Search results for: flight test data

Authors: Tigabu Dagne Akal

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Electronic health records (EHRs) can help to store, maintain, and make the appropriate handling of patient histories for proper treatment and decision. Merging the EHRs with big data analytics (BDA) capabilities enable healthcare stakeholders to provide effective and efficient treatments for chronic diseases. Though there are huge opportunities and efforts that exist in the deployment of EMRs and the development of BDA, there are challenges in addressing resources and organizational capabilities that are required to achieve the competitive advantage and sustainability of EHRs and BDA. The resource-based view (RBV), information system (IS), and non- IS theories should be extended to examine organizational capabilities and resources which are required for successful data analytics in the healthcare industries. The main purpose of this study is to develop a conceptual framework for the development of healthcare BDA capabilities based on past works so that researchers can extend. The research question was formulated for the search strategy as a research methodology. The study selection was made at the end. Based on the study selection, the conceptual framework for the development of BDA capabilities in the healthcare settings was formulated.

Keywords: EHR, EMR, Big data, Big data analytics, resource-based view

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Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

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Every year, fog formation over the Indo-Gangetic Plains (IGPs) of Indian region during the winter months of December and January is believed to create numerous hazards, inconvenience, and economic loss to the inhabitants of this densely populated region of Indian subcontinent. The aim of the paper is to analyze the spatial and temporal variability of winter fog over IGPs. Long term ground observations of visibility and other meteorological parameters (1971-2010) have been analyzed to understand the formation of fog phenomena and its relevance during the peak winter months of January and December over IGP of India. In order to examine the temporal variability, time series and trend analysis were carried out by using the Mann-Kendall Statistical test. Trend analysis performed by using the Mann-Kendall test, accepts the alternate hypothesis with 95% confidence level indicating that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, the Theil and Sen’s median slope estimate showed that the magnitude of trend is positive. Magnitude is higher during January compared to December for the entire IGP except in December when it is high over the western IGP. Decade wise time series analysis revealed that there has been continuous increase in fog days. The net overall increase of 99 % was observed over IGP in last four decades. Diurnal variability and average daily persistence were computed by using descriptive statistical techniques. Geo-statistical analysis of fog was carried out to understand the spatial variability of fog. Geo-statistical analysis of fog revealed that IGP is a high fog prone zone with fog occurrence frequency of more than 66% days during the study period. Diurnal variability indicates the peak occurrence of fog is between 06:00 and 10:00 local time and average daily fog persistence extends to 5 to 7 hours during the peak winter season. The results would offer a new perspective to take proactive measures in reducing the irreparable damage that could be caused due to changing trends of fog.

Keywords: fog, climatology, Mann-Kendall test, trend analysis, spatial variability, temporal variability, visibility

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Authors: Taruna Katyal Arora, Geeta Kumari, Hari Shankar, Neelima Mishra

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Substandard and counterfeit antimalarials is a major problem in malaria endemic areas. The availability of counterfeit/ substandard medicines is not only decreasing the efficacy in patients, but it is also one of the contributing factors for developing antimalarial drug resistance. Owing to this, a pilot study was conducted to survey quality of drugs collected from different malaria endemic areas of India. Artesunate+Sulphadoxine-Pyrimethamine (AS+SP), Artemether-Lumefantrine (AL), Chloroquine (CQ) tablets were randomly picked from public health facilities in selected states of India. The quality of antimalarial drugs from these areas was assessed by using Global Pharma Health Fund Minilