Search results for: single detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7590

Search results for: single detection

3660 Ductility Reduction Factors for Displacement Spectra Corresponding to Soft Soil Zone of the Valley of Mexico

Authors: Noé D. Lazos-Gallardo, Sonia E. Ruiz, Federico Valenzuela-Beltran

Abstract:

A simplified mathematical expression to estimate ductility reduction factors of the displacement spectra corresponding to the soft soil zone of Mexico City is proposed. The aim is to allow a better characterization of the displacement spectra and provide a simple expression to be used in displacement based design (DBD). Emphasis is on the Mexico City Building Code. The study is based on the analysis of single degree of freedom (SDOF) systems with elasto-plastic hysteretic behavior. Several seismic ground motions corresponding to subduction events with magnitudes equal to or greater than 6 and recorded in different stations of Mexico City are used. The proposed expression involves the ratio of elastic and inelastic pseudo-aceleration spectra, and depends on factors such the ductility demand and the vibration period of the structural system. The resulting ductility reduction factors obtained in this study are compared with others existing in the literature, and their advantages and disadvantages are discussed.

Keywords: displacement based design, displacements spectrum, ductility reduction factors, soft soil

Procedia PDF Downloads 158
3659 Analysis of Microbiological Quality and Detection of Antibiotic Residue in Bovine Raw Milk Produced in Blida State, Algeria

Authors: M. N. Boukhatem, M. A. Ferhat, K. Mansour

Abstract:

Bovine raw milk represents a favorable environment for the growth of several food-spoilage strains and some pathogens. It must meet stringent standards to ensure the highest microbiological and toxicological qualities.In order to assess the microbiological risks associated with the consumption of this food, we conducted this study to determine the microbiological quality of bovine raw milk (54 samples) commercialized at the state of Blida (Algeria). The samples analyzed were unsatisfactory in terms of total flora where 61.11% of samples were considered as non acceptable in terms of quality standards, fecal coliforms (40.74%), fecal streptococci (55.55%) and staphylococci (74.07%). Salmonella and Clostridium strains were not detected in all the samples. Furthermore, antibiotic residues were found in 26% of analysed samples. These results reflect non-compliance with the rules of good hygiene practices at milking, storage, transportatio, and sale of milk. Bovine raw milk consumed presents a serious health risk to the population of the study areas.The livestock coaching actors and dissemination of good hygiene practices throughout the production chain are needed to improve the quality of local milk.

Keywords: bovine raw milk, microbiological quality, fecal coliforms, antibiotic residue, Blida state

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3658 CLOUD Japan: Prospective Multi-Hospital Study to Determine the Population-Based Incidence of Hospitalized Clostridium difficile Infections

Authors: Kazuhiro Tateda, Elisa Gonzalez, Shuhei Ito, Kirstin Heinrich, Kevin Sweetland, Pingping Zhang, Catia Ferreira, Michael Pride, Jennifer Moisi, Sharon Gray, Bennett Lee, Fred Angulo

Abstract:

Clostridium difficile (C. difficile) is the most common cause of antibiotic-associated diarrhea and infectious diarrhea in healthcare settings. Japan has an aging population; the elderly are at increased risk of hospitalization, antibiotic use, and C. difficile infection (CDI). Little is known about the population-based incidence and disease burden of CDI in Japan although limited hospital-based studies have reported a lower incidence than the United States. To understand CDI disease burden in Japan, CLOUD (Clostridium difficile Infection Burden of Disease in Adults in Japan) was developed. CLOUD will derive population-based incidence estimates of the number of CDI cases per 100,000 population per year in Ota-ku (population 723,341), one of the districts in Tokyo, Japan. CLOUD will include approximately 14 of the 28 Ota-ku hospitals including Toho University Hospital, which is a 1,000 bed tertiary care teaching hospital. During the 12-month patient enrollment period, which is scheduled to begin in November 2018, Ota-ku residents > 50 years of age who are hospitalized at a participating hospital with diarrhea ( > 3 unformed stools (Bristol Stool Chart 5-7) in 24 hours) will be actively ascertained, consented, and enrolled by study surveillance staff. A stool specimen will be collected from enrolled patients and tested at a local reference laboratory (LSI Medience, Tokyo) using QUIK CHEK COMPLETE® (Abbott Laboratories). which simultaneously tests specimens for the presence of glutamate dehydrogenase (GDH) and C. difficile toxins A and B. A frozen stool specimen will also be sent to the Pfizer Laboratory (Pearl River, United States) for analysis using a two-step diagnostic testing algorithm that is based on detection of C. difficile strains/spores harboring toxin B gene by PCR followed by detection of free toxins (A and B) using a proprietary cell cytotoxicity neutralization assay (CCNA) developed by Pfizer. Positive specimens will be anaerobically cultured, and C. difficile isolates will be characterized by ribotyping and whole genomic sequencing. CDI patients enrolled in CLOUD will be contacted weekly for 90 days following diarrhea onset to describe clinical outcomes including recurrence, reinfection, and mortality, and patient reported economic, clinical and humanistic outcomes (e.g., health-related quality of life, worsening of comorbidities, and patient and caregiver work absenteeism). Studies will also be undertaken to fully characterize the catchment area to enable population-based estimates. The 12-month active ascertainment of CDI cases among hospitalized Ota-ku residents with diarrhea in CLOUD, and the characterization of the Ota-ku catchment area, including estimation of the proportion of all hospitalizations of Ota-ku residents that occur in the CLOUD-participating hospitals, will yield CDI population-based incidence estimates, which can be stratified by age groups, risk groups, and source (hospital-acquired or community-acquired). These incidence estimates will be extrapolated, following age standardization using national census data, to yield CDI disease burden estimates for Japan. CLOUD also serves as a model for studies in other countries that can use the CLOUD protocol to estimate CDI disease burden.

Keywords: Clostridium difficile, disease burden, epidemiology, study protocol

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3657 The Role of Okra (Abelmoschus esculentus Linn.) on Lipopolysaccharide-Induced Reactive Oxygen Species and Inflammatory Mediator in BV2 Microglial Cells

Authors: Nootchanat Mairuae, Walaiporn Tongjaroenbuangam, Chalisa Louicharoen Cheepsunthorn, Poonlarp Cheepsunthorn

Abstract:

The aim of this study was to investigate the anti-oxidative effect, the anti-inflammatory effects, and the molecular mechanisms of okra (Abelmoschus esculentus Linn.) on lipopolysaccharide (LPS)-stimulated BV2 microglial cells. The BV2 cells were treated with LPS in the presence or absence of okra. Reactive oxygen species (ROS) and nitric oxide (NO) production were measured using the ROS detection reagent DCF-DA and the Griess reaction, respectively. The phosphorylation levels of nuclear factor-kappa B (NF-kB) p65 was detected by Western blot assay. Treatment of BV2 microglia cells with okra was found to significantly suppress the LPS-induced inflammatory mediator NO as well as ROS compared to untreated cells. The levels of LPS-induced NF-kB p65 phosphorylation were significantly decreased following okra treatment too. These results show that okra exerts anti-oxidative and anti-inflammatory effects in LPS-stimulated BV2 microglial cells by suppressing the NF-κB pathway. This suggests okra might be a valuable agent for treatment of anti-neuroinflammatory diseases mediated by microglial cells.

Keywords: Abelmoschus esculentus Linn, microglia, neuroinflammation, reactive oxygen spicy

Procedia PDF Downloads 268
3656 Analysis of the Gait Characteristics of Soldier between the Normal and Loaded Gait

Authors: Ji-il Park, Min Kyu Yu, Jong-woo Lee, Sam-hyeon Yoo

Abstract:

The purpose of this research is to analyze the gait strategy between the normal and loaded gait. To this end, five male participants satisfied two conditions: the normal and loaded gait (backpack load 25.2 kg). As expected, results showed that additional loads elicited not a proportional increase in vertical and shear ground reaction force (GRF) parameters but also increase of the impulse, momentum and mechanical work. However, in case of the loaded gait, the time duration of the double support phase was increased unexpectedly. It is because the double support phase which is more stable than the single support phase can reduce instability of the loaded gait. Also, the directions of the pre-collision and after-collision were moved upward and downward compared to the normal gait. As a result, regardless of the additional backpack load, the impulse-momentum diagram during the step-to-step transition was maintained such as the normal gait. It means that human walk efficiently to keep stability and minimize total net works in case of the loaded gait.

Keywords: normal gait, loaded gait, impulse, collision, gait analysis, mechanical work, backpack load

Procedia PDF Downloads 278
3655 Comparing the Detection of Autism Spectrum Disorder within Males and Females Using Machine Learning Techniques

Authors: Joseph Wolff, Jeffrey Eilbott

Abstract:

Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

Procedia PDF Downloads 191
3654 Comparison of Dynamic Characteristics of Railway Bridge Spans to Know the Health of Elastomeric Bearings Using Tri Axial Accelerometer Sensors

Authors: Narayanakumar Somasundaram, Venkat Nihit Chirivella, Venkata Dilip Kumar Pasupuleti

Abstract:

Ajakool, India, has a multi-span bridge that is constructed for rail transport with a maximum operating speed of 100 km/hr. It is a standard RDSO design of a PSC box girder carrying a single railway track. The Structural Health Monitoring System (SHM) is designed and installed to compare and analyze the vibrations and displacements on the bridge due to different live loads from moving trains. The study is conducted for three different spans of the same bridge to understand the health of the elastomeric bearings. Also, to validate the same, a three-dimensional finite element model is developed, and modal analysis is carried out. The proposed methodology can help in detecting deteriorated elastomeric bearings using only wireless tri-accelerometer sensors. Detailed analysis and results are presented in terms of mode shapes, accelerations, displacements, and their importance to each other. This can be implemented with a lot of ease and can be more accurate.

Keywords: dynamic effects, vibration analysis, accelerometer sensors, finite element analysis, structural health monitoring, elastomeric bearing

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3653 Optimization and Vibration Suppression of Double Tuned Inertial Mass Damper of Damped System

Authors: Chaozhi Yang, Xinzhong Chen, Guoqing Huang

Abstract:

Inerter is a two-terminal inertial element that can produce apparent mass far larger than its physical mass. A double tuned inertial mass damper (DTIMD) is developed by combining a spring with an inerter and a dashpot in series to replace the viscous damper of a tuned mass damper (TMD), and its performance is investigated. Firstly, the DTIMD is optimized numerically with H∞ and H2 methods considering the system’s damping based on the single-degree-of-freedom (SDOF)-DTIMD system, and the optimal structural parameters are obtained. Then, compared with a TMD, the control effect of the DTIMD with the optimal structural parameters on wind-induced vibration of a wind turbine in downwind direction under the shutdown condition is studied. The results demonstrate that the vibration suppression of the DTIMD is superior than that of a TMD at the same mass ratio. And at the identical vibration suppression, the tuned mass of the DTIMD can be reduced by up to 40% compared with a TMD.

Keywords: wind-induced vibration, vibration control, inerter, tuned mass damper, damped system

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3652 Hydrogenation of CO2 to Methanol over Copper-Zinc Oxide-Based Catalyst

Authors: S. F. H. Tasfy, N. A. M. Zabidi, M. S. Shaharun

Abstract:

Carbon dioxide is highly thermochemical stable molecules where it is very difficult to activate the molecule and achieve higher catalytic conversion into alcohols or other hydrocarbon compounds. In this paper, series of the bimetallic Cu/ZnO-based catalyst supported by SBA-15 were systematically prepared via impregnation technique with different Cu: Zn ratio for hydrogenation of CO2 to methanol. The synthesized catalysts were characterized by transmission electron microscopy (TEM), temperature programmed desorption, reduction, oxidation and pulse chemisorption (TPDRO), and surface area determination was also performed. All catalysts were tested with respect to the hydrogenation of CO2 to methanol in microactivity fixed-bed reactor at 250oC, 2.25 MPa, and H2/CO2 ratio of 3. The results demonstrate that the catalytic structure, activity, and methanol selectivity was strongly affected by the ratio between Cu: Zn, Where higher catalytic activity of 14 % and methanol selectivity of 92 % was obtained over Cu/ZnO-SBA-15 catalyst with Cu:Zn ratio of 7:3 wt. %. Comparing with the single catalyst, the synergetic between Cu and Zn provides additional active sites to adsorb more H2 and CO2 and accelerate the CO2 conversion, resulting in higher methanol production under mild reaction conditions.

Keywords: hydrogenation of carbon dioxide, methanol synthesis, Cu/ZnO-based catalyst, mesoporous silica (SBA-15), metal ratio

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3651 Scalar Modulation Technique for Six-Phase Matrix Converter Fed Series-Connected Two-Motor Drives

Authors: A. Djahbar, M. Aillerie, E. Bounadja

Abstract:

In this paper we treat a new structure of a high-power actuator which is used to either industry or electric traction. Indeed, the actuator is constituted by two induction motors, the first is a six-phase motor connected in series with another three-phase motor via the stators. The whole is supplied by a single static converter. Our contribution in this paper is the optimization of the system supply source. This is feeding the multimotor group by a direct converter frequency without using the DC-link capacitor. The modelling of the components of multimotor system is presented first. Only the first component of stator currents is used to produce the torque/flux of the first machine in the group. The second component of stator currents is considered as additional degrees of freedom and which can be used for power conversion for the other connected motors. The decoupling of each motor from the group is obtained using the direct vector control scheme. Simulation results demonstrate the effectiveness of the proposed structure.

Keywords: induction machine, motor drives, scalar modulation technique, three-to-six phase matrix converter

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3650 Cyber-Softbook: A Platform for Collaborative Content Development and Delivery for Cybersecurity Education

Authors: Eniye Tebekaemi, Martin Zhao

Abstract:

The dichotomy between the skills set of newly minted college graduates and the skills required by cybersecurity employers is on the rise. Colleges are struggling to cope with the rapid pace of technology evolution using outdated tools and practices. Industries are getting frustrated due to the need to retrain fresh college graduates on skills they should have acquired. There is a dire need for academic institutions to develop new tools and systems to deliver cybersecurity education to meet the ever-evolving technology demands of the industry. The Cyber-Softbook project’s goal is to bridge the tech industry and tech education gap by providing educators a framework to collaboratively design, manage, and deliver cybersecurity academic courses that meet the needs of the tech industry. The Cyber-Softbook framework, when developed, will provide a platform for academic institutions and tech industries to collaborate on tech education and for students to learn about cybersecurity with all the resources they need to understand concepts and gain valuable skills available on a single platform.

Keywords: cybersecurity, education, skills, labs, curriculum

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3649 Prediction of Compressive Strength Using Artificial Neural Network

Authors: Vijay Pal Singh, Yogesh Chandra Kotiyal

Abstract:

Structures are a combination of various load carrying members which transfer the loads to the foundation from the superstructure safely. At the design stage, the loading of the structure is defined and appropriate material choices are made based upon their properties, mainly related to strength. The strength of materials kept on reducing with time because of many factors like environmental exposure and deformation caused by unpredictable external loads. Hence, to predict the strength of materials used in structures, various techniques are used. Among these techniques, Non-Destructive Techniques (NDT) are the one that can be used to predict the strength without damaging the structure. In the present study, the compressive strength of concrete has been predicted using Artificial Neural Network (ANN). The predicted strength was compared with the experimentally obtained actual compressive strength of concrete and equations were developed for different models. A good co-relation has been obtained between the predicted strength by these models and experimental values. Further, the co-relation has been developed using two NDT techniques for prediction of strength by regression analysis. It was found that the percentage error has been reduced between the predicted strength by using combined techniques in place of single techniques.

Keywords: rebound, ultra-sonic pulse, penetration, ANN, NDT, regression

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3648 Health Advocacy in Medical School: An American Survey on Attitudes and Engagement in Clerkships

Authors: Rachel S. Chang, Samuel P. Massion, Alan Z. Grusky, Heather A. Ridinger

Abstract:

Introduction Health advocacy is defined as activities that improve access to care, utilize resources, address health disparities, and influence health policy. Advocacy is increasingly being recognized as a critical component of a physician’s role, as understanding social determinants of health and improving patient care are important aspects within the American Medical Association’s Health Systems Science framework. However, despite this growing prominence, educational interventions that address advocacy topics are limited and variable across medical school curricula. Furthermore, few recent studies have evaluated attitudes toward health advocacy among physicians-in-training in the United States. This study examines medical student attitudes towards health advocacy, along with perceived knowledge, ability, and current level of engagement with health advocacy during their clerkships. Methods This study employed a cross-sectional survey design using a single anonymous, self-report questionnaire to all second-year medical students at Vanderbilt University School of Medicine (n=96) in December 2020 during clerkship rotations. The survey had 27 items with 5-point Likert scale (15), multiple choice (11), and free response questions (1). Descriptive statistics and thematic analysis were utilized to analyze responses. The study was approved by the Vanderbilt University Institutional Review Board. Results There was an 88% response rate among second-year clerkship medical students. A majority (83%) agreed that formal training in health advocacy should be a mandatory part of the medical student curriculum Likewise, 83% of respondents felt that acting as a health advocate or patients should be part of their role as a clerkship student. However, a minority (25%) felt adequately prepared. While 72% of respondents felt able to identify a psychosocial need, 18% felt confident navigating the healthcare system and only 9% felt able to connect a patient to a psychosocial resource to fill that gap. 44% of respondents regularly contributed to conversations with their medical teams when discussing patients’ social needs, such as housing insecurity, financial insecurity, or legal needs. On average, respondents reported successfully connecting patients to psychosocial resources 1-2 times per 8-week clerkship block. Barriers to participating in health advocacy included perceived time constraints, lack of awareness of resources, lower emphasis among medical teams, and scarce involvement with social work teams. Conclusions In this single-institutional study, second-year medical students on clerkships recognize the importance of advocating for patients and support advocacy training within their medical school curriculum. However, their perceived lack of ability to navigate the healthcare system and connect patients to psychosocial resources, result in students feeling unprepared to advocate as effectively as they hoped during their clerkship rotations. Our results support the ongoing need to equip medical students with training and resources necessary for them to effectively act as advocates for patients.

Keywords: clerkships, medical students, patient advocacy, social medicine

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3647 Nafion Multiwalled Carbon Nano Tubes Composite Film Modified Glassy Carbon Sensor for the Voltammetric Estimation of Dianabol Steroid in Pharmaceuticals and Biological Fluids

Authors: Nouf M. Al-Ourfi, A. S. Bashammakh, M. S. El-Shahawi

Abstract:

The redox behavior of dianabol steroid (DS) on Nafion Multiwalled Carbon nano -tubes (MWCNT) composite film modified glassy carbon electrode (GCE) in various buffer solutions was studied using cyclic voltammetry (CV) and differential pulse- adsorptive cathodic stripping voltammetry (DP-CSV) and successfully compared with the results at non modified bare GCE. The Nafion-MWCNT composite film modified GCE exhibited the best electrochemical response among the two electrodes for the electro reduction of DS that was inferred from the EIS, CV and DP-CSV. The modified sensor showed a sensitive, stable and linear response in the concentration range of 5 – 100 nM with a detection limit of 0.08 nM. The selectivity of the proposed sensor was assessed in the presence of high concentration of major interfering species. The analytical application of the sensor for the quantification of DS in pharmaceutical formulations and biological fluids (urine) was determined and the results demonstrated acceptable recovery and RSD of 5%. Statistical treatment of the results of the proposed method revealed no significant differences in the accuracy and precision. The relative standard deviations for five measurements of 50 and 300 ng mL−1 of DS were 3.9 % and 1.0 %, respectively.

Keywords: dianabol steroid, determination, modified GCE, urine

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3646 Evaluating Portfolio Performance by Highlighting Network Property and the Sharpe Ratio in the Stock Market

Authors: Zahra Hatami, Hesham Ali, David Volkman

Abstract:

Selecting a portfolio for investing is a crucial decision for individuals and legal entities. In the last two decades, with economic globalization, a stream of financial innovations has rushed to the aid of financial institutions. The importance of selecting stocks for the portfolio is always a challenging task for investors. This study aims to create a financial network to identify optimal portfolios using network centralities metrics. This research presents a community detection technique of superior stocks that can be described as an optimal stock portfolio to be used by investors. By using the advantages of a network and its property in extracted communities, a group of stocks was selected for each of the various time periods. The performance of the optimal portfolios compared to the famous index. Their Sharpe ratio was calculated in a timely manner to evaluate their profit for making decisions. The analysis shows that the selected potential portfolio from stocks with low centrality measurement can outperform the market; however, they have a lower Sharpe ratio than stocks with high centrality scores. In other words, stocks with low centralities could outperform the S&P500 yet have a lower Sharpe ratio than high central stocks.

Keywords: portfolio management performance, network analysis, centrality measurements, Sharpe ratio

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3645 A Study on the False Alarm Rates of MEWMA and MCUSUM Control Charts When the Parameters Are Estimated

Authors: Umar Farouk Abbas, Danjuma Mustapha, Hamisu Idi

Abstract:

It is now a known fact that quality is an important issue in manufacturing industries. A control chart is an integrated and powerful tool in statistical process control (SPC). The mean µ and standard deviation σ parameters are estimated. In general, the multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) are used in the detection of small shifts in joint monitoring of several correlated variables; the charts used information from past data which makes them sensitive to small shifts. The aim of the paper is to compare the performance of Shewhart xbar, MEWMA, and MCUSUM control charts in terms of their false rates when parameters are estimated with autocorrelation. A simulation was conducted in R software to generate the average run length (ARL) values of each of the charts. After the analysis, the results show that a comparison of the false alarm rates of the charts shows that MEWMA chart has lower false alarm rates than the MCUSUM chart at various levels of parameter estimated to the number of ARL0 (in control) values. Also noticed was that the sample size has an advert effect on the false alarm of the control charts.

Keywords: average run length, MCUSUM chart, MEWMA chart, false alarm rate, parameter estimation, simulation

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3644 Tuberculosis in Patients with HIV-Infection in Russia: Cohort Study over the Period of 2015-2016 Years

Authors: Marina Nosik, Irina Rymanova, Konstantin Ryzhov, Joan Yarovaya, Alexander Sobkin

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Tuberculosis (TB) associated with HIV is one of the top causes of death worldwide. However, early detection and treatment of TB in HIV-infected individuals significantly reduces the risk of developing severe forms of TB and mortality. The goal of the study was to analyze the peculiarities of TB associated with HIV infection. Over the period of 2015-2016 a retrospective cohort study was conducted among 377 patients with TB/HIV co-infection who attended the Moscow Tuberculosis Clinic. The majority of the patients was male (64,5%). The median age was: men 37,9 (24÷62) and women 35,4 (22÷72) years. The most prevalent age group was 30-39 years both for men and women (73,3% and 54,7%, respectively). The ratio of patients in age group 50-59 and senior was 3,9%. Socioeconomic status of patients was rather low: only 2.3% of patients had a university degree; 76,1% was unemployed (of whom 21,7% were disabled). Most patients had disseminated pulmonary tuberculosis in the phase of infiltration/ decay (41,5%). The infiltrative TB was detected in 18,9% of patients; 20,1% patients had tuberculosis of intrathoracic lymph nodes. The occurrence of MDR-TB was 16,8% and XDR-TB – 17,9%. The number of HIV-positive patients with newly diagnosed TB was n=261(69,2%). The active TB-form (MbT+) among new TB/HIV cases was 44,7 %. The severe clinical forms of TB and a high TB incidence rate among HIV-infected individuals alongside with a large number of cases of newly diagnosed tuberculosis, indicate the need for more intense interaction with TB services for timely diagnosis of TB which will optimize treatment outcomes.

Keywords: HIV, tuberculosis (TB), TB associated with HIV, multidrug-resistant TB (MDR-TB)

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3643 Estimating Gait Parameter from Digital RGB Camera Using Real Time AlphaPose Learning Architecture

Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

Abstract:

Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

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3642 Seismic Investigation on the Effect of Surface Structures and Twin Tunnel on the Site Response in Urban Areas

Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Site response has a profound effect on earthquake damages. Seismic interaction of urban tunnels with surface structures could also affect seismic site response. Here, we use FLAC 2D to investigate the interaction of a single tunnel and twin tunnels-surface structures on the site response. Soil stratification and properties are selected based on Line. No 7 of the Tehran subway. The effect of surface structure is considered in two ways: Equivalent surcharge and geometrical modeling of the structure. Comparison of the results shows that consideration of the structure geometry is vital in dynamic analysis and leads to the changes in the magnitude of displacements, accelerations and response spectrum. Therefore it is necessary for the surface structures to be wholly modeled and not just considered as a surcharge in dynamic analysis. The use of twin tunnel also leads to the reduction of dynamic residual settlement.

Keywords: superstructure, tunnel, site response, surcharge, interaction

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3641 Clustering of Association Rules of ISIS & Al-Qaeda Based on Similarity Measures

Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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3640 First-Principles Modeling of Nanoparticle Magnetization, Chaining, and Motion

Authors: Pierce Radecki, Pulkit Malik, Bharath Ramaswamy, Ben Shapiro

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The ability to effectively design and test magnetic nanoparticles for controlled movement has been an elusive goal in the design of these particles. Magnetic nanoparticles of various characteristics have been created for use towards therapeutic effects, however the challenge of designing for controlled movement remains unmet. A step towards design in this aspect is a first principles model that captures and predicts the behaviors of particles in a magnetic field. The model is governed by four forces acting on the particles, the magnetic gradient, the dipole-dipole forces, the steric forces, and the viscous drag force. The particles are multi-core or single core, and incorporate a preferred magnetization axis. Particles exhibit behaviors, such as chaining, in simulations that are similar to those witnessed through experimentation. Currently, experimental results are being compared to the modeling results for verification of the model, through the analysis of chaining behaviors. This modeling system will be used in designing magnetic nanoparticles for specific chaining and movement behaviors.

Keywords: controlled movement, modeling, magnetic nanoparticles, nanoparticle design

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3639 Integration of Rapid Generation Technology in Pulse Crop Breeding

Authors: Saeid H. Mobini, Monika Lulsdorf, Thomas D. Warkentin

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The length of the breeding cycle from seed to seed is a limiting factor in the development of improved homozygous lines for breeding or recombinant inbred lines (RILs) for genetic analysis. The objective of this research was to accelerate the production of field pea RILs through application of rapid generation technology (RGT). RGT is based on the principle of growing miniature plants in an artificial medium under controlled conditions, and allowing them to produce a few flowers which develop seeds that are harvested prior to normal seed maturity. We aimed to maintain population size and genetic diversity in regeneration cycles. The effects of flurprimidol (a gibberellin synthesis inhibitor), plant density, hydroponic system, scheduled fertilizer applications, artificial light spectrum, photoperiod, and light/dark temperature were evaluated in the development of RILs from a cross between cultivars CDC Dakota and CDC Amarillo. The main goal was to accelerate flowering while reducing maintenance and space costs. In addition, embryo rescue of immature seeds was tested for shortening the seed fill period. Data collected over seven generations included plant height, the percentage of plant survival, flowering rate, seed setting rate, the number of seeds per plant, and time from seed to seed. Applying 0.6 µM flurprimidol reduced the internode length. Plant height was decreased to approximately 32 cm allowing for higher plant density without a delay in flowering and seed setting rate. The three light systems (T5 fluorescent bulbs, LEDs, and High Pressure Sodium +Metal-halide lamp) evaluated did not differ significantly in terms of flowering time in field pea. Collectively, the combination of 0.6 µM flurprimidol, 217 plant. m-2, 20 h photoperiod, 21/16 oC light/dark temperature in a hydroponic system with vermiculite substrate, applying scheduled fertilizer application based on growth stage, and 500 µmole.m-2.s-1 light intensity using T5 bulbs resulted in 100% of plants flowering within 34 ± 3 days and 96.5% of plants completed seed setting in 68.2 ± 3.6 days, i.e., 30-45 days/generation faster than conventional single seed descent (SSD) methods. These regeneration cycles were reproducible consistently. Hence, RGT could double (5.3) generations per year, using 3% occupying space, compared to SSD (2-3 generation/year). Embryo rescue of immature seeds at 7-8 mm stage, using commercial fertilizer solutions (Holland’s Secret™) showed seed setting rate of 95%, while younger embryos had lower germination rate. Mature embryos had a seed setting rate of 96.5% without either hormones or sugar added. So, considering the higher cost of embryo rescue using a procedure which requires skill, additional materials, and expenses, it could be removed from RGT with a further cost saving, and the process could be stopped between generations if required.

Keywords: field pea, flowering, rapid regeneration, recombinant inbred lines, single seed descent

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3638 Analysis and Modeling of Vibratory Signals Based on LMD for Rolling Bearing Fault Diagnosis

Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

Abstract:

The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally non-stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. the results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, local mean decomposition, rolling element bearing, vibration analysis

Procedia PDF Downloads 393
3637 Effect of Composition Fuel on Safety of Combustion Process

Authors: Lourdes I. Meriño, Viatcheslav Kafarov, Maria Gómez

Abstract:

Fuel gas used in the burner receives as contributors other gases from different processes and this result in variability in the composition, which may cause an incomplete combustion. The burners are designed to operate in a certain curve, the calorific power dependent on the pressure and gas burners. When deviation of propane and C5+ is huge, there is a large release of energy, which causes it to work out the curves of the burners, because less pressure is required to force curve into operation. That increases the risk of explosion in an oven, besides of a higher environmental impact. There should be flame detection systems, and instrumentation equipment, such as local pressure gauges located at the entrance of the gas burners, to permit verification by the operator. Additionally, distributed control systems must be configured with different combustion instruments associated with respective alarms, as well as its operational windows, and windows control guidelines of integrity, leaving the design information of this equipment. Therefore, it is desirable to analyze when a plant is taken out of service and make good operational analysis to determine the impact of changes in fuel gas streams contributors, by varying the calorific power. Hence, poor combustion is one of the cause instability in the flame of the burner and having a great impact on process safety, the integrity of individuals and teams and environment.

Keywords: combustion process, fuel composition, safety, fuel gas

Procedia PDF Downloads 481
3636 A Study of Interleukin-1β Genetic Polymorphisms in Gastric Carcinoma and Colorectal Carcinoma in Egyptian Patients

Authors: Mariam Khaled, Noha Farag, Ghada Mohamed Abdel Salam, Khaled Abu-Aisha, Mohamed El-Azizi

Abstract:

Gastric and colorectal cancers are among the most frequent causes of cancer-associated mortalities in Africa. They have been considered as a global public health concern, as nearly one million new cases are reported per year. IL-1β is a pro-inflammatory cytokine-produced by activated macrophages and monocytes- and a member of the IL-1 family. The inactive IL-1β precursor is cleaved and activated by caspase-1 enzyme, which itself is activated by the assembly of intracellular structures defined as NLRP3 (Nod Like receptor P3) inflammasomes. Activated IL-1β stimulates the Interleukin-1 receptor type-1 (IL-1R1), which is responsible for the initiation of a signal transduction pathway leading to cell proliferation. It has been proven that the IL-1β gene is a highly polymorphic gene in which single nucleotide polymorphisms (SNPs) may affect its expression. It has been previously reported that SNPs including base transitions between C and T at positions, -511 (C-T; dbSNP: rs16944) and -31 (C-T; dbSNP: rs1143627), from the transcriptional start site, contribute to the pathogenesis of gastric and colorectal cancers by affecting IL-1β levels. Altered production of IL-1β due to such polymorphisms is suspected to stimulate an amplified inflammatory response and promote Epithelial Mesenchymal Transition leading to malignancy. Allele frequency distribution of the IL-1β-31 and -511 SNPs, in different populations, and their correlation to the incidence of gastric and colorectal cancers, has been intriguing to researchers worldwide. The current study aims to investigate allele distributions of the IL-1β SNPs among gastric and colorectal cancers Egyptian patients. In order to achieve to that, 89 Biopsy and surgical specimens from the antrum and corpus mucosa of chronic gastritis subjects and gastric and colorectal carcinoma patients was collected for DNA extraction followed by restriction fragment length polymorphism polymerase chain reaction (RFLP-PCR). The amplified PCR products of IL-1β-31C > T and IL-1β-511T > C were digested by incubation with the restriction endonuclease enzymes ALu1 and Ava1. Statistical analysis was carried out to determine the allele frequency distribution in the three studied groups. Also, the effect of the IL-1β -31 and -511 SNPs on nuclear factor binding was analyzed using Fluorescence Electrophoretic Mobility Shift Assay (EMSA), preceded by nuclear factor extraction from gastric and colorectal tissue samples and LPS stimulated monocytes. The results of this study showed that a significantly higher percentage of Egyptian gastric cancer patients have a homozygous CC genotype at the IL-1β-31 position and a heterozygous TC genotype at the IL-1β-511 position. Moreover, a significantly higher percentage of the colorectal cancer patients have a homozygous CC genotype at the IL-1β-31 and -511 positions as compared to the control group. In addition, the EMSA results showed that IL-1β-31C/T and IL-1β-511T/C SNPs do not affect nuclear factor binding. Results of this study suggest that the IL-1β-31 C/T and IL-1β-511 T/C may be correlated to the incidence of gastric cancer in Egyptian patients; however, similar findings couldn’t be proven in the colorectal cancer patients group for the IL-1β-511 T/C SNP. This is the first study to investigate IL-1β -31 and -511 SNPs in the Egyptian population.

Keywords: colorectal cancer, Egyptian patients, gastric cancer, interleukin-1β, single nucleotide polymorphisms

Procedia PDF Downloads 128
3635 Stability Indicating Method Development and Validation for Estimation of Antiasthmatic Drug in Combined Dosages Formed by RP-HPLC

Authors: Laxman H. Surwase, Lalit V. Sonawane, Bhagwat N. Poul

Abstract:

A simple stability indicating high performance liquid chromatographic method has been developed for the simultaneous determination of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical dosage form using reverse phase Zorbax Eclipse Plus C8 column (250mm×4.6mm), with mobile phase phosphate buffer (0.05M KH2PO4): acetonitrile (55:45v/v) pH 3.5 adjusted with ortho-phosphoric acid, the flow rate was 1.0 mL/min and the detection was carried at 212 nm. The retention times of Levosalbutamol Sulphate and Ipratropium Bromide were 2.2007 and 2.6611 min respectively. The correlation coefficient of Levosalbutamol Sulphate and Ipratropium Bromide was found to be 0.997 and 0.998.Calibration plots were linear over the concentration ranges 10-100µg/mL for both Levosalbutamol Sulphate and Ipratropium Bromide. The LOD and LOQ of Levosalbutamol Sulphate were 2.520µg/mL and 7.638µg/mL while for Ipratropium Bromide was 1.201µg/mL and 3.640 µg/mL. The accuracy of the proposed method was determined by recovery studies and found to be 100.15% for Levosalbutamol Sulphate and 100.19% for Ipratropium Bromide respectively. The method was validated for accuracy, linearity, sensitivity, precision, robustness, system suitability. The proposed method could be utilized for routine analysis of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical capsule dosage form.

Keywords: levosalbutamol sulphate, ipratropium bromide, RP-HPLC, phosphate buffer, acetonitrile

Procedia PDF Downloads 333
3634 A Deep Learning Based Approach for Dynamically Selecting Pre-processing Technique for Images

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

Abstract:

Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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3633 Bitplanes Image Encryption/Decryption Using Edge Map (SSPCE Method) and Arnold Transform

Authors: Ali A. Ukasha

Abstract:

Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression, salt and peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

Procedia PDF Downloads 479
3632 Air Cargo Network Structure Characteristics and Robustness Analysis under the Belt and Road Area

Authors: Feng-jie Xie, Jian-hong Yan

Abstract:

Based on the complex network theory, we construct the air cargo network of the Belt and Road area, analyze its regional distribution and structural characteristics, measure the robustness of the network. The regional distribution results show that Southeast Asia and China have the most prominent development in the air cargo network of the Belt and Road area, Central Asia is the least developed. The structure characteristics found that the air cargo network has obvious small-world characteristics; the degree distribution has single-scale property; it shows a significant rich-club phenomenon simultaneously. The network robustness is measured by two attack strategies of degree and betweenness, but the betweenness of network nodes has a greater impact on network connectivity. And identified 24 key cities that have a large impact on the robustness of the network under the two attack strategies. Based on these results, recommendations are given to maintain the air cargo network connectivity in the Belt and Road area.

Keywords: air cargo, complex network, robustness, structure properties, The Belt and Road

Procedia PDF Downloads 174
3631 Topic Modelling Using Latent Dirichlet Allocation and Latent Semantic Indexing on SA Telco Twitter Data

Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

Abstract:

Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

Procedia PDF Downloads 137