Search results for: accuracy ratio

Authors: Kathrina Aseanne Acapulco-Gomez, Shayne Julieane Morales, Tzar Francis Verame

Abstract:

Mean platelet volume (MPV) is the most accurate measure of the size of platelets and is routinely measured by most automated hematological analyzers. Several studies have shown associations between MPV and cardiovascular risks and outcomes. Although its measurement may provide useful data, MPV remains to be a diagnostic tool that is yet to be included in routine clinical decision making. The aim of this systematic review and meta-analysis is to determine summary estimates of the diagnostic accuracy of mean platelet volume for the diagnosis of myocardial infarction among adult patients with angina and/or its equivalents in terms of sensitivity, specificity, diagnostic odds ratio, and likelihood ratios, and to determine the difference of the mean MPV values between those with MI and those in the non-MI controls. The primary search was done through search in electronic databases PubMed, Cochrane Review CENTRAL, HERDIN (Health Research and Development Information Network), Google Scholar, Philippine Journal of Pathology, and Philippine College of Physicians Philippine Journal of Internal Medicine. The reference list of original reports was also searched. Cross-sectional, cohort, and case-control articles studying the diagnostic performance of mean platelet volume in the diagnosis of acute myocardial infarction in adult patients were included in the study. Studies were included if: (1) CBC was taken upon presentation to the ER or upon admission (within 24 hours of symptom onset); (2) myocardial infarction was diagnosed with serum markers, ECG, or according to accepted guidelines by the Cardiology societies (American Heart Association (AHA), American College of Cardiology (ACC), European Society of Cardiology (ESC); and, (3) if outcomes were measured as significant difference AND/OR sensitivity and specificity. The authors independently screened for inclusion of all the identified potential studies as a result of the search. Eligible studies were appraised using well-defined criteria. Any disagreement between the reviewers was resolved through discussion and consensus. The overall mean MPV value of those with MI (9.702 fl; 95% CI 9.07 – 10.33) was higher than in those of the non-MI control group (8.85 fl; 95% CI 8.23 – 9.46). Interpretation of the calculated t-value of 2.0827 showed that there was a significant difference in the mean MPV values of those with MI and those of the non-MI controls. The summary sensitivity (Se) and specificity (Sp) for MPV were 0.66 (95% CI; 0.59 - 0.73) and 0.60 (95% CI; 0.43 – 0.75), respectively. The pooled diagnostic odds ratio (DOR) was 2.92 (95% CI; 1.90 – 4.50). The positive likelihood ratio of MPV in the diagnosis of myocardial infarction was 1.65 (95% CI; 1.20 – 22.27), and the negative likelihood ratio was 0.56 (95% CI; 0.50 – 0.64). The intended role for MPV in the diagnostic pathway of myocardial infarction would perhaps be best as a triage tool. With a DOR of 2.92, MPV values can discriminate between those who have MI and those without. For a patient with angina presenting with elevated MPV values, it is 1.65 times more likely that he has MI. Thus, it is implied that the decision to treat a patient with angina or its equivalents as a case of MI could be supported by an elevated MPV value.

Keywords: mean platelet volume, MPV, myocardial infarction, angina, chest pain

Procedia PDF Downloads 86

Authors: Sophie Mills, Leila L. Touil, Richard Sisson

Abstract:

Introduction: The TNM classification is the global standard for the staging of head and neck cancers. Accurate clinical-radiological staging of tumours (cTNM) is essential to predict prognosis, facilitate surgical planning and determine the need for other therapeutic modalities. This study aims to determine the accuracy of pre-operative cTNM staging using pathological TNM (pTNM) and consider possible causes of TNM stage migration, noting any variation throughout the COVID-19 pandemic. Materials and Methods: A retrospective cohort study examined records of patients with surgical management of head and neck cancer at a tertiary head and neck centre from November 2019 to November 2020. Data was extracted from Somerset Cancer Registry and histopathology reports. cTNM and pTNM were compared before and during the first wave of COVID-19, as well as with other potential prognostic factors such as tumour site and tumour stage. Results: 119 cases were identified, of which 52.1% (n=62) were male, and 47.9% (n=57) were female with a mean age of 67 years. Clinical and pathological staging differed in 54.6% (n=65) of cases. Of the patients with stage migration, 40.4% (n=23) were up-staged and 59.6% (n=34) were down-staged compared with pTNM. There was no significant difference in the accuracy of cTNM staging compared with age, sex, or tumour site. There was a statistically highly significant (p < 0.001) correlation between cTNM accuracy and tumour stage, with the accuracy of cTNM staging decreasing with the advancement of pTNM staging. No statistically significant variation was noted between patients staged prior to and during COVID-19. Conclusions: Discrepancies in staging can impact management and outcomes for patients. This study found that the higher the pTNM, the more likely stage migration will occur. These findings are concordant with the oncology literature, which highlights the need to improve the accuracy of cTNM staging for more advanced tumours.

Keywords: COVID-19, head and neck cancer, stage migration, TNM staging

Procedia PDF Downloads 109

Authors: Adel Edwar Waheeb Louka

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

Procedia PDF Downloads 73

Authors: M. R. Akbari, H. Yousefnia, A. Ghasemi

Abstract:

Al2O3:C,Mg fluorescent nuclear track detector (FNTD) and Al2O3:C optically stimulated luminescence detector (OSLD) are becoming two of the applied detectors in ion dosimetry. Therefore, the response of these detectors to hadron beams is highly of interest in radiation therapy (RT) using ion beams. In this study, these detectors' responses to proton and Helium-4 ion beams were compared using Monte Carlo simulations. The calculated data for proton beams were compared with Markus ionization chamber (IC) measurement (in water phantom) from M.D. Anderson proton therapy center. Monte Carlo simulations were performed via the FLUKA code (version 2011.2-17). The detectors were modeled in cylindrical shape at various depths of the water phantom without shading each other for obtaining relative depth dose in the phantom. Mono-energetic parallel ion beams in different incident energies (100 MeV/n to 250 MeV/n) were collided perpendicularly on the phantom surface. For proton beams, the results showed that the simulated detectors have over response relative to IC measurements in water phantom. In all cases, there were good agreements between simulated ion ranges in the water with calculated and experimental results reported by the literature. For proton, maximum peak to entrance dose ratio in the simulated water phantom was 4.3 compared with about 3 obtained from IC measurements. For He-4 ion beams, maximum peak to entrance ratio calculated by both detectors was less than 3.6 in all energies. Generally, it can be said that FLUKA is a good tool to calculate Al2O3:C,Mg FNTD and Al2O3:C OSLD detectors responses to therapeutic proton and He-4 ion beams. It can also calculate proton and He-4 ion ranges with a reasonable accuracy.

Keywords: comparison, FNTD and OSLD detectors response, light ion beams, Monte Carlo simulations

Procedia PDF Downloads 343

Authors: Navab Karimi, Tohid Alizadeh

Abstract:

An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

Procedia PDF Downloads 73

Authors: Daniel Fozer

Abstract:

Limiting global warming to 1.5°C to the pre-industrial levels urges the application of efficient and sustainable carbon dioxide removal (CDR) technologies. Microalgae based biorefineries offer scalable solutions for the biofixation of CO2, where the produced biomass can be transformed into value added products by applying thermochemical processes. In this paper we report on the utilization of hydrochar as a blending component in hydrothermal gasification (HTG) process. The effects of blending ratio and hydrochar quality were investigated on the biogas yield and and composition. It is found that co-gasifying the hydrochar and the algae biomass can increase significantly the total gas yield and influence the biogas (H2, CH4, CO2, CO, C2H4, C2H6) composition. It is determined that the carbon conversion ratio, hydrogen and methane selectivity can be increased by influencing the fuel ratio of hydrochar via hydrothermal carbonization. In conclusion, it is found that increasing the synergy between hydrothermal technologies result in elevated conversion efficiency.

Keywords: biogas, CDR, Co-HTG, hydrochar, microalgae

Procedia PDF Downloads 147

Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

Abstract:

Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

Procedia PDF Downloads 125

Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

Abstract:

In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

Procedia PDF Downloads 39

Authors: Bo-Jian Wu, Si-Heng Wu

Abstract:

Objectives: Frailty is a condition of a person who has chronic health problems complicated by a loss of physiological reserve and deteriorating functional abilities. The frailty syndrome was defined by Fried and colleagues, i.e., weight loss, fatigue, decreased grip strength, slow gait speed, and low physical activity. However, to our best knowledge, there have been rare studies exploring the prevalence of frailty and its association with falls in patients with schizophrenia. Methods: A total of 559 hospitalized patients were recruited from a public psychiatric hospital in 2013. The majority of the subjects were males (361, 64.6%). The average age was 53.5 years. All patients received the assessment of frailty status defined by Fried and colleagues. The status of a fall within one year after the assessment of frailty, clinical and demographic data was collected from medical records. Logistic regression was used to calculate the odds ratio of associated factors. Results : A total of 9.2% of the participants met the criteria of frailty. The percentage of patients having a fall was 7.2%. Age were significantly associated with frailty (odds ratio = 1.057, 95% confidence interval = 1.025-1.091); however, sex was not associated with frailty (p = 0.17). After adjustment for age and sex, frailty status was associated with a fall (odds ratio = 3.62, 95% confidence interval = 1.58-8.28). Concerning the components of frailty, decreased grip strength (odds ratio = 2.44, 95% confidence interval = 1.16-5.14), slow gait speed (odds ratio = 2.82, 95% confidence interval = 1.21-6.53), and low physical activity (odds ratio = 2.64, 95% confidence interval = 1.21-5.78) were found to be associated with a fall. Conclusions: Our findings suggest the prevalence of frailty was about 10% in hospitalized patients with chronic patients with schizophrenia, and frailty status was significant with a fall in this group. By using the status of frailty, it may be beneficial to potential target candidates having fallen in the future as early as possible. The effective intervention of prevention of further falls may be given in advance. Our results bridge this gap and open a potential avenue for the prevention of falls in patients with schizophrenia. Frailty is certainly an important factor for maintaining wellbeing among these patients.

Keywords: fall, frailty, schizophrenia, Taiwan

Procedia PDF Downloads 165

Authors: Marwan Ahmed Swileh, Amal Hussein Abuaffan

Abstract:

Objective: This study aimed to explore the existence of golden proportion (GP) between the widths of maxillary anterior teeth and golden standard (GS) for width to height ratio of maxillary central incisor in individuals with attractive and non-attractive smiles. Materials and methods: A total of 82 females were recruited and divided into 2 groups: attractive smile (n= 41) and non-attractive smile (n= 41). Frontal photographs were taken, scanned, and saved on a personal computer. The apparent mesiodistal width of each anterior tooth was measured. The data were analyzed using the appropriate statistical tests at p-value < 0.05. Results: Frequency of GP was very low among the total sample, and most proportions were higher than GP. No significant differences were found between both groups in relation to central-to-lateral ratio while significant differences were found in relation to canine-to-lateral ratio. Similarly, most proportions of width to height ratio were higher than GS. Difference between groups was significant for left side and for both sides (p < 0.05) but was not for right side (p > 0.05). Conclusion: Frequency of golden proportion was very low among the study population. Smile attractiveness is not related that much to the proportions between the teeth.

Keywords: golden proportion, golden standard, attractive smile, esthetic, anterior teeth

Procedia PDF Downloads 142

Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

Abstract:

This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

Procedia PDF Downloads 96

Authors: Amin AminiKhafri, James M. Dawson-Edwards, Ryan M. Simpson, Simaan M. AbouRizk

Abstract:

Earned value management (EVM) has been introduced as an integrated method to combine schedule, budget, and work breakdown structure (WBS). EVM provides various indices to demonstrate project performance including the cost performance index (CPI). CPI is also used to forecast final project cost at completion based on the cost performance during the project execution. Knowing the final project cost during execution can initiate corrective actions, which can enhance project outputs. CPI, however, is not constant during the project, and calculating the final project cost using a variable index is an inaccurate and challenging task for practitioners. Since CPI is based on the cumulative progress values and because of the learning curve effect, CPI variation dampens and stabilizes as project progress. Although various definitions for the CPI stability have been proposed in literature, many scholars have agreed upon the definition that considers a project as stable if the CPI at 20% completion varies less than 0.1 from the final CPI. While 20% completion point is recognized as the stability point for military development projects, construction projects stability have not been studied. In the current study, an empirical study was first conducted using construction project data to determine the stability point for construction projects. Early findings have demonstrated that a majority of construction projects stabilize towards completion (i.e., after 70% completion point). To investigate the effect of CPI stability on cost forecast accuracy, the correlation between CPI stability and project cost at completion forecast accuracy was also investigated. It was determined that as projects progress closer towards completion, variation of the CPI decreases and final project cost forecast accuracy increases. Most projects were found to have 90% accuracy in the final cost forecast at 70% completion point, which is inlined with findings from the CPI stability findings. It can be concluded that early stabilization of the project CPI results in more accurate cost at completion forecasts.

Keywords: cost performance index, earned value management, empirical study, final project cost

Procedia PDF Downloads 156

Authors: Riznaldi Akbar

Abstract:

In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.

Keywords: debt crisis, external debt, artificial neural network, ANN

Procedia PDF Downloads 438

Authors: Chongyang Ye, Rong Liu

Abstract:

Compression textiles such as compression stockings (CSs) have been extensively applied for the prevention and treatment of chronic venous insufficiency of lower extremities. The involvement of multiple mechanical factors such as interface pressure, frictional force, and elastic materials make the interactions between lower limb and CSs to be complex. Determination of Poisson’s ratio and elastic moduli of CS materials are critical for constructing finite element (FE) modeling to numerically simulate a complex interactive system of CS and lower limb. In this study, a mixed approach, including an analytic model based on the orthotropic Hooke’s Law and experimental study (uniaxial tension testing and pure shear testing), has been proposed to determine Young’s modulus, Poisson’s ratio, and shear modulus of CS fabrics. The results indicated a linear relationship existing between the stress and strain properties of the studied CS samples under controlled stretch ratios (< 100%). The newly proposed method and the determined key mechanical properties of elastic orthotropic CS fabrics facilitate FE modeling for analyzing in-depth the effects of compression material design on their resultant biomechanical function in compression therapy.

Keywords: elastic compression stockings, Young’s modulus, Poisson’s ratio, shear modulus, mechanical analysis

Procedia PDF Downloads 118

Authors: Helen Zhang

Abstract:

Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogeneous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning

Procedia PDF Downloads 117

Authors: Fernando Maass, Pablo Martin, Jorge Olivares

Abstract:

The Bessel function J₀(x) is very important in Electrodynamics and Physics, as well as its zeros. In this work, a method to obtain high accuracy approximation is presented through an application to that function. In most of the applications of this function, the values of the zeros are very important. In this work, analytic approximations for this function have been obtained valid for all positive values of the variable x, which have high accuracy for the function as well as for the zeros. The approximation is determined by the simultaneous used of the power series and asymptotic expansion. The structure of the approximation is a combination of two rational functions with elementary functions as trigonometric and fractional powers. Here us in Pade method, rational functions are used, but now there combined with elementary functions us fractional powers hyperbolic or trigonometric functions, and others. The reason of this is that now power series of the exact function are used, but together with the asymptotic expansion, which usually includes fractional powers trigonometric functions and other type of elementary functions. The approximation must be a bridge between both expansions, and this can not be accomplished using only with rational functions. In the simplest approximation using 4 parameters the maximum absolute error is less than 0.006 at x ∼ 4.9. In this case also the maximum relative error for the zeros is less than 0.003 which is for the second zero, but that value decreases rapidly for the other zeros. The same kind of behaviour happens for the relative error of the maximum and minimum of the functions. Approximations with higher accuracy and more parameters will be also shown. All the approximations are valid for any positive value of x, and they can be calculated easily.

Keywords: analytic approximations, asymptotic approximations, Bessel functions, quasirational approximations

Procedia PDF Downloads 251

Authors: K. K. Saijaand, K. Prabhakaran Nair

Abstract:

This study aims to determine change in optimal lo-cations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multi-objective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization results shows that the inboard flap location at low Ct/σ ratio move farther from the baseline value and at high Ct/σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: helicopter rotor, trailing-edge flap, thrust coefficient to solidity (Ct /σ) ratio, optimization

Procedia PDF Downloads 475

Authors: Barenten Suciu

Abstract:

In order to explain the damping mechanism, related to the hunting motion of the wheel axle of a high-speed railway vehicle, a generalized dynamic model is proposed. Based on such model, analytic expressions for the damping coefficient and damped natural frequency are derived, without imposing restrictions on the ratio between the lateral and vertical creep coefficients. Influence of the travelling speed, wheel conicity, dimensionless mass of the wheel axle, ratio of the creep coefficients, ratio of the track span to the yawing diameter, etc. on the damping coefficient and damped natural frequency, is clarified.

Keywords: high-speed railway vehicle, hunting motion, wheel axle, damping, creep, vibration model, analysis.

Procedia PDF Downloads 290

Authors: R. Abd-Rahman, M. M. Isa, H. H. Goh

Abstract:

A compound parabolic concentrator (CPC) is a well known non-imaging concentrator that will concentrate the solar radiation onto receiver (PV cell). One of disadvantage of CPC is has tall and narrow height compared to its diameter entry aperture area. Therefore, for economic reason, a truncation had been done by removed from the top of the full height CPC. This is also will lead to the decreases of concentration ratio but it will be negligible. In this paper, the flux distribution of untruncated and truncated 2-D hollow compound parabolic trough concentrator (hCPTC) design is presented. The untruncated design has initial height, H=193.4mm with concentration ratio, C_(2-D)=4. This paper presents the optical simulation of compound parabolic trough concentrator using ray-tracing software TracePro. Results showed that, after the truncation, the height of CPC reduced 45% from initial height with the geometrical concentration ratio only decrease 10%. Thus, the cost of reflector and material dielectric usage can be saved especially at manufacturing site.

Keywords: compound parabolic trough concentrator, optical modelling, ray-tracing analysis, improved performance

Procedia PDF Downloads 462

Authors: Arafat Husain

Abstract:

The lubricants are one of the most used resource in today’s world. Lot of the superpowers are dependent on the lubricant resource for their country to function. To see that the lubricants are not adulterated we need to develop some efficient ways and to see which fluid has been added to the lubricant. So to observe the these malpractices in the lubricant we need to develop a method. We take a elastic ball and through it at probability circle in the submerged in the lubricant at a fixed force and see the distance of pitching and the point of fall. Then we the ratio of distance of falling to the distance of pitching and if the measured ratio is greater than one the fluid is less viscous and if the ratio is lesser than the lubricant is viscous. We will check the falling point of pure lubricant at fixed force and every pure lubricant would have a fixed falling point. After that we would adulterate the lubricant and note the falling point and if the falling point is less than the standard value then adulterate is solid and if the adulterate is liquid the falling point will be more than the standard value. Hence the comparison with the standard falling point will give the efficiency of the lubricant.

Keywords: falling point of lubricant, falling point ratios, probability circle, octane number

Procedia PDF Downloads 495

Authors: Afrizon Reskino

Abstract:

The Article explores how the role of Zakat and Corporate Social Responsibility (CSR) can enhance corporate values. This research is a descriptive study which aimed to find out how the impact of Zakat and CSR disclosure towards corporate values. Sample taken in this research is the company has entered into the Jakarta Islamic Index, and it estimated to have implemented CSR and also made statements of sources and uses of Zakat taking PT. INCO, PT. Inducement and PT. Semen Gresik. The reasons for selecting of three companies are known from the data and facts every year they always provide significant CSR funds. CSR and charity both have a role and responsibility for the welfare of the peoples. This study found that in 2008, debt-to-equity ratio of PT. INCO approximately 15%. In 2009, It increased to 23%. While Debt-to-equity ratio of PT Semen Gresik increase of 3% to 4%. PT Inducement is weaken from 10% to 7%, but the average debt-to-equity ratio of the three companies has increased.

Keywords: zakat, charity, corporate social responsibility, corporate values

Procedia PDF Downloads 405

Authors: Cristian Chacha, David Asiain, Jesús Ponce de León, José Ramón Beltrán

Abstract:

This work explores and characterizes the behavior of the AFE AD5941 in impedance measurement using an embedded algorithm with a constant current AC source. The main aim of this research is to improve the exact measurement of impedance values for their application in EDA-focused wearable devices. Through comprehensive study and characterization, it has been observed that employing a measurement sequence with a constant current source produces results with increased dispersion but higher accuracy. As a result, this approach leads to a more accurate system for impedance measurement.

Keywords: EDA, constant current AC source, wearable, precision, accuracy, impedance

Procedia PDF Downloads 107

Authors: Bakhtishod Matmuratov, Sakhiba Madraximova, Rakhmat Esanov, Alimjan Matchanov

Abstract:

Studies have been performed to obtain complexes of glycyrrhizic acid and kinetins in a 2:1 ratio. The complex of glycyrrhizic acid and kinetins in a 2:1 ratio was considered evidence of the formation of a molecular complex by determining the molecular masses using chromato-mass spectroscopy and analyzing the IR spectra.

Keywords: monoammonium salt of glycyrrhizic acid, glycyrrhizic acid, supramolecular complex, isomolar series, IR spectroscopy

Procedia PDF Downloads 177

Authors: Wiji Wijaya

Abstract:

The aim of this research is to examine the effect of internal control weaknesses and audit opinion on the state’s loss findings of audit compliance to the regulation in public sector. The samples of this research consisted of 175 local government financial statements in the area of Central Java Province at 2009 until 2013. Area sampling design was used to select the financial statements. This study using quantitative descriptive statistical analysis and regression was run for data analysis and hypothesis examination. Result of this study indicated that internal control weaknesses and audit opinion contributes a positive influence which is significant to the state’s loss findings of audit compliance to the regulation. The internal control weaknesses that affect the state's loss finding are weakness control system of accounting and reporting with the value of the critical ratio 0.010 p 2.613 ; weakness budget execution control system with critical ratio value of 3.421 p 0.001 and weaknesses internal control structure with critical ratio value of 2.246 p 0.026 . While the audit opinion with a critical ratio value of 4.401 p 0.000. The implications of this research so that policy makers at the local government should give more attention to the implementation and improvement of internal control system.

Keywords: audit compliance findings, state’s loss, audit opinion, internal control, local government

Procedia PDF Downloads 379

Authors: Arulselvi Subramanian, Albert Venencia, Sanjeev Bhoi

Abstract:

Coagulopathy of trauma is an early endogenous coagulation abnormality that occurs shortly resulting in high mortality. In emergency trauma situations, viscoelastic tests may be better in identifying the various phenotypes of coagulopathy and demonstrate the contribution of platelet function to coagulation. We aimed to determine thrombin generation and clot strength, by estimating a ratio of Maximum amplitude and R-time (MA-R ratio) for identifying trauma coagulopathy and predicting subsequent mortality. Methods: We conducted a prospective cohort analysis of acutely injured trauma patients of the adult age groups (18- 50 years), admitted within 24hrs of injury, for one year at a Level I trauma center and followed up on 3rd day and 5th day of injury. Patients with h/o coagulation abnormalities, liver disease, renal impairment, with h/o intake of drugs were excluded. Thromboelastography was done and a ratio was calculated by dividing the MA by the R-time (MA-R). Patients were further stratified into sub groups based on the calculated MA-R quartiles. First sampling was done within 24 hours of injury; follow up on 3rd and 5thday of injury. Mortality was the primary outcome. Results: 100 acutely injured patients [average, 36.6±14.3 years; 94% male; injury severity score 12.2(9-32)] were included in the study. Median (min-max) on admission MA-R ratio was 15.01(0.4-88.4) which declined 11.7(2.2-61.8) on day three and slightly rose on day 5 13.1(0.06-68). There were no significant differences between sub groups in regard to age, or gender. In the lowest MA-R ratios subgroup; MA-R1 (<8.90; n = 27), injury severity score was significantly elevated. MA-R2 (8.91-15.0; n = 23), MA-R3 (15.01-19.30; n = 24) and MA-R4 (>19.3; n = 26) had no difference between their admission laboratory investigations, however slight decline was observed in hemoglobin, red blood cell count and platelet counts compared to the other subgroups. Also significantly prolonged R time, shortened alpha angle and MA were seen in MA-R1. Elevated incidence of mortality also significantly correlated with on admission low MA-R ratios (p 0.003). Temporal changes in the MA-R ratio did not correlated with mortality. Conclusion: The MA-R ratio provides a snapshot of early clot function, focusing specifically on thrombin burst and clot strength. In our observation, patients with the lowest MA-R time ratio (MA-R1) had significantly increased mortality compared with all other groups (45.5% MA-R1 compared with <25% in MA-R2 to MA-R3, and 9.1% in MA-R4; p < 0.003). Maximum amplitude and R-time may prove highly useful to predict at-risk patients early, when other physiologic indicators are absent.

Keywords: coagulopathy, trauma, thromboelastography, mortality

Procedia PDF Downloads 174

Authors: Yessi Nirwana Kurniadi, Nira Yunita Permata

Abstract:

Coastline is vulnerable to coastal erosion which damage infrastructure and buildings. Floating breakwaters are applied in order to minimize material cost but still can reduce wave height. In this paper, we investigated floating breakwater anchored by piles based on experimental study in the laboratory with model scale 1:8. Two type of floating model were tested with several combination wave height, wave period and surface water elevation to determined transmission coefficient. This experimental study proved that floating breakwater with piles can prevent wave height up to 27 cm. The physical model shows that ratio of depth to wave length is less than 0.6 and ratio of model width to wave length is less than 0.3. It is confirmed that if those ratio are less than those value, the transmission coefficient is 0.5. The result also showed that the first type model of floating breakwater can reduce wave height by 60.4 % while the second one can reduce up to 55.56 %.

Keywords: floating breakwater, experimental study, pile, transimission coefficient

Procedia PDF Downloads 530

Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

Abstract:

Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

Procedia PDF Downloads 330

Authors: Sumit Sharma, Rakesh Chandra, Pramod Kumar, Navin Kumar

Abstract:

Molecular dynamics (MD) simulation has been used to study the effect of carbon nanofiber (CNF) volume fraction (Vf) and aspect ratio (l/d) on mechanical properties of CNF reinforced polypropylene (PP) composites. Materials Studio 5.5 has been used as a tool for finding the modulus and damping in composites. CNF composition in PP was varied by volume from 0 to 16%. Aspect ratio of CNF was varied from l/d=5 to l/d=100. To the best of the knowledge of the authors, till date there is no study, either experimental or analytical, which predict damping for CNF-PP composites at the nanoscale. Hence, this will be a valuable addition in the area of nanocomposites. Results show that with only 2% addition by volume of CNF in PP, E11 increases 748%. Increase in E22 is very less in comparison to the increase in E11. With increase in CNF aspect ratio (l/d) till l/d=60, the longitudinal loss factor (η11) decreases rapidly. Results of this study have been compared with those available in literature.

Keywords: carbon nanofiber, elasticity, mechanical properties, molecular dynamics

Procedia PDF Downloads 484

Authors: Swarnalata Sahoo, Smita Mohanty, S. K. Nayak

Abstract:

Environmentally friendly Polyurethane(PU) synthesis from Castor oil(CO) has been studied extensively. Probably due to high proportion of fatty hydroxy acids and unsaturated bond, CO showed better performance than other oil, can be easily utilized as commercial applications. In this work, cured PU polymers having different –NCO/OH ratio with and without catalyst were synthesized by using partially biobased Isocyanate with castor oil (CO). Curing time has been studied by observing at the time of reaction, which can be confirmed by AT-FTIR. DSC has been studied to monitor the reaction between CO & Isocyanates using non Isothermal process. Curing kinetics have also been studied to investigate the catalytic effect of the NCO / OH ratio of Polyurethane. Adhesion properties were evaluated from Lapshear test. Tg of the PU polymer was evaluated by DSC which can be compared by DMA. Surface Properties were studied by contact angle measurement. Improvement of the interfacial adhesion between the nonpolar surface of Aluminum substrate and the polar adhesive has been studied by modifying surface.

Keywords: polyurethane, partially bio-based isocyanate, castor oil, catalyst

Procedia PDF Downloads 450

Authors: Jingting Luo, Yong Wang, Ying Wang

Abstract:

Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

Procedia PDF Downloads 141