupole(GC-MS/MS) was developed for the determination of MOSH/MOAH in various products such as vegetable oils, animal feed, foods, and infant formula. A glass solid phase extraction cartridge loaded with 7 g of activated silica gel impregnated with 10 % silver nitrate for removal of olefins and lipids. The MOSH/MOAH fractions were eluated with hexane and hexane: dichloromethane : toluene, respectively. Each eluate was concentrated to 50 µl in toluene and injected on splitless mode into GC-MS/MS. Accuracy of the method was estimated as measurement of recovery of spiked oil samples at 2.0, 15.0, and 30.0 mg kg -1, and recoveries varied from 85 to 105 %. The method was applied to the different types of samples (sunflower meal, chocolate ships, santa milk chocolate, biscuits, infant milk, cornflakes, refined sunflower oil, crude sunflower oil), detecting MOSH up to 56 mg/kg and MOAH up to 5 mg/kg. The limit of quantification(LOQ) of the proposed method was estimated at 0.5 mg/kg and 0.3 mg/kg for MOSH and MOAH, respectively.

Keywords: MOSH, MOAH, GC-MS/MS, foods, solid phase extraction

Procedia PDF Downloads 64
17366 A High Performance Piano Note Recognition Scheme via Precise Onset Detection and Segmented Short-Time Fourier Transform

Authors: Sonali Banrjee, Swarup Kumar Mitra, Aritra Acharyya

Abstract:

A piano note recognition method has been proposed by the authors in this paper. The authors have used a comprehensive method for onset detection of each note present in a piano piece followed by segmented short-time Fourier transform (STFT) for the identification of piano notes. The performance evaluation of the proposed method has been carried out in different harsh noisy environments by adding different levels of additive white Gaussian noise (AWGN) having different signal-to-noise ratio (SNR) in the original signal and evaluating the note detection error rate (NDER) of different piano pieces consisting of different number of notes at different SNR levels. The NDER is found to be remained within 15% for all piano pieces under consideration when the SNR is kept above 8 dB.

Keywords: AWGN, onset detection, piano note, STFT

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17365 Investigation of Long-Term Thermal Insulation Performance of Vacuum Insulation Panels with Various Enveloping Methods

Authors: Inseok Yeo, Tae-Ho Song

Abstract:

To practically apply vacuum insulation panels (VIPs) to buildings or home appliances, VIPs have demanded long-term lifespan with outstanding insulation performance. Service lives of VIPs enveloped with Al-foil and three-layer Al-metallized envelope are calculated. For Al-foil envelope, the service life is longer but edge conduction is too large compared with the Al metallized envelope. To increase service life even more, the proposed double enveloping method and metal-barrier-added enveloping method are further analyzed. The service lives of the VIP to employ two enveloping methods are calculated. Also, pressure increase and thermal insulation performance characteristics are investigated. For the metal- barrier-added enveloping method, effective thermal conductivity increase with time is close to that of Al-foil envelope, especially, for getter-inserted VIPs. For the double enveloping method, if water vapor is perfectly adsorbed, the effect of service life enhancement becomes much greater. From these methods, the VIP can be guaranteed for the service life of more than 20 years.

Keywords: vacuum insulation panels, service life, double enveloping, metal-barrier-added enveloping, edge conduction

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17364 An Erudite Technique for Face Detection and Recognition Using Curvature Analysis

Authors: S. Jagadeesh Kumar

Abstract:

Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

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17363 Free Vibration Analysis of Pinned-Pinned and Clamped-Clamped Equal Strength Columns under Self-Weight and Tip Force Using Differential Quadrature Method

Authors: F. Waffo Tchuimmo, G. S. Kwandio Dongoua, C. U. Yves Mbono Samba, O. Dafounansou, L. Nana

Abstract:

The strength criterion is an important condition of great interest to guarantee the stability of the structural elements. The present work is based on the study of the free vibration of Euler’s Bernoulli column of equal strength in compression while considering its own weight and the axial load in compression and tension subjected to symmetrical boundary conditions. We use the differential quadrature method to investigate the first fifth naturals frequencies parameters of the column according to the different forms of geometrical sections. The results of this work give help in making a judicious choice of type of cross-section and a better boundary condition to guarantee good stability of this type of column in civil constructions.

Keywords: free vibration, equal strength, self-weight, tip force, differential quadrature method

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17362 Optimal Feedback Linearization Control of PEM Fuel Cell

Authors: E. Shahsavari, R. Ghasemi, A. Akramizadeh

Abstract:

This paper presents a new method to design nonlinear feedback linearization controller for polymer electrolyte membrane fuel cells (PEMFCs). A nonlinear controller is designed based on nonlinear model to prolong the stack life of PEM fuel cells. Since it is known that large deviations between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell, feedback linearization is applied to the PEM fuel cell system so that the deviation can be kept as small as possible during disturbances or load variations. To obtain an accurate feedback linearization controller, tuning the linear parameters are always important. So in proposed study NSGA_II method was used to tune the designed controller in aim to decrease the controller tracking error. The simulation result showed that the proposed method tuned the controller efficiently.

Keywords: nonlinear dynamic model, polymer electrolyte membrane fuel cells, feedback linearization, optimal control, NSGA_II

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17361 Application of Optical Method for Calcul of Deformed Object Samples

Authors: R. Daira

Abstract:

The electronic speckle interferometry technique used to measure the deformations of scatterers process is based on the subtraction of interference patterns. A speckle image is first recorded before deformation of the object in the RAM of a computer, after a second deflection. The square of the difference between two images showing correlation fringes observable in real time directly on monitor. The interpretation these fringes to determine the deformation. In this paper, we present experimental results of deformation out of the plane of two samples in aluminum, electronic boards and stainless steel.

Keywords: optical method, holography, interferometry, deformation

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17360 Stator Short-Circuits Fault Diagnosis in Induction Motors

Authors: K. Yahia, M. Sahraoui, A. Guettaf

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental results, show the effectiveness of the used method.

Keywords: induction motors (IMs), inter-turn short-circuits diagnosis, discrete wavelet transform (DWT), Current Park’s Vector Modulus (CPVM)

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17359 Development and Validation of a HPLC Method for 6-Gingerol and 6-Shogaol in Joint Pain Relief Gel Containing Ginger (Zingiber officinale)

Authors: Tanwarat Kajsongkram, Saowalux Rotamporn, Sirinat Limbunruang, Sirinan Thubthimthed.

Abstract:

High-Performance Liquid Chromatography (HPLC) method was developed and validated for simultaneous estimation of 6-Gingerol(6G) and 6-Shogaol(6S) in joint pain relief gel containing ginger extract. The chromatographic separation was achieved by using C18 column, 150 x 4.6mm i.d., 5μ Luna, mobile phase containing acetonitrile and water (gradient elution). The flow rate was 1.0 ml/min and the absorbance was monitored at 282 nm. The proposed method was validated in terms of the analytical parameters such as specificity, accuracy, precision, linearity, range, limit of detection (LOD), limit of quantification (LOQ), and determined based on the International Conference on Harmonization (ICH) guidelines. The linearity ranges of 6G and 6S were obtained over 20-60 and 6-18 µg/ml respectively. Good linearity was observed over the above-mentioned range with linear regression equation Y= 11016x- 23778 for 6G and Y = 19276x-19604 for 6S (x is concentration of analytes in μg/ml and Y is peak area). The value of correlation coefficient was found to be 0.9994 for both markers. The limit of detection (LOD) and limit of quantification (LOQ) for 6G were 0.8567 and 2.8555 µg/ml and for 6S were 0.3672 and 1.2238 µg/ml respectively. The recovery range for 6G and 6S were found to be 91.57 to 102.36 % and 84.73 to 92.85 % for all three spiked levels. The RSD values from repeated extractions for 6G and 6S were 3.43 and 3.09% respectively. The validation of developed method on precision, accuracy, specificity, linearity, and range were also performed with well-accepted results.

Keywords: ginger, 6-gingerol, HPLC, 6-shogaol

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17358 Evaluation of Corrosion Property of Aluminium-Zirconium Dioxide (AlZrO2) Nanocomposites

Authors: M. Ramachandra, G. Dilip Maruthi, R. Rashmi

Abstract:

This paper aims to study the corrosion property of aluminum matrix nanocomposite of an aluminum alloy (Al-6061) reinforced with zirconium dioxide (ZrO2) particles. The zirconium dioxide particles are synthesized by solution combustion method. The nanocomposite materials are prepared by mechanical stir casting method, varying the percentage of n-ZrO2 (2.5%, 5% and 7.5% by weight). The corrosion behavior of base metal (Al-6061) and Al/ZrO2 nanocomposite in seawater (3.5% NaCl solution) is measured using the potential control method. The corrosion rate is evaluated by Tafel extrapolation technique. The corrosion potential increases with the increase in wt.% of n-ZrO2 in the nanocomposite which means the decrease in corrosion rate. It is found that on addition of n-ZrO2 particles to the aluminum matrix, the corrosion rate has decreased compared to the base metal.

Keywords: Al6061 alloy, corrosion, solution, stir casting, combustion, potentiostat, zirconium dioxide

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17357 Meteosat Second Generation Image Compression Based on the Radon Transform and Linear Predictive Coding: Comparison and Performance

Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

Abstract:

Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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17356 A Study of General Attacks on Elliptic Curve Discrete Logarithm Problem over Prime Field and Binary Field

Authors: Tun Myat Aung, Ni Ni Hla

Abstract:

This paper begins by describing basic properties of finite field and elliptic curve cryptography over prime field and binary field. Then we discuss the discrete logarithm problem for elliptic curves and its properties. We study the general common attacks on elliptic curve discrete logarithm problem such as the Baby Step, Giant Step method, Pollard’s rho method and Pohlig-Hellman method, and describe in detail experiments of these attacks over prime field and binary field. The paper finishes by describing expected running time of the attacks and suggesting strong elliptic curves that are not susceptible to these attacks.c

Keywords: discrete logarithm problem, general attacks, elliptic curve, prime field, binary field

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17355 Preliminary dosimetric Evaluation of a New Therapeutic 177LU Complex for Human Based on Biodistribution Data in Rats

Authors: H. Yousefnia, S. Zolghadri, A. Golabi Dezfuli

Abstract:

Tris (1,10-phenanthroline) lanthanum(III)] trithiocyanate is a new compound that has shown to stop DNA synthesis in CCRF-CEM and Ehrlich ascites cells leading to a cell cycle arrest in G0/G1. One other important property of the phenanthroline nucleus is its ability to act as a triplet-state photosensitizer especially in complexes with lanthanides. In Nowadays, the radiation dose assessment resource (RADAR) method is known as the most common method for absorbed dose calculation. 177Lu was produced by irradiation of a natural Lu2O3 target at a thermal neutron flux of approximately 4 × 1013 n/cm2•s. 177Lu-PL3 was prepared in the optimized condition. The radiochemical yield was checked by ITLC method. The biodistribution of the complex was investigated by intravenously injection to wild-type rats via their tail veins. In this study, the absorbed dose of 177Lu-PL3 to human organs was estimated by RADAR method. 177Lu was prepared with a specific activity of 2.6-3 GBq.mg-1 and radionuclide purity of 99.98 %. The 177Lu-PL3 complex can prepare with high radiochemical yield (> 99 %) at optimized conditions. The results show that liver and spleen have received the highest absorbed dose of 1.051 and 0.441 mSv/MBq, respectivley. The absorbed dose values for these two dose-limiting tissues suggest more biological studies special in tumor-bearing animals.

