Search results for: service evaluation

Authors: Habibullah Pathan

Abstract:

The present study aims to explore problems faced by English Language Teachers (ELT) while implementing the Outcome Based Education (OBE) model in engineering universities of Sindh. OBE is an emerging model initiative of the International Engineering Alliance. Traditional educational systems are teacher-centered or curriculum-centered, in which learners are not able to achieve desired outcomes, but the OBE model enables learners to know the outcomes before the start of the program. OBE is a circular process that begins from the needs and demands of society to stakeholders who ask the experts to produce the alumnus who can fulfill the needs and ends up getting new enrollment in the respective programs who can work according to the demands. In all engineering institutions, engineering courses besides English language courses are taught on the OBE model. English language teachers were interviewed to learn the in-depth of the problems faced by them. The study found that teachers were facing problems including pedagogical, OBE training, assessment, evaluation and administrative support. This study will be a guide for public and private English language teachers to cope with these challenges while teaching the English language on the OBE model. OBE is an emerging model by which the institutions can produce such a product that can meet the demands.

Keywords: problems of ELT teachers, outcome based education (OBE), implementing, assessment

Procedia PDF Downloads 70

Authors: Ahmed Elbeheri, Tarek Zayed

Abstract:

Steel bridges deterioration has been one of the problems in North America for the last years. Steel bridges deterioration mainly attributed to the difficult weather conditions. Steel bridges suffer fatigue cracks and corrosion, which necessitate immediate inspection. Visual inspection is the most common technique for steel bridges inspection, but it depends on the inspector experience, conditions, and work environment. So many Non-destructive Evaluation (NDE) models have been developed use Non-destructive technologies to be more accurate, reliable and non-human dependent. Non-destructive techniques such as The Eddy Current Method, The Radiographic Method (RT), Ultra-Sonic Method (UT), Infra-red thermography and Laser technology have been used. Digital Image processing will be used for Corrosion detection as an Alternative for visual inspection. Different models had used grey-level and colored digital image for processing. However, color image proved to be better as it uses the color of the rust to distinguish it from the different backgrounds. The detection of the rust is an important process as it’s the first warning for the corrosion and a sign of coating erosion. To decide which is the steel element to be repainted and how urgent it is the percentage of rust should be calculated. In this paper, an image processing approach will be developed to detect corrosion and its severity. Two models were developed 1st to detect rust and 2nd to detect rust percentage.

Keywords: steel bridge, bridge inspection, steel corrosion, image processing

Procedia PDF Downloads 289

Authors: M. Khaledi Pour, P. Akbartehrani, M. Amini, M. Khani, M. Mohajeri Tehrani, R. Radi, B. Shokri

Abstract:

Diabetic Foot Ulcer (DFU) is one of the costly severe complications of diabetes. Neuropathy and Peripheral Arterial Disease (PAD) due to diabetes are significant causes of this complication. In 10 years the patients with DFUs are twice as likely to die as patients without DFUs. Cold Atmospheric Plasma (CAP) is a promising tool for medical purposes. CAP generate reactive species at room temperature and are effective in killing bacteria and fibroblast proliferation. These CAP-based tools produce NO, which has bactericidal and angiogenesis properties. It also showed promising effects in the DFUs surface reduction and the time to wound closure. In this paper, we evaluated the effect of the Argon Plasma Jet (APJ) on the healing process of the Wagner Grade 2 DFUs in a randomized clinical trial. The 20 kHz sinusoidal voltage frequency derives the APJ. Patients (n=20) were randomly double-blinded assigned into two groups. These groups receive the standard care (SC, n=10) and the standard care with APJ treatment (SC+APJ, n=10) for five sessions in four weeks. The results showed that the APJ treatment along standard care could reduce the wound surface by 20 percent more than the standard care. Also, It showed a more influential role in controlling wound infection.

