Search results for: feature detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4614

Search results for: feature detection

954 Prenatal Diagnosis of Beta Thalassemia Intermedia in Vietnamese Family: Case Report

Authors: Ha T. T. Ly, Truc B. Truc, Hai N. Truong, Mai P. T. Nguyen, Ngoc D. Ngo, Khanh V. Tran, Hai T. Le

Abstract:

Beta thalassemia is one of the most common inherited blood disorders, which is characterized by decreased or absent in beta globin expression. Patients with Beta thalassemia whose anemia is not so severe as to necessitate transfusions are said to have thalassemia intermedia. Objective: The goal of this study is prenatal diagnosis for pregnancy woman with Beta thalassemia intermedia and her husband with Beta thalassemia carrier at high risk of Beta thalassemia major in Northern of Vietnam. Material and method: The family has a 6 years-old compound heterozygous thalassemia major for CD71/72(+A) and Hbb:c. -78A>G/nt-28(A>G) male child. The father was heterozygous for CD71/72(+A) mutation which is Beta plus type and the mother was compound heterozygosity of two different variants, namely, Hbb: c. -78A>G/nt-28(A>G) and CD26(A-G) HbE. Prenatal Beta thalassemia mutation detection in fetal DNA was carried out using multiplex Amplification-refractory mutation system ARMS-PCR and confirmed by direct Sanger-sequencing Hbb gene. Prenatal diagnoses were perfomed by amniotic fluid sampling from pregnant woman in the 16-18th week of pregnancy after the genotypes of parents of the probands were identified. Result: When amniotic fluid sample was analyzed for Beta globin gene (Hbb), we found that the genotype is heterozygous for CD71/72(+A) and CD26(A-G) HbE. This genotype is different from the 1st child of this family. Conclusion: Prenatal diagnosis helps the parents to know the genotype and the thalassemia status of the fetus, so they can have early decision on their pregnancy. Genetic diagnosis provided a useful method in diagnosis for familial members in pedigree, genetic counseling and prenatal diagnosis.

Keywords: beta thalassemia intermedia, Hbb gene, pedigree, prenatal diagnosis

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953 Case-Based Reasoning Application to Predict Geological Features at Site C Dam Construction Project

Authors: Shahnam Behnam Malekzadeh, Ian Kerr, Tyson Kaempffer, Teague Harper, Andrew Watson

Abstract:

The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and bedding planes at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including bedding plane elevations and coordinates. Thirteen (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ±55cm, while the actual results showed that 69% of predicted elevations were within ±79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ±99cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: case-based reasoning, geological feature, geology, piezometer, pressure sensor, core logging, dam construction

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952 Use Multiphysics Simulations and Resistive Pulse Sensing to Study the Effect of Metal and Non-Metal Nanoparticles in Different Salt Concentration

Authors: Chun-Lin Chiang, Che-Yen Lee, Yu-Shan Yeh, Jiunn-Haur Shaw

Abstract:

Wafer fabrication is a critical part of the semiconductor process, when the finest linewidth with the improvement of technology continues to decline and the structure development from 2D towards to 3D. The nanoparticles contained in the slurry or in the ultrapure water which used for cleaning have a large influence on the manufacturing process. Therefore, semiconductor industry is hoping to find a viable method for on-line detection the nanoparticles size and concentration. The resistive pulse sensing technology is one of the methods that may cover this question. As we know that nanoparticles properties of material differ significantly from their properties at larger length scales. So, we want to clear that the metal and non-metal nanoparticles translocation dynamic when we use the resistive pulse sensing technology. In this study we try to use the finite element method that contains three governing equations to do multiphysics coupling simulations. The Navier-Stokes equation describes the laminar motion, the Nernst-Planck equation describes the ion transport, and the Poisson equation describes the potential distribution in the flow channel. To explore that the metal nanoparticles and the non-metal nanoparticles in different concentration electrolytes, through the nanochannel caused by ion current changes. Then the reliability of the simulation results was verified by resistive pulse sensing test. The existing results show that the lower ion concentration, the greater effect of nanoparticles on the ion concentration in the nanochannel. The conductive spikes are correlated with nanoparticles surface charge. Then we can be concluded that in the resistive pulse sensing technique, the ion concentration in the nanochannel and nanoparticle properties are important for the translocation dynamic, and they have the interactions.

Keywords: multiphysics simulations, resistive pulse sensing, nanoparticles, nanochannel

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951 Local Interpretable Model-agnostic Explanations (LIME) Approach to Email Spam Detection

Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

Abstract:

The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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950 Object-Scene: Deep Convolutional Representation for Scene Classification

Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

Abstract:

Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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949 Effect of Labisia pumila var. alata with a Structured Exercise Program in Women with Polycystic Ovarian Syndrome

Authors: D. Maryama AG. Daud, Zuliana Bacho, Stephanie Chok, DG. Mashitah PG. Baharuddin, Mohd Hatta Tarmizi, Nathira Abdul Majeed, Helen Lasimbang

Abstract:

Lifestyle, physical activity, food intake, genetics and medication are contributing factors for people getting obese. Which in some of the obese people were a low or non-responder to exercise. And obesity is very common clinical feature in women affected by Polycystic Ovarian Syndrome (PCOS). Labisia pumila var. alata (LP) is a local herb which had been widely used by Malay women in treating menstrual irregularities, painful menstruation and postpartum well-being. Therefore, this study was carried out to investigate the effect of LP with a structured exercise program on anthropometric, body composition and physical fitness performance of PCOS patients. By using a single blind and parallel study design, where by subjects were assigned into a 16-wk structured exercise program (3 times a week) interventions; (LP and exercise; LPE, and exercise only; E). All subjects in the LPE group were prescribed 200mg LP; once a day, for 16 weeks. The training heart rate (HR) was monitored based on a percentage of the maximum HR (HRmax) achieved during submaximal exercise test that was conducted at wk-0 and wk-8. The progression of aerobic exercise intensity from 25–30 min at 60 – 65% HRmax during the first week to 45 min at 75–80% HRmax by the end of this study. Anthropometric (body weight, Wt; waist circumference, WC; and hip circumference, HC), body composition (fat mass, FM; percentage body fat, %BF; Fat Free Mass, FFM) and physical fitness performance (push up to failure, PU; 1-minute Sit Up, SU; and aerobic step test, PVO2max) were measured at wk-0, wk-4, wk-8, wk-12, and wk-16. This study found that LP does not have a significant effect on body composition, anthropometric and physical fitness performance of PCOS patients underwent a structured exercise program. It means LP does not improve exercise responses of PCOS patients towards anthropometric, body composition and physical fitness performance. The overall data shows exercise responses of PCOS patients is by increasing their aerobic endurance and muscle endurance performances, there is a significant reduction in FM, PBF, HC, and Wt significantly. Therefore, exercise program for PCOS patients have to focus on aerobic fitness, and muscle endurance.

Keywords: polycystic ovarian syndrome, Labisia pumila var. alata, body composition, aerobic endurance, muscle endurance, anthropometric

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948 Development of a Turbulent Boundary Layer Wall-pressure Fluctuations Power Spectrum Model Using a Stepwise Regression Algorithm

Authors: Zachary Huffman, Joana Rocha

Abstract:

Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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947 Chemical Characterization and Prebiotic Effect of Water-Soluble Polysaccharides from Zizyphus lotus Leaves

Authors: Zakaria Boual, Abdellah Kemassi, Toufik Chouana, Philippe Michaud, Mohammed Didi Ould El Hadj

Abstract:

In order to investigate the prebiotic potential of oligosaccharides prepared by chemical hydrolysis of water-soluble polysaccharides (WSP) from Zizyphus lotus leaves, the effect of oligosaccharides on bacterial growth was studied. The chemical composition of WSP was evaluated by colorimetric assays revealed the average values: 7.05±0.73% proteins and 86.21±0.74% carbohydrates, among them 64.81±0.42% are neutral sugar and the rest 16.25±1.62% are uronic acids. The characterization of monosaccharides was determined by high performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD) was found to be composed of galactose (23.95%), glucose (21.30%), rhamnose (20.28%), arabinose (9.55%), and glucuronic acid (22.95%). The effects of oligosaccharides on the growth of lactic acid bacteria were compared with those of fructo-oligosaccharide (RP95). The oligosaccharides concentration was 1g/L of man rogosa sharpe broth. Bacterial growth was assessed during 2, 4.5, 6.5, 9, 12, 16 and 24 h by measuring the optical density of the cultures at 600 nm (OD600) and pH values. During fermentation, pH in broth cultures decreased from 6.7 to 5.87±0.15. The enumeration of lactic acid bacteria indicated that oligosaccharides led to a significant increase in bacteria (P≤0.05) compared to the control. The fermentative metabolism appeared to be faster on RP95 than on oligosaccharides from Zizyphus lotus leaves. Both RP95 and oligosaccharides showed clear prebiotic effects, but had differences in fermentation kinetics because of to the different degree of polymerization. This study shows the prebiotic effectiveness of oligosaccharides, and provides proof for the selection of leaves of Zizyphus lotus for use as functional food ingredients.

Keywords: Zizyphus lotus, polysaccharides, characterization, prebiotic effects

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946 Numerical Modelling of Skin Tumor Diagnostics through Dynamic Thermography

Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

Abstract:

Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

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945 Regression-Based Approach for Development of a Cuff-Less Non-Intrusive Cardiovascular Health Monitor

Authors: Pranav Gulati, Isha Sharma

Abstract:

Hypertension and hypotension are known to have repercussions on the health of an individual, with hypertension contributing to an increased probability of risk to cardiovascular diseases and hypotension resulting in syncope. This prompts the development of a non-invasive, non-intrusive, continuous and cuff-less blood pressure monitoring system to detect blood pressure variations and to identify individuals with acute and chronic heart ailments, but due to the unavailability of such devices for practical daily use, it becomes difficult to screen and subsequently regulate blood pressure. The complexities which hamper the steady monitoring of blood pressure comprises of the variations in physical characteristics from individual to individual and the postural differences at the site of monitoring. We propose to develop a continuous, comprehensive cardio-analysis tool, based on reflective photoplethysmography (PPG). The proposed device, in the form of an eyewear captures the PPG signal and estimates the systolic and diastolic blood pressure using a sensor positioned near the temporal artery. This system relies on regression models which are based on extraction of key points from a pair of PPG wavelets. The proposed system provides an edge over the existing wearables considering that it allows for uniform contact and pressure with the temporal site, in addition to minimal disturbance by movement. Additionally, the feature extraction algorithms enhance the integrity and quality of the extracted features by reducing unreliable data sets. We tested the system with 12 subjects of which 6 served as the training dataset. For this, we measured the blood pressure using a cuff based BP monitor (Omron HEM-8712) and at the same time recorded the PPG signal from our cardio-analysis tool. The complete test was conducted by using the cuff based blood pressure monitor on the left arm while the PPG signal was acquired from the temporal site on the left side of the head. This acquisition served as the training input for the regression model on the selected features. The other 6 subjects were used to validate the model by conducting the same test on them. Results show that the developed prototype can robustly acquire the PPG signal and can therefore be used to reliably predict blood pressure levels.

Keywords: blood pressure, photoplethysmograph, eyewear, physiological monitoring

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944 A Retrospective Study on the Age of Onset for Type 2 Diabetes Diagnosis

Authors: Mohamed A. Hammad, Dzul Azri Mohamed Noor, Syed Azhar Syed Sulaiman, Majed Ahmed Al-Mansoub, Muhammad Qamar

Abstract:

There is a progressive increase in the prevalence of early onset Type 2 diabetes mellitus. Early detection of Type 2 diabetes enhances the length and/or quality of life which might result from a reduction in the severity, frequency or prevent or delay of its long-term complications. The study aims to determine the onset age for the first diagnosis of Type 2 diabetes mellitus. A retrospective study conducted in the endocrine clinic at Hospital Pulau Pinang in Penang, Malaysia, January- December 2016. Records of 519 patients with Type 2 diabetes mellitus were screened to collect demographic data and determine the age of first-time diabetes mellitus diagnosis. Patients classified according to the age of diagnosis, gender, and ethnicity. The study included 519 patients with age (55.6±13.7) years, female 265 (51.1%) and male 254 (48.9%). The ethnicity distribution was Malay 191 (36.8%), Chinese 189 (36.4%) and Indian 139 (26.8%). The age of Type 2 diabetes diagnosis was (42±14.8) years. The female onset of diabetes mellitus was at age (41.5±13.7) years, while male (42.6±13.7) years. Distribution of diabetic onset by ethnicity was Malay at age (40.7±13.7) years, Chinese (43.2±13.7) years and Indian (42.3±13.7) years. Diabetic onset was classified by age as follow; ≤20 years’ cohort was 33 (6.4%) cases. Group >20- ≤40 years was 190 (36.6%) patients, and category >40- ≤60 years was 270 (52%) subjects. On the other hand, the group >60 years was 22 (4.2%) patients. The range of diagnosis was between 10 and 73 years old. Conclusion: Malay and female have an earlier onset of diabetes than Indian, Chinese and male. More than half of the patients had diabetes between 40 and 60 years old. Diabetes mellitus is becoming more common in younger age <40 years. The age at diagnosis of Type 2 diabetes mellitus has decreased with time.

Keywords: age of onset, diabetes diagnosis, diabetes mellitus, Malaysia, outpatients, type 2 diabetes, retrospective study

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943 Offline High Voltage Diagnostic Test Findings on 15MVA Generator of Basochhu Hydropower Plant

Authors: Suprit Pradhan, Tshering Yangzom

Abstract:

Even with availability of the modern day online insulation diagnostic technologies like partial discharge monitoring, the measurements like Dissipation Factor (tanδ), DC High Voltage Insulation Currents, Polarization Index (PI) and Insulation Resistance Measurements are still widely used as a diagnostic tools to assess the condition of stator insulation in hydro power plants. To evaluate the condition of stator winding insulation in one of the generators that have been operated since 1999, diagnostic tests were performed on the stator bars of 15 MVA generators of Basochhu Hydropower Plant. This paper presents diagnostic study done on the data gathered from the measurements which were performed in 2015 and 2016 as part of regular maintenance as since its commissioning no proper aging data were maintained. Measurement results of Dissipation Factor, DC High Potential tests and Polarization Index are discussed with regard to their effectiveness in assessing the ageing condition of the stator insulation. After a brief review of the theoretical background, the strengths of each diagnostic method in detecting symptoms of insulation deterioration are identified. The interesting results observed from Basochhu Hydropower Plant is taken into consideration to conclude that Polarization Index and DC High Voltage Insulation current measurements are best suited for the detection of humidity and contamination problems and Dissipation Factor measurement is a robust indicator of long-term ageing caused by oxidative degradation.

Keywords: dissipation Factor (tanδ), polarization Index (PI), DC High Voltage Insulation Current, insulation resistance (IR), Tan Delta Tip-Up, dielectric absorption ratio

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942 Polymeric Sustained Biodegradable Patch Formulation for Wound Healing

Authors: Abhay Asthana, Gyati Shilakari Asthana

Abstract:

It’s the patient compliance and stability in combination with controlled drug delivery and biocompatibility that forms the core feature in present research and development of sustained biodegradable patch formulation intended for wound healing. The aim was to impart sustained degradation, sterile formulation, significant folding endurance, elasticity, biodegradability, bio-acceptability and strength. The optimized formulation was developed using component including polymers including Hydroxypropyl methyl cellulose, Ethylcellulose, and Gelatin, and Citric Acid PEG Citric acid (CPEGC) triblock dendrimers and active Curcumin. Polymeric mixture dissolved in geometric order in suitable medium through continuous stirring under ambient conditions. With continued stirring Curcumin was added with aid of DCM and Methanol in optimized ratio to get homogenous dispersion. The dispersion was sonicated with optimum frequency and for given time and later casted to form a patch form. All steps were carried out under under strict aseptic conditions. The formulations obtained in the acceptable working range were decided based on thickness, uniformity of drug content, smooth texture and flexibility and brittleness. The patch kept on stability using butter paper in sterile pack displayed folding endurance in range of 20 to 23 times without any evidence of crack in an optimized formulation at room temperature (RT) (24 ± 2°C). The patch displayed acceptable parameters after stability study conducted in refrigerated conditions (8±0.2°C) and at RT (24 ± 2°C) upto 90 days. Further, no significant changes were observed in critical parameters such as elasticity, biodegradability, drug release and drug content during stability study conducted at RT 24±2°C for 45 and 90 days. The drug content was in range 95 to 102%, moisture content didn’t exceeded 19.2% and patch passed the content uniformity test. Percentage cumulative drug release was found to be 80% in 12h and matched the biodegradation rate as drug release with correlation factor R2>0.9. The biodegradable patch based formulation developed shows promising results in terms of stability and release profiles.

Keywords: sustained biodegradation, wound healing, polymers, stability

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941 DLtrace: Toward Understanding and Testing Deep Learning Information Flow in Deep Learning-Based Android Apps

Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

Abstract:

With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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940 Synthesis and Preparation of Carbon Ferromagnetic Nanocontainers for Cancer Therapy

Authors: L. Szymanski, Z. Kolacinski, Z. Kamiński, G. Raniszewski, J. Fraczyk, L. Pietrzak

Abstract:

In the article the development and demonstration of method and the model device for hyperthermic selective destruction of cancer cells are presented. This method was based on the synthesis and functionalization of carbon nanotubes serving as ferromagnetic material nano containers. Methodology of the production carbon - ferromagnetic nanocontainers includes: the synthesis of carbon nanotubes, chemical and physical characterization, increasing the content of ferromagnetic material and biochemical functionalization involving the attachment of the key addresses. Biochemical functionalization of ferromagnetic nanocontainers is necessary in order to increase the binding selectively with receptors presented on the surface of tumour cells. Multi-step modification procedure was finally used to attach folic acid on the surface of ferromagnetic nanocontainers. Folic acid is ligand of folate receptors which is overexpresion in tumor cells. The presence of ligand should ensure the specificity of the interaction between ferromagnetic nanocontainers and tumor cells. The chemical functionalization contains several step: oxidation reaction, transformation of carboxyl groups into more reactive ester or amide groups, incorporation of spacer molecule (linker), attaching folic acid. Activation of carboxylic groups was prepared with triazine coupling reagent (preparation of superactive ester attached on the nanocontainers). The spacer molecules were designed and synthesized. In order to ensure biocompatibillity of linkers they were built from amino acids or peptides. Spacer molecules were synthesized using the SPPS method. Synthesis was performed on 2-Chlorotrityl resin. The linker important feature is its length. Due to that fact synthesis of peptide linkers containing from 2 to 4 -Ala- residues was carried out. Independent synthesis of the conjugate of foilic acid with 6-aminocaproic acid was made. Final step of synthesis was connecting conjugat with spacer molecules and attaching it on the ferromagnetic nanocontainer surface. This article contains also information about special CVD and microvave plasma system to produce nanotubes and ferromagnetic nanocontainers. The first tests in the device for hyperthermal RF generator will be presented. The frequency of RF generator was in the ranges from 10 to 14Mhz and from 265 to 621kHz.

Keywords: synthesis of carbon nanotubes, hyperthermia, ligands, carbon nanotubes

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939 Detecting Financial Bubbles Using Gap between Common Stocks and Preferred Stocks

Authors: Changju Lee, Seungmo Ku, Sondo Kim, Woojin Chang

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How to detecting financial bubble? Addressing this simple question has been the focus of a vast amount of empirical research spanning almost half a century. However, financial bubble is hard to observe and varying over the time; there needs to be more research on this area. In this paper, we used abnormal difference between common stocks price and those preferred stocks price to explain financial bubble. First, we proposed the ‘W-index’ which indicates spread between common stocks and those preferred stocks in stock market. Second, to prove that this ‘W-index’ is valid for measuring financial bubble, we showed that there is an inverse relationship between this ‘W-index’ and S&P500 rate of return. Specifically, our hypothesis is that when ‘W-index’ is comparably higher than other periods, financial bubbles are added up in stock market and vice versa; according to our hypothesis, if investors made long term investments when ‘W-index’ is high, they would have negative rate of return; however, if investors made long term investments when ‘W-index’ is low, they would have positive rate of return. By comparing correlation values and adjusted R-squared values of between W-index and S&P500 return, VIX index and S&P500 return, and TED index and S&P500 return, we showed only W-index has significant relationship between S&P500 rate of return. In addition, we figured out how long investors should hold their investment position regard the effect of financial bubble. Using this W-index, investors could measure financial bubble in the market and invest with low risk.

Keywords: financial bubble detection, future return, forecasting, pairs trading, preferred stocks

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938 Morphological Differentiation and Temporal Variability in Essential Oil Yield and Composition among Origanum vulgare ssp. hirtum L., Origanum onites L. and Origanum x intercedens from Ikaria Island (Greece)

Authors: A.Assariotakis, P. Vahamidis, P. Tarantilis, G. Economou

Abstract:

Greece, due to its geographical location and the particular climatic conditions, presents high biodiversity of Medicinal and Aromatic Plants. Among them, the genus Origanum not only presents a wide distribution, but it also has great economic importance. After extensive surveys in Ikaria Island (Greece), 3 species of the genus Origanum were identified, namely, Origanum vulgare ssp. hirtum (Greek oregano), Origanum onites (Turkish oregano) and Origanum x intercedens (hybrid), a naturally occurring hybrid between O. hirtum and O. onites. The purpose of this study was to determine their morphological as well as their temporal variability in essential oil yield and composition under field conditions. For this reason, a plantation of each species was created using vegetative propagation and was established at the experimental field of the Agricultural University of Athens (A.U.A.). From the establishment year and for the following two years (3 years of observations), several observations were taken during each growing season with the purpose of identifying the morphological differences among the studied species. Each year collected plant (at bloom stage) material was air-dried at room temperature in the shade. The essential oil content was determined by hydrodistillation using a Clevenger-type apparatus. The chemical composition of essential oils was investigated by Gas Chromatography-Mass Spectrometry (GC – MS). Significant differences were observed among the three oregano species in terms of plant height, leaf size, inflorescence features, as well as concerning their biological cycle. O. intercedens inflorescence presented more similarities with O. hirtum than with O. onites. It was found that calyx morphology could serve as a clear distinction feature between O. intercedens and O. hirtum. The calyx in O. hirtum presents five isometric teeth whereas in O. intercedens two high and three shorter. Essential oil content was significantly affected by genotype and year. O. hirtum presented higher essential oil content than the other two species during the first year of cultivation, however during the second year the hybrid (O. intercedens) recorded the highest values. Carvacrol, p-cymene and γ-terpinene were the main essential oil constituents of the three studied species. In O. hirtum carvacrol content varied from 84,28 - 93,35%, in O. onites from 86,97 - 91,89%, whereas in O. intercedens it was recorded the highest carvacrol content, namely from 89,25 - 97,23%.

Keywords: variability, oregano biotypes, essential oil, carvacrol

Procedia PDF Downloads 111
937 Implementing Lesson Study in Qatari Mathematics Classroom: A Case Study of a New Experience for Teachers through IMPULS-QU Lesson Study Program

Authors: Areej Isam Barham

Abstract:

The implementation of Japanese lesson study approach in the mathematics classroom has been grown worldwide as a model of professional development for teachers. In Qatar, the implementation of IMPULS-QU lesson study program aimed to establish a robust organizational improvement model of professional development for mathematics teachers in Qatar schools. This study describes the implementation of a lesson study model at Al-Markhyia Independent Primary School through different stages; and discusses how the planning process, the research lesson, and the post discussion participates in providing teachers and researchers with a successful research lesson for teacher professional development. The research followed a case study approach in one mathematics classroom. Two teachers and one professional development specialist participated the planning process. One teacher conducted the research lesson study by introducing a problem solving related to the concept of the ‘Mean’ in a mathematics class, 21 students in grade 6 participated in solving the mathematic problem, 11 teachers, 4 professional development specialists, and 4 mathematics professors observed the research lesson. All previous participants except the students participated in a pre and post-lesson discussion within this research. This study followed a qualitative research approach by analyzing the collected data through different stages in the research lesson study. Observation, field notes, and semi-structured interviews conducted to collect data to achieve the research aims. One feature of this lesson study research is that this research describes the implementation for a lesson study as a new experience for one mathematics teacher and 21 students after 3 years of conducting IMPULS-QU project in Al-Markhyia school. The research describes various stages through the implementation of this lesson study model starting from the planning process and ending by the post discussion process. Findings of the study also address the impact of lesson study approach in teaching mathematics for the development of teachers from their point views. Results of the study show the benefits of using lesson study from the point views of participated teachers, theory perceptions about the essential features of lesson study, and their needs for future development. The discussion of the study addresses different features and issues related to the implementation of IMPULS-QU lesson study model in the mathematics classroom. In the light of the study, the research presents recommendations and suggestions for future professional development.

Keywords: lesson study, mathematics education, mathematics teaching experience, teacher professional development

Procedia PDF Downloads 164
936 Geospatial Techniques and VHR Imagery Use for Identification and Classification of Slums in Gujrat City, Pakistan

Authors: Muhammad Ameer Nawaz Akram

Abstract:

The 21st century has been revealed that many individuals around the world are living in urban settlements than in rural zones. The evolution of numerous cities in emerging and newly developed countries is accompanied by the rise of slums. The precise definition of a slum varies countries to countries, but the universal harmony is that slums are dilapidated settlements facing severe poverty and have lacked access to sanitation, water, electricity, good living styles, and land tenure. The slum settlements always vary in unique patterns within and among the countries and cities. The core objective of this study is the spatial identification and classification of slums in Gujrat city Pakistan from very high-resolution GeoEye-1 (0.41m) satellite imagery. Slums were first identified using GPS for sample site identification and ground-truthing; through this process, 425 slums were identified. Then Object-Oriented Analysis (OOA) was applied to classify slums on digital image. Spatial analysis softwares, e.g., ArcGIS 10.3, Erdas Imagine 9.3, and Envi 5.1, were used for processing data and performing the analysis. Results show that OOA provides up to 90% accuracy for the identification of slums. Jalal Cheema and Allah Ho colonies are severely affected by slum settlements. The ratio of criminal activities is also higher here than in other areas. Slums are increasing with the passage of time in urban areas, and they will be like a hazardous problem in coming future. So now, the executive bodies need to make effective policies and move towards the amelioration process of the city.

Keywords: slums, GPS, satellite imagery, object oriented analysis, zonal change detection

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935 Identification and Isolation of E. Coli O₁₅₇:H₇ From Water and Wastewater of Shahrood and Neka Cities by PCR Technique

Authors: Aliasghar Golmohammadian, Sona Rostampour Yasouri

Abstract:

One of the most important intestinal pathogenic strains is E. coli O₁₅₇:H₇. This pathogenic bacterium is transmitted to humans through water and food. E. coli O₁₅₇:H₇ is the main cause of Hemorrhagic colitis (HC), Hemolytic Uremic Syndrome (HUS), Thrombotic Thrombocytopenic Purpura (TTP) and in some cases death. Since E. coli O₁₅₇:H₇ can be transmitted through the consumption of different foods, including vegetables, agricultural products, and fresh dairy products, this study aims to identify and isolate E. coli O₁₅₇:H₇ from wastewater by PCR technique. One hundred twenty samples of water and wastewater were collected by Falcom Sterile from Shahrood and Neka cities. The samples were checked for colony formation after appropriate centrifugation and cultivation in the specific medium of Sorbitol MacConkey Agar (SMAC) and other diagnostic media of E. coli O₁₅₇:H₇. Also, the plates were observed macroscopically and microscopically. Then, the necessary phenotypic tests were performed on the colonies, and finally, after DNA extraction, the PCR technique was performed with specific primers related to rfbE and stx2 genes. The number of 5 samples (6%) out of all the samples examined were determined positive by PCR technique with observing the bands related to the mentioned genes on the agarose gel electrophoresis. PCR is a fast and accurate method to identify the bacteria E. coli O₁₅₇:H₇. Considering that E. coli bacteria is a resistant bacteria and survives in water and food for weeks and months, the PCR technique can provide the possibility of quick detection of contaminated water. Moreover, it helps people in the community control and prevent the transfer of bacteria to healthy and underground water and agricultural and even dairy products.

Keywords: E. coli O₁₅₇:H₇, PCR, water, wastewater

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934 Virtual Process Hazard Analysis (Pha) Of a Nuclear Power Plant (Npp) Using Failure Mode and Effects Analysis (Fmea) Technique

Authors: Lormaine Anne A. Branzuela, Elysa V. Largo, Monet Concepcion M. Detras, Neil C. Concibido

Abstract:

The electricity demand is still increasing, and currently, the Philippine government is investigating the feasibility of operating the Bataan Nuclear Power Plant (BNPP) to address the country’s energy problem. However, the lack of process safety studies on BNPP focused on the effects of hazardous substances on the integrity of the structure, equipment, and other components, have made the plant operationalization questionable to the public. The three major nuclear power plant incidents – TMI-2, Chernobyl, and Fukushima – have made many people hesitant to include nuclear energy in the energy matrix. This study focused on the safety evaluation of possible operations of a nuclear power plant installed with a Pressurized Water Reactor (PWR), which is similar to BNPP. Failure Mode and Effects Analysis (FMEA) is one of the Process Hazard Analysis (PHA) techniques used for the identification of equipment failure modes and minimizing its consequences. Using the FMEA technique, this study was able to recognize 116 different failure modes in total. Upon computation and ranking of the risk priority number (RPN) and criticality rating (CR), it showed that failure of the reactor coolant pump due to earthquakes is the most critical failure mode. This hazard scenario could lead to a nuclear meltdown and radioactive release, as identified by the FMEA team. Safeguards and recommended risk reduction strategies to lower the RPN and CR were identified such that the effects are minimized, the likelihood of occurrence is reduced, and failure detection is improved.

Keywords: PHA, FMEA, nuclear power plant, bataan nuclear power plant

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933 Complex Management of Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy

Authors: Abdullah A. Al Qurashi, Hattan A. Hassani, Bader K. Alaslap

Abstract:

Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C) is an uncommon, inheritable cardiac disorder characterized by the progressive substitution of cardiac myocytes by fibro-fatty tissues. This pathologic substitution predisposes patients to ventricular arrhythmias and right ventricular failure. The underlying genetic defect predominantly involves genes encoding for desmosome proteins, particularly plakophilin-2 (PKP2). These aberrations lead to impaired cell adhesion, heightening the susceptibility to fibrofatty scarring under conditions of mechanical stress. Primarily, ARVD/C affects the right ventricle, but it can also compromise the left ventricle, potentially leading to biventricular heart failure. Clinical presentations can vary, spanning from asymptomatic individuals to those experiencing palpitations, syncopal episodes, and, in severe instances, sudden cardiac death. The establishment of a diagnostic criterion specifically tailored for ARVD/C significantly aids in its accurate diagnosis. Nevertheless, the task of early diagnosis is complicated by the disease's frequently asymptomatic initial stages, and the overall rarity of ARVD/C cases reported globally. In some cases, as exemplified by the adult female patient in this report, the disease may advance to terminal stages, rendering therapies like Ventricular Tachycardia (VT) ablation ineffective. This case underlines the necessity for increased awareness and understanding of ARVD/C to aid in its early detection and management. Through such efforts, we aim to decrease morbidity and mortality associated with this challenging cardiac disorder.

Keywords: arrhythmogenic right ventricular dysplasia, cardiac disease, interventional cardiology, cardiac electrophysiology

Procedia PDF Downloads 38
932 Clinical Signs of Neonatal Calves in Experimental Colisepticemia

Authors: Samad Lotfollahzadeh

Abstract:

Escherichia coli (E.coli) is the most isolated bacteria from blood circulation of septicemic calves. Given the prevalence of septicemia in animals and its economic importance in veterinary practice, better understanding of changes in clinical signs following disease, may contribute to early detection of the disorder. The present study has been carried out to detect changes of clinical signs in induced sepsis in calves with E.coli. Colisepticemia has been induced in 10 twenty-day old healthy Holstein- Frisian calves with intravenous injection of 1.5 X 109 colony forming units (cfu) of O111: H8 strain of E.coli. Clinical signs including rectal temperature, heart rate, respiratory rate, shock, appetite, sucking reflex, feces consistency, general behavior, dehydration and standing ability were recorded in experimental calves during 24 hours after induction of colisepticemia. Blood culture was also carried out from calves four times during the experiment. ANOVA with repeated measure is used to see changes of calves’ clinical signs to experimental colisepticemia, and values of P≤ 0.05 was considered statistically significant. Mean values of rectal temperature and heart rate as well as median values of respiratory rate, appetite, suckling reflex, standing ability and feces consistency of experimental calves increased significantly during the study (P<0.05). In the present study, median value of shock score was not significantly increased in experimental calves (P> 0.05). The results of present study showed that total score of clinical signs in calves with experimental colisepticemia increased significantly, although the score of some clinical signs such as shock did not change significantly.

Keywords: calves, clinical signs scoring, E. coli O111:H8, experimental colisepticemia

Procedia PDF Downloads 355
931 Calculation of the Normalized Difference Vegetation Index and the Spectral Signature of Coffee Crops: Benefits of Image Filtering on Mixed Crops

Authors: Catalina Albornoz, Giacomo Barbieri

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Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

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930 Preparation of Frozen Bivalent Babesial (Babesia Bovis and Babesia Bigemina) Vaccine from Field Isolates and Evaluation of Its Efficacy in Calves

Authors: Muhammad Fiaz Qamar, Ahmad Faraz, Muhammad Arfan Zaman, Kazim Ali, Waleed Akram

Abstract:

Babesiosis is reflected as the most important disease of cattle that are transmitted by arthropods. In Pakistan, its prevalence is up to 29% in the cattle and buffalo population in different regions. Cattle show a long lasting and durable immunity by giving an infection of B.bovis, B. bigemina, or Babesiadivergens. this is used in cattle to immunize them in a few countries as anti-babesiosis vaccine. Development of frozen vaccine allows for complete testing after production of each batch, However, once thawed, its reduced its shelf life, frozen vaccines are more difficult to transport as well as expensive to produce as compared to chilled vaccine. The contamination of blood derived vaccine has the potential risk that makes pre-production and post-production quality control necessary. For the trail master seed production of whole blood frozen bivalent Babesia(Babesiabovis and Babesiabigemina), 100 blood samples of Babesial positive suspected cattle was taken and processed for separation microscopic detection and rectification by PCR. Vaccine passages were done to reduce the parasitaemiasis in live calves. After 8 passages, parasitemia of Babesia reduced from 80% to 15%. Infected donor calf’s blood was taken by jugular cannulation by using preservative free lithium heparin as an anticoagulant (5 International Units IU heparin/ml blood). In lab, parasite containing blood was mixed in equal volumes with 3 M glycerol in PBS supplemented with 5 mM glucose (final concentration of glycerol 1.5 M) at 37°C. The mixture was then equilibrized at 37°C for 30 minutes and were dispensed in required containers (e.g., 5 ml cryovials).

Keywords: distribution, babesia, primer sequences, PCV

Procedia PDF Downloads 83
929 Radio-Frequency Technologies for Sensing and Imaging

Authors: Cam Nguyen

Abstract:

Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: RF sensors, radars, surface sensing, subsurface sensing

Procedia PDF Downloads 293
928 Prediction of Damage to Cutting Tools in an Earth Pressure Balance Tunnel Boring Machine EPB TBM: A Case Study L3 Guadalajara Metro Line (Mexico)

Authors: Silvia Arrate, Waldo Salud, Eloy París

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The wear of cutting tools is one of the most decisive elements when planning tunneling works, programming the maintenance stops and saving the optimum stock of spare parts during the evolution of the excavation. Being able to predict the behavior of cutting tools can give a very competitive advantage in terms of costs and excavation performance, optimized to the needs of the TBM itself. The incredible evolution of data science in recent years gives the option to implement it at the time of analyzing the key and most critical parameters related to machinery with the purpose of knowing how the cutting head is performing in front of the excavated ground. Taking this as a case study, Metro Line 3 of Guadalajara in Mexico will develop the feasibility of using Specific Energy versus data science applied over parameters of Torque, Penetration, and Contact Force, among others, to predict the behavior and status of cutting tools. The results obtained through both techniques are analyzed and verified in the function of the wear and the field situations observed in the excavation in order to determine its effectiveness regarding its predictive capacity. In conclusion, the possibilities and improvements offered by the application of digital tools and the programming of calculation algorithms for the analysis of wear of cutting head elements compared to purely empirical methods allow early detection of possible damage to cutting tools, which is reflected in optimization of excavation performance and a significant improvement in costs and deadlines.

Keywords: cutting tools, data science, prediction, TBM, wear

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927 The Economic Burden of Breast Cancer on Women in Nigeria: Implication for Socio-Economic Development

Authors: Tolulope Allo, Mofoluwake P. Ajayi, Adenike E. Idowu, Emmanuel O. Amoo, Fadeke Esther Olu-Owolabi

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Breast cancer which was more prevalent in Europe and America in the past is gradually being mirrored across the world today with greater economic burden on low and middle income countries (LMCs). Breast cancer is the most common cancer among women globally and current studies have shown that a woman dies with the diagnosis of breast cancer every thirteen minutes. The economic cost of breast cancer is overwhelming particularly for developing economies. While it causes billion of dollar in losses of national income, it pushes millions of people below poverty line. This study examined the economic burden of breast cancer on Nigerian women, its impacts on their standard of living and its effects on Nigeria’s socio economic development. The study adopts a qualitative research approach using the in-depth interview technique to elicit valuable information from respondents with cancer experience from the Southern part of Nigeria. Respondents constituted women in their reproductive age (15-49 years) that have experienced and survived cancer and also those that are currently receiving treatment. Excerpts from the interviews revealed that the cost of treatment is one of the major factors contributing to the late presentation of breast cancer incidences among women as many of them could not afford to pay for their own treatment. The study also revealed that many women prefer to explore other options such as herbal treatments and spiritual consultations which is less expensive and affordable. The study therefore concludes that breast cancer diagnosis and treatment should be subsidized by the government in order to facilitate easy access and affordability thereby promoting early detection and reducing the economic burden of treatment on women.

Keywords: breast cancer, development, economic burden, women

Procedia PDF Downloads 338
926 A Bayesian Parameter Identification Method for Thermorheological Complex Materials

Authors: Michael Anton Kraus, Miriam Schuster, Geralt Siebert, Jens Schneider

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Polymers increasingly gained interest in construction materials over the last years in civil engineering applications. As polymeric materials typically show time- and temperature dependent material behavior, which is accounted for in the context of the theory of linear viscoelasticity. Within the context of this paper, the authors show, that some polymeric interlayers for laminated glass can not be considered as thermorheologically simple as they do not follow a simple TTSP, thus a methodology of identifying the thermorheologically complex constitutive bahavioir is needed. ‘Dynamical-Mechanical-Thermal-Analysis’ (DMTA) in tensile and shear mode as well as ‘Differential Scanning Caliometry’ (DSC) tests are carried out on the interlayer material ‘Ethylene-vinyl acetate’ (EVA). A navoel Bayesian framework for the Master Curving Process as well as the detection and parameter identification of the TTSPs along with their associated Prony-series is derived and applied to the EVA material data. To our best knowledge, this is the first time, an uncertainty quantification of the Prony-series in a Bayesian context is shown. Within this paper, we could successfully apply the derived Bayesian methodology to the EVA material data to gather meaningful Master Curves and TTSPs. Uncertainties occurring in this process can be well quantified. We found, that EVA needs two TTSPs with two associated Generalized Maxwell Models. As the methodology is kept general, the derived framework could be also applied to other thermorheologically complex polymers for parameter identification purposes.

Keywords: bayesian parameter identification, generalized Maxwell model, linear viscoelasticity, thermorheological complex

Procedia PDF Downloads 239
925 Investigation of a Novel Dual Band Microstrip/Waveguide Hybrid Antenna Element

Authors: Raoudane Bouziyan, Kawser Mohammad Tawhid

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Microstrip antennas are low in profile, light in weight, conformable in structure and are now developed for many applications. The main difficulty of the microstrip antenna is its narrow bandwidth. Several modern applications like satellite communications, remote sensing, and multi-function radar systems will find it useful if there is dual-band antenna operating from a single aperture. Some applications require covering both transmitting and receiving frequency bands which are spaced apart. Providing multiple antennas to handle multiple frequencies and polarizations becomes especially difficult if the available space is limited as with airborne platforms and submarine periscopes. Dual band operation can be realized from a single feed using slot loaded or stacked microstrip antenna or two separately fed antennas sharing a common aperture. The former design, when used in arrays, has certain limitations like complicated beam forming or diplexing network and difficulty to realize good radiation patterns at both the bands. The second technique provides more flexibility with separate feed system as beams in each frequency band can be controlled independently. Another desirable feature of a dual band antenna is easy adjustability of upper and lower frequency bands. This thesis presents investigation of a new dual-band antenna, which is a hybrid of microstrip and waveguide radiating elements. The low band radiator is a Shorted Annular Ring (SAR) microstrip antenna and the high band radiator is an aperture antenna. The hybrid antenna is realized by forming a waveguide radiator in the shorted region of the SAR microstrip antenna. It is shown that the upper to lower frequency ratio can be controlled by the proper choice of various dimensions and dielectric material. Operation in both linear and circular polarization is possible in either band. Moreover, both broadside and conical beams can be generated in either band from this antenna element. Finite Element Method based software, HFSS and Method of Moments based software, FEKO were employed to perform parametric studies of the proposed dual-band antenna. The antenna was not tested physically. Therefore, in most cases, both HFSS and FEKO were employed to corroborate the simulation results.

Keywords: FEKO, HFSS, dual band, shorted annular ring patch

Procedia PDF Downloads 380