Keywords: internal dosimetry, Lutetium-177, radar, animals

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17354 Particle Size Analysis of Itagunmodi Southwestern Nigeria Alluvial Gold Ore Sample by Gaudin Schumann Method

Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

Abstract:

Mining of alluvial gold ore by artisanal miners has been going on for decades at Itagunmodi, Southwestern Nigeria. In order to optimize the traditional panning gravity separation method commonly used in the area, a mineral particle size analysis study is critical. This study analyzed alluvial gold ore samples collected at identified five different locations in the area with a view to determine the ore particle size distributions. 500g measured of as-received alluvial gold ore sample was introduced into the uppermost sieve of an electrical sieve shaker consisting of sieves arranged in the order of decreasing nominal apertures of 5600μm, 3350μm, 2800μm, 355μm, 250μm, 125μm and 90μm, and operated for 20 minutes. The amount of material retained on each sieve was measured and tabulated for analysis. A screen analysis graph using the Gaudin Schuman method was drawn for each of the screen tests on the alluvial samples. The study showed that the percentages of fine particle size -125+90 μm fraction were 45.00%, 36.00%, 39.60%, 43.00% and 36.80% for the selected samples. These primary ore characteristic results provide reference data for the alluvial gold ore processing method selection, process performance measurement and optimization.

Keywords: alluvial gold ore, sieve shaker, particle size, Gaudin Schumann

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17353 Neurocognitive and Executive Function in Cocaine Addicted Females

Authors: Gwendolyn Royal-Smith

Abstract:

Cocaine ranks as one of the world’s most addictive and commonly abused stimulant drugs. Recent evidence indicates that the abuse of cocaine has risen so quickly among females that this group now accounts for about 40 percent of all users in the United States. Neuropsychological studies have demonstrated that specific neural activation patterns carry higher risks for neurocognitive and executive function in cocaine addicted females thereby increasing their vulnerability for poorer treatment outcomes and more frequent post-treatment relapse when compared to males. This study examined secondary data with a convenience sample of 164 cocaine addicted male and females to assess neurocognitive and executive function. The principal objective of this study was to assess whether individual performance on the Stroop Word Color Task is predictive of treatment success by gender. A second objective of the study evaluated whether individual performance employing neurocognitive measures including the Stroop Word-Color task, the Rey Auditory Verbal Learning Test (RALVT), the Iowa Gambling Task, the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale (FrSBE) test demonstrated differences in neurocognitive and executive function performance by gender. Logistic regression models were employed utilizing a covariate adjusted model application. Initial analyses of the Stroop Word color tasks indicated significant differences in the performance of males and females, with females experiencing more challenges in derived interference reaction time and associate recall ability. In early testing including the Rey Auditory Verbal Learning Test (RALVT), the number of advantageous vs disadvantageous cards from the Iowa Gambling Task, the number of perseverance errors from the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale, results were mixed with women scoring lower in multiple indicators in both neurocognitive and executive function.

Keywords: cocaine addiction, gender, neuropsychology, neurocognitive, executive function

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17352 An Efficient Separation for Convolutive Mixtures

Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we use a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation, estimates, full-band, mixtures, sub-band

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17351 Numerical Pricing of Financial Options under Irrational Exercise Times and Regime-Switching Models

Authors: Mohammad Saber Rohi, Saghar Heidari

Abstract:

In this paper, we studied the pricing problem of American options under a regime-switching model with the possibility of a non-optimal exercise policy (early or late exercise time) which is called an irrational strategy. For this, we consider a Markovmodulated model for the dynamic of the underlying asset as an alternative model to the classical Balck-Scholes-Merton model (BSM) and an intensity-based model for the irrational strategy, to provide more realistic results for American option prices under the irrational behavior in real financial markets. Applying a partial differential equation (PDE) approach, the pricing problem of American options under regime-switching models can be formulated as coupled PDEs. To solve the resulting systems of PDEs in this model, we apply a finite element method as the numerical solving procedure to the resulting variational inequality. Under some appropriate assumptions, we establish the stability of the method and compare its accuracy to some recent works to illustrate the suitability of the proposed model and the accuracy of the applied numerical method for the pricing problem of American options under the regime-switching model with irrational behaviors.

Keywords: irrational exercise strategy, rationality parameter, regime-switching model, American option, finite element method, variational inequality

Procedia PDF Downloads 62