Keywords: argon plasma jet, cold atmospheric plasma, diabetes, diabetic foot ulcer

Procedia PDF Downloads 182

Authors: Wei Zhang, Yan He, Yan Wang, Yufeng Li, Chuanpeng Hao

Abstract:

Surface roughness is an important index for evaluating surface quality, needs to be accurately measured to ensure the performance of the workpiece. The roughness measurement based on machine vision involves various image features, some of which are redundant. These redundant features affect the accuracy and speed of the visual approach. Previous research used correlation analysis methods to select the appropriate features. However, this feature analysis is independent and cannot fully utilize the information of data. Besides, blindly reducing features lose a lot of useful information, resulting in unreliable results. Therefore, the focus of this paper is on providing a redundant feature removal approach for visual roughness measurement. In this paper, the statistical methods and gray-level co-occurrence matrix(GLCM) are employed to extract the texture features of machined images effectively. Then, the principal component analysis(PCA) is used to fuse all extracted features into a new one, which reduces the feature dimension and maintains the integrity of the original information. Finally, the relationship between new features and roughness is established by the support vector machine(SVM). The experimental results show that the approach can effectively solve multi-feature information redundancy of machined surface images and provides a new idea for the visual evaluation of surface roughness.

Keywords: feature analysis, machine vision, PCA, surface roughness, SVM

Procedia PDF Downloads 201

Authors: Oznur Ispir, Oya Celebi Cakiroglu, Esengul Elibol, Emine Ceribas, Gizem Acikgoz, Hande Yesilbas, Merve Tarhan

Abstract:

This study was conducted to evaluate the academic staff teaching the 'Nursing Management' course in the undergraduate nursing programs of the state universities in Turkey and to assess the current content of the course. Design of the study is descriptive. Population of the study consists of seventy-eight undergraduate nursing programs in the state universities in Turkey. The questionnaire/survey prepared by the researchers was used as a data collection tool. The data were obtained by screening the content of the websites of nursing education programs between March and May 2016. Descriptive statistics were used to analyze the data. The research performed within the study indicated that 58% of the undergraduate nursing programs from which the data were derived were included in the school of health, 81% of the academic staff graduated from the undergraduate nursing programs, 40% worked as a lecturer and 37% specialized in a field other than the nursing. The research also implied that the above-mentioned course was included in 98% of the programs from which it was possible to obtain data. The full name of the course was 'Nursing Management' in 95% of the programs and 98% stated that the course was compulsory. Theory and application hours were 3.13 and 2.91, respectively. Moreover, the content of the course was not shared in 65% of the programs reviewed. This study demonstrated that the experience and expertise of the academic staff teaching the 'Nursing Management' course was not sufficient in the management area, and the schedule and content of the course were not sufficient although many nursing education programs provided the course. Comparison between the curricula of the course revealed significant differences.

Keywords: nursing, nursing management, nursing management course, undergraduate program

Procedia PDF Downloads 344

Authors: Zahra Khodaee

Abstract:

Environmental Justice (EJ) concept consists of multifaceted movements, community struggles, and discourses in contemporary societies that seek to reduce environmental risks, increase environmental protections, and generally reduce environmental inequalities suffered by minority and poor communities; a term that incorporates ‘environmental racism’ and ‘environmental classism,’ captures the idea that different racial and socioeconomic groups experience differential access to environmental quality. This article explores environmental justice as an urban phenomenon in urban planning and applies it in peri-urban environment of a metropolis. Tehran peri-urban environments which are the result of meeting the city- village- nature systems or «city-village junction» have gradually faced effects such as accelerated environmental decline, changes without land-use plan, and severe service deficiencies. These problems are instances of environmental injustice which make the planners to adjust the problems and use and apply the appropriate strategies and policies by looking for solutions and resorting to theories, techniques and methods related to environmental justice. In order to access to this goal, try to define environmental justice through justice and determining environmental justice indices to analysis environmental injustice in case study. Then, make an effort to introduce some criteria to select case study in two micro and micro levels. Qiyamdasht town as the peri-urban environment of Tehran metropolis is chosen and examined to show the existence of environmental injustice by questionnaire analysis and SPSS software. Finally, use AIDA technique to design a strategic plan and reduce environmental injustice in case study by introducing the better scenario to be used in policy and decision making areas.

Keywords: environmental justice, metropolis of Tehran, Qiyam, Dasht peri, urban settlement, analysis of interconnected decision area (AIDA)

Procedia PDF Downloads 470

Authors: Mehaiguene Madjid, Meddi Mohamed

Abstract:

The results of applying the model WEAP 21 or 'Water Evaluation and Planning System' in Upper and Middle Cheliff are presented in cartographic and graphic forms by considering two scenarios: -Reference scenario 1961-1990, -Climate change scenarios (low and high) for 2020 and 2050. These scenarios are presented together in the results and compared them to know the impact on aquatic systems and water resources. For the low scenario for 2050, a decrease in the rate of runoff / infiltration will be 81.4 to 3.7 Hm3 between 2010 and 2050. While for the high scenario for 2050, the reduction will be 87.2 to 78.9 Hm3 between 2010 and 2050. Comparing the two scenarios, shows that the water supplied will increase by 216.7 Hm3 to 596 Hm3 up to 2050 if we do not take account of climate change. Whereas, if climate change will decrease step by step: from 2010 to 2026: for the climate change scenario (high scenario) by 2050, water supplied from 346 Hm3 to 361 Hm3. That of the reference scenario (1961-1990) will increase to 379.7 Hm3 in 2050. This is caused by the increased demand (increased population, irrigated area, etc ). The balance water management basin is positive for the different Horizons and different situations. If we do not take account of climate change will be the outflow of 5881.4 Hm3. This excess at the basin can be used as part of a transfer for example.

Keywords: balance water, management basin, climate change scenario, Upper and Middle Cheliff

Procedia PDF Downloads 295

Authors: N. Cetinkaya, F. Erdem

Abstract:

Juncus acutus (Juncaceae) is a perennial wetland plant and it is commonly known as spiny rush or sharp rush. It is the most abundant plant in Kizilirmak grassland, Samsun, Turkey. Heavy metals are significant environmental contaminants in delta and their toxicity is an increasing problem for animals whose natural habitat is delta. The objective of this study was to evaluate heavy metal concentrations mainly As, Cd, Sb, Ba, Pb and Hg in stem and seed of Juncus acutus for grazing animals and birds in delta. The Juncus acutus stem and seed samples were collected from Kizilirmak Delta in July, August and September. Heavy metal concentrations of collected samples were analyzed by Inductively Coupled Plasma – Mass Spectrometer (ICP-MS). The obtained mean values of three months for As, Cd, Sb, Ba, Pb and Hg of stem and seed samples of Juncus acutus were 0.11 and 0.23 mg/kg; 0.07 and 0.11 mg/kg; 0.02 and 0.02 mg/kg; 5.26 and 1.75 mg/kg; 0.05 and not detectable in July respectively. Hg was not detected in both stem and seed of Juncus acutus, Pb concentration was determined only in stem of Juncus acutus but not in seed. There were no significant differences between the values of three months for As, Cd, Sb, Ba, Pb and Hg of stem and seed samples of Juncus acutus. The obtained As, Cd, Sb, Ba, Pb and Hg results of stem and seed of Juncus acutus show that seed and stem of Juncus acutus may be safely consumed for grazing animals and birds regarding to heavy metals contamination in Kizilirmak Delta.

Keywords: heavy metals, Juncus acutus, Kizilirmak Delta, wetland

Procedia PDF Downloads 118

Authors: Abdulkarim Yusuf

Abstract:

Motivation: The Nigerian economy has seen significant macroeconomic instability, fuelled mostly by an overreliance on fluctuating oil revenues. The rising disparity between tax receipts and government spending in Nigeria necessitates government borrowing to fund the anticipated pace of economic growth. Rising public debt and fiscal sustainability are limiting the government's ability to invest in key infrastructure that promotes private investment and growth in Nigeria. Objective: This paper fills an empirical research vacuum by examining the impact of public debt on fiscal sustainability in Nigeria, given the significance of fiscal stability in decreasing poverty and the constraints that an unsustainable debt burden imposes on it. Data and method: Annual time series data covering the period 1980 to 2022 exposed to conventional and structural breaks stationarity tests and the Autoregressive Distributed Lag estimation approach were adopted for this study. Results: The results reveal that domestic debt stock, debt service payment, foreign reserve stock, exchange rate, and private investment all had a major adverse effect on fiscal stability in the long and short run, corroborating the debt overhang and crowding-out hypothesis. External debt stock, prime lending rate, and degree of trade openness, which boosted fiscal stability in the long run, had a major detrimental effect on fiscal stability in the short run, whereas foreign direct investment inflows had an important beneficial impact on fiscal stability in both the long and short run. Implications: The results indicate that fiscal measures that inspire domestic resource mobilization, sustainable debt management techniques, and dependence on external debt to boost deficit financing will improve fiscal stability and drive growth.

Keywords: ARDL co-integration, debt overhang, debt servicing, fiscal stability, public debt

Procedia PDF Downloads 34

Authors: Arezoo Fallahi

Abstract:

Background and purpose: Non-alcoholic fatty liver is one of the most common liver disorders, which, as the most important cause of death from liver disease, has unpleasant consequences and complications. The aim of this study was to investigate the effect of an educational intervention based on a health belief model to prevent non-alcoholic fatty liver among women. Materials and Methods: This experimental study was performed among 110 women referring to comprehensive health service centers in Malayer City, west of Iran, in 2023. Using the available sampling method, 110 Participants were divided into experimental and control groups. The data collection tool included demographic characteristics and a questionnaire based on the health belief model. In The experimental group, three one-hour training sessions were conducted in the form of pamphlets, lectures and group discussions. Data were analyzed using SPSS software version 21, by correlation tests, paired t-tests independent t-tests. Results: The mean age of participants was 38.07±6.28 years, and Most of the participants were middle-aged, married, housewives with academic education, middle-income and overweight. After the educational intervention, the mean scores of the constructs include perceived sensitivity (p=0.01), perceived severity (p=0.01), perceived benefits (p=0.01), guidance for internal (p=0.01) and external action (p=0.01), and perceived self-efficacy (p=0.01) in the experimental group were significantly higher than the control group. The score of perceived barriers in the experimental group decreased after training. The perceived obstacles score in the test group decreased after the training (15.2 ± 3.9 v.s 11.2 ± 3.3, (p<0.01). Conclusion: The findings of the study showed that the design and implementation of educational programs based on the constructs of the health belief model can be effective in preventing women from developing higher levels of non-alcoholic fatty liver.

Keywords: health, education, believe, behaviour

Procedia PDF Downloads 30

Authors: Pei Yi Lin

Abstract:

Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

Procedia PDF Downloads 52

Authors: Pareshkumar Umedbhai Patel

Abstract:

Variety of microbes were isolated from surface of fruit and vegetables to get idea about normal flora of their surface. The process of isolation of microbes involved use of sterilized cotton swabs to wipe the surface of the samples. For isolation of Bacteria, yeast and fungi microbiological media used were nutrient agar medium, GYE agar medium and MRBA agar medium respectively. The microscopical and macroscopical characteristics of all the isolates were studied. Different plants with known antimicrobial activity were selected for obtaining samples for extraction e.g. Ficus (Ficus religosa) stem, Amla (Phyllanthus emblica) fruit, Tulsi (Ocimum tenuiflorum) leaves and Lemon grass (Cymbopogon citratus) oil. Antimicrobial activity of these samples was tested initially against known bacteria followed by study against microbes isolated from surface of vegetables and fruits. During the studies carried out throughout the work, lemongrass oil and Amla extract were found superior. Lemongrass oil and Amla extract respectively inhibited growth of 65% and 42% microbes isolated from fruit and vegetable surfaces. Rest two studied plant extracts showed only 11% of inhibition against the studied isolates. The results of isolate inhibition show the antibacterial effect of lemongrass oil better than the rest of the studied plant extracts.

Keywords: herbal extracts, vegetables, fruits, antimicrobial activity

Procedia PDF Downloads 147

Authors: Sharda Kumari, Saiman Shetty

Abstract:

Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

Procedia PDF Downloads 89

Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

Abstract:

With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

Procedia PDF Downloads 339

Authors: Yibeltal T. Bayou, Yohana S. Mashalla, Gloria Thupayagale-Tshweneagae

Abstract:

Background: Maternal mortality has been shown to be lower in urban areas than in rural areas. However, disparities for the fast-growing population of urban poor who struggle as much their rural counterparts to access quality healthcare are masked by the urban averages. The aim of this paper is to report on the findings of antenatal adequacy among slum residents in Addis Ababa, Ethiopia. Methods and Materials: A quantitative and cross-sectional community-based study design was employed. A stratified two-stage cluster sampling technique was used to determine the sample and data was collected using structured questionnaire administered to 837 women aged 15-49 years. Binary logistic regression models were employed to identify predictors of adequacy of antenatal care. Results: The majority of slum residents did not have adequate antenatal care services i.e., only 50.7%, 19.3% and 10.2% of the slum resident women initiated early antenatal care, received adequate antenatal care service contents and had overall adequate antenatal care services. Pregnancy intention, educational status and place of ANC visits were important determinant factors for adequacy of ANC in the study area. Women with secondary and above educational status were 2.9 times more likely to have overall adequate care compared to those with no formal education. Similarly, women whose last pregnancy was intended and clients of private healthcare facilities were 1.8 and 2.8 times more likely to have overall adequate antenatal care compared to those whose last pregnancy was unintended and clients of public healthcare facilities respectively. Conclusion: In order to improve ANC adequacy in the study area, the policymaking, planning, and implementation processes should focus on the poor adequacy of ANC among the disadvantaged groups in particular and the slum residents in general.

Keywords: Addis Ababa, adequacy of antenatal care, slum residents, maternal mortality

Procedia PDF Downloads 405

Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

Abstract:

Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: dynamic impact, deformable boundary conditions, finite element modelling, LS-DYNA, stainless steel pipe

Procedia PDF Downloads 136

Authors: Palash Dey, Sudip Talukdar

Abstract:

In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

Procedia PDF Downloads 236

Authors: Muhammad Tariq A. Chaudhary

Abstract:

Soil-structure interaction (SSI) in bridges under seismic excitation is a complex phenomenon which involves coupling between the non-linear behavior of bridge pier columns and SSI in the soil-foundation part. It is a common practice in the study of SSI to model the bridge piers as linear elastic while treating the soil and foundation with a non-linear or an equivalent linear modeling approach. Consequently, the contribution of soil and foundation to the SSI phenomenon is disproportionately highlighted. The present study considered non-linear behavior of bridge piers in FEM model of a 4-span, pile-supported bridge that was designed for five different soil conditions in a moderate seismic zone. The FEM model of the bridge system was subjected to a suite of 21 actual ground motions representative of three levels of earthquake hazard (i.e. Design Basis Earthquake, Functional Evaluation Earthquake and Maximum Considered Earthquake). Results of the FEM analysis were used to delineate the influence of pier column non-linearity and SSI on critical design parameters of the bridge system. It was found that pier column non-linearity influenced the bridge lateral displacement and base shear more than SSI for majority of the analysis cases for the class of bridge investigated in the study.

Keywords: bridge, FEM model, reinforced concrete pier, pile foundation, seismic loading, soil-structure interaction

Procedia PDF Downloads 220

Authors: Byung Wook Yang, Jong Dae Park, Wang Soo Shin, Ji-Hyeon Song, Seo-Yun Choi, Boo-Yong Lee, Young Tae Hahm

Abstract:

Korean ginseng (Panax ginseng C. A. Meyer) is frequently taken orally as a traditional herbal medicine with ginsenosides as the main pharmacological component in Asian countries, and its use is increasing worldwide. Recently, the increase in global temperature has been reported to cause various kinds of biological disorders induced by heat stress in human. The standardized black ginseng extract (SBGE; KGR-BG1) was developed in our biological screening experiment on the thermo-regulation, whose chemical characteristics were evaluated as ginsenoside Rg1, Rb1, Rg3(S), as well as Re, Rf, Rg2(S), Rh1(S), Rh2(S), and Rg5+Rk1. Heat stress responses such as body weight, food intake, water consumption have been measured when treated with Standardized Black Ginseng Extract (SBGE) in the animal experiment and also, biomarkers. SBGE treated group has been found to inhibit a decrease in body weight, a decrease in food intake and an increase in the water consumption when compared with non-treated group against environmental heat stress. These results suggest that SBGE might have a protective effect against environmental heat stress. And also, the several factors of stress response on the immune system need to be done for further studies and its evaluation is in progress.

Keywords: ginseng, ginsenoside, standardization, heat stress, immunomodulatory effect

Procedia PDF Downloads 282

Authors: A. Prajapati, K. L. Koo, F. Ghassemi, M. Mulimakwenda

Abstract:

In the UK, as the volume of non-linear loads connected to transmission grid continues to rise steeply, the harmonic distortion levels on transmission network are becoming a serious concern for the network owners and system operators. This paper outlines the findings of the study conducted to verify the proposal that the harmonic mitigation could be optimized and can be managed economically and effectively at the transmission network level by the Transmission Owner (TO) instead of the individual polluter connected to the grid. Harmonic mitigation studies were conducted on selected regions of the transmission network in England for recently connected offshore wind power plants to strategize and optimize selected harmonic filter options. The results – filter volume and capacity – were then compared against the mitigation measures adopted by the individual connections. Estimation ratios were developed based on the actual installed and optimal proposed filters. These estimation ratios were then used to derive harmonic filter requirements for future contracted connections. The study has concluded that a saving of 37% in the filter volume/capacity could be achieved if the TO is to centrally manage the harmonic mitigation instead of individual polluter installing their own mitigation solution.

Keywords: C-type filter, harmonics, optimization, offshore wind farms, interconnectors, HVDC, renewable energy, transmission owner

Procedia PDF Downloads 149

Authors: Aria Teimourzadeh, Marc Favier, Samaneh Kakavand

Abstract:

The emergence of social networks has revolutionized the exchange of information. Every behavior on these platforms contributes to the generation of data known as social network data that are processed, stored and published by the social network service providers. Hence, it is vital to investigate the role of these platforms in user data by considering the privacy measures, especially when we observe the increased number of individuals and organizations engaging with the current virtual platforms without being aware that the data related to their positioning, connections and behavior is uncovered and used by third parties. Performing analytics on social network datasets may result in the disclosure of confidential information about the individuals or organizations which are the members of these virtual environments. Analyzing separate datasets can reveal private information about relationships, interests and more, especially when the datasets are analyzed jointly. Intentional breaches of privacy is the result of such analysis. Addressing these privacy concerns requires an understanding of the nature of data being accumulated and relevant data privacy regulations, as well as motivations for disclosure of personal information on social network platforms. Some significant points about how user's online information is controlled by the influence of social factors and to what extent the users are concerned about future use of their personal information by the organizations, are highlighted in this paper. Firstly, this research presents a short literature review about the structure of a network and concept of privacy in Online Social Networks. Secondly, the factors of user behavior related to privacy protection and self-disclosure on these virtual communities are presented. In other words, we seek to demonstrates the impact of identified variables on user information disclosure that could be taken into account to explain the privacy preservation of individuals on social networking platforms. Thirdly, a few research directions are discussed to address this topic for new researchers.

Keywords: information disclosure, privacy measures, privacy preservation, social network analysis, user experience

Procedia PDF Downloads 267

Authors: G. Mazor, I. Ladizhensky, A. Shapiro, D. Nemirovsky

Abstract:

A lot of researches was dedicated to the evaluation of the efficiency of the uniform constant and temporary coatings enhancing a heat transfer rate. Our goal is an investigation of the sand coatings distributed by both uniform and non-uniform forms. The sand of different sizes (0.2-0.4-0.6 mm) was attached to a copper ball (30 mm diameter) surface by means of PVA adhesive as a uniform layer. At the next stage, sand spots were distributed over the ball surface with an areal density that ranges between one spot per 1.18 cm² (for low-density spots) and one spot per 0.51 cm² (for high-density spots). The spot's diameter value varied from 3 to 6.5 mm and height from 0.5 to 1.5 mm. All coatings serve as a heat transfer enhancer during the quenching in liquid nitrogen. Highest heat flux densities, achieved during quenching, lie in the range 10.8-20.2 W/cm², depending on the sand layer structure. Application of the enhancing coating increases an amount of heat, evacuated by highly effective nucleate and transition boiling, by a factor of 4.5 as compared to the bare sample. The non-uniform sand coatings were increasing the heat transfer rate value under all pool boiling conditions: nucleate boiling, transfer boiling and the most severe film boiling. A combination of uniform sand coating together with high-density sand spots increased the average heat transfer rate by a factor of 3.

Keywords: heat transfer enhancement, nucleate boiling, film boiling, transfer boiling

Procedia PDF Downloads 113

Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

Abstract:

In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the Spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are Class balancing, Data shuffling, and Standardization were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the Sequential model and Relu activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: neural network, pineapple, soluble solid content, spectroscopy

Procedia PDF Downloads 56

Authors: K. A. Ghazaryan, G. A. Gevorgyan, H. S. Movsesyan, N. P. Ghazaryan, K. V. Grigoryan

Abstract:

The heavy metal pollution degree in the soils around the Zangezur copper and molybdenum combine in Syunik Marz, Armenia was aessessed. The results of the study showed that heavy metal pollution degree in the soils mainly decreased with increasing distance from the open mine and the ore enrichment combine which indicated that the open mine and the ore enrichment combine were the main sources of heavy metal pollution. The only exception was observed in the northern part of the open mine where pollution degree in the sites (along the open mine) situated 600 meters far from the mine was higher than that in the sites located 300 meters far from the mine. This can be explained by the characteristics of relief and air currents as well as the weak vegetation cover of these sites and the characteristics of soil structure. According to geo-accumulation index (I-geo), contamination factor (Cf), contamination degree (Cd) and pollution load index (PLI) values, the pollution degree in the soils around the open mine and the ore enrichment combine was higher than that in the soils around the tailing dumps which was due to the proper and accurate operation of the Artsvanik tailing damp and the recultivation of the Voghji tailing dump. The high Cu and Mo pollution of the soils was conditioned by the character of industrial activities, the moving direction of air currents as well as the physicochemical peculiarities of the soils.

Keywords: Armenia, Zangezur copper and molybdenum combine, soil, heavy metal pollution degree

Procedia PDF Downloads 285

Authors: Liberata Borralho, Saúl N. de Jesus, Adelinda Candeias, Victória Fernández-Puig

Abstract:

In the last decades, we have witnessed a deterioration in the health of teachers worldwide, reflecting the constant social, political and economic changes. The quality of teaching and the success of students depends on the health status of the teachers, which justifies the importance of periodically evaluating their health. With this purpose, the Teacher’s Health Questionnaire was applied to 15.394 teachers teaching in Portugal and Spain (6.208 Spanish and 9.186 Portuguese) of primary and secondary education (3.482 men, 11.911 women). This questionnaire is specific and includes both the main risks of the teaching profession and the manifestations of teacher well-being, according to the definition recommended by the World Health Organization. A descriptive analysis of the results was carried out, including a study of the dimensions and the differences according to some sociodemographic and professional variables, from an analysis of variance ANOVA, applying the Bonferroni correction. Cluster analysis (K-means) allowed us to obtain cutoff scores to assess health status. The results allow concluding that Portuguese teachers perceive a poor well-being in the performance of their professional activity and that more than half present manifestations in the various dimensions of health deterioration, highlighting the exhaustion and cognitive disorders. In turn, Spanish teachers demonstrate a high level of well-being, being the musculoskeletal dimensions and cognitive disorders the main manifestations of deterioration of health.

Keywords: job prevention, occupational health, teacher’s health, teachers work risks, teacher’s well-being

Procedia PDF Downloads 223

Authors: Karen Armstrong

Abstract:

This study is a narrative inquiry into the use of simulated person methodology (SPM) in teacher education classes. This methodology -often used in medical schools- has tremendous benefits in terms of enhancing experiential education in teacher education classes. Literacy education is a major focus in elementary schools. New teachers must work with parents to ensure that children learn to read and expand their literacy horizons. The classes used in this narrative inquiry research consist of one graduate class on family literacy and two pre-service teacher education classes: literacy and culture and early and family literacy. Two scenarios were devised, both of which simulated a parent-teacher interview. In the first scenario, the parent is a reluctant father who is ashamed of his lack of reading ability and does not understand why literacy is important. His seven-year-old son, wanting to emulate his father, has suddenly transformed from an eager student to one who rejects the value of reading in loyalty to his father who cannot read. In the second scenario, a father is called in by the teacher because his son has started acting out in class. The mother in this scenario is temporarily absent from the home, and the father is now the sole caregiver. In each of the scenarios, students are the teachers who are problem-solving these dilemmas in a safe environment with the 'parent' who is a specially trained simulated person. Teacher candidates enact, with the trained simulated person, their strategies for encouraging parents to engage in the literacy development of their children. Teacher candidates attempt to offer support and encouragement to parents. This simulation strategy offers both beginning and more experienced teachers the opportunity to practice an interview with two distinct and contrasting family situations with regard to the literacy of young children. The paper discusses the details of the scenarios enacted in class and the reflective discussion through which students learn from the simulation.

Keywords: experiential education, literacy, simulated person methodology, teacher education

Procedia PDF Downloads 95

Authors: Tamara Díaz-Chang, Elizabeth-H Arredondo

Abstract:

This article presents the results of mixed approach research, where the ocular movements of students are examined while they solve questionnaires related to some abstract mathematical concepts. The objective of this research is to determine possible correlations between the parameters of ocular activity and the level of difficulty of the tasks. The difficulty level categories were established based on two types of criteria: a subjective one, through an evaluation, carried out by the subjects, and a behavioral one, related to obtaining the correct solution. Correlations of these criteria with ocular activity parameters, which were considered indicators of mental effort, were identified. The analysis of the data obtained allowed us to observe discrepancies in the categorization of difficulty levels based on subjective and behavioral criteria. There was a negative correlation of the eye movement parameters with the students' opinions on the level of difficulty of the questions, while a strong positive and significant correlation was noted between most of the parameters of ocular activity and the level of difficulty, determined by the percentage of correct answers. The results obtained by the analysis of the data suggest that eye movement parameters can be taken as indicators of the difficulty level of the tasks related to the study of some abstract mathematical concepts at the university.

Keywords: abstract mathematical concepts, cognitive neuroscience, eye-tracking, university education

Procedia PDF Downloads 104

Authors: Yafa Haron, Hanna Adami

Abstract:

Background: World Health Organization emphasizes the contribution of nurses in planning and implementing health policies and reforms. Aim: To evaluate nursing students’ attitudes towards nurses’ involvement in health policy issues. Methods: Mixed-methods; qualitative and quantitative – a descriptive study. Participants - nursing students who were enrolled in their last year in the undergraduate program (BSN). Qualitative data included two open-ended questions: What is health policy and what is the importance of studying health policy, and 18 statements on the Likert Scale range 1-5. Results: Qualitativeanalysisrevealed that the majority of students defined health policy as a set of rules and regulations that defined procedures, borders, and proper conduct. 73% of students responded that nurses should be active in policymaking, but only 22% thought that nurses were currently involved in political issues. 28% thought that nurses do not have the knowledge and the time needed (60%) for political activity. 77% thought that the work environment did not encourage nurses to be politically active. Nursing students are aware of the importance towards nurses’ involvement in health policy issues, however, they do not have role models based on their low evaluation regarding nurses’ involvement in the health policy decision making process at the local or national level. Conclusions: Results emphasize the importance and the need of implementation the recommendation to include “advance policy changes” as core competency in nursing education and practice.

Keywords: health policy, nursing education, health systems, student perceptions

Procedia PDF Downloads 85

Authors: Md. Shaheen Shah, Abdelsalam Abugharara, Dipesh Maharjan, Syed Imtiaz, Stephen Butt

Abstract:

Drilling performance is an essential goal in petroleum and mining industry. Drilling rate of penetration (ROP), which is inversely proportional to the mechanical specific energy (MSE) is influenced by numerous factors among which are the applied parameter: torque (T), weight on bit (WOB), fluid flow rate, revolution per minute (rpm), rock related parameters: rock type, rock homogeneousness, rock anisotropy orientation, and mechanical parameters: bit type, configuration of the bottom hole assembly (BHA). This paper is focused on studying the drilling performance by implementing a passive vibration assisted rotary drilling tool (pVARD) as part of the BHA through using different bit types: coring bit, roller cone bit, and PDC bit and various rock types: rock-like material, granite, sandstone, etc. The results of this study aim to produce a pVARD index for optimal drilling performance considering the recommendations of the pVARD’s spring compression tests and stress-strain analysis of rock samples conducted prior to drilling experiments, analyzing the cutting size distribution, and evaluating the applied drilling parameters as a function of WOB. These results are compared with those obtained from drilling without pVARD, which represents the typical rigid BHA of the conventional drilling.

Keywords: BHA, drilling performance, MSE, pVARD, rate of penetration, ROP, tensile and shear fractures, unconfined compressive strength

Procedia PDF Downloads 133

Authors: Ahmed Mostafa, Mohamed Mahmoud, Nesreen H. Hafez, Mohamed Fahim

Abstract:

This retrospective study includes 60 patients with pre-invasive breast cancer. Aim of the study: Evaluation of premalignant lesions of the breast (DCIS), different treatment methods and outcome. Patients and methods: 60 patients with DCIS were studied from the period between 2005 to 2012, for 38 patients the primary surgical method was wide local resection (WLE) (63.3%) and the other cases (22 patients, 36.7%) had mastectomy, fourteen cases from those who underwent local excision received radiotherapy, while no adjuvant radiotherapy was given for those who underwent mastectomy. In case of hormonal receptor positive DCIS lesions hormonal treatment (Tamoxifen) was given after local control. Results: No difference in overall survival between mastectomy & breast conserving therapy (wide local excision and adjuvant radiotherapy), however local recurrence rate is higher in case of breast conserving therapy, also no role of Axillary evacuation in case of DCIS. The use of hormonal therapy decreases the incidence of local recurrence by about 98%. Conclusion: The main management of DCIS is local treatment (wide local excision and radiotherapy) with hormonal treatment in case of hormone receptor positive lesions.

Keywords: ductal carcinoma in situ, surgical treatment, radiotherapy, breast conserving therapy, hormonal treatment

Procedia PDF Downloads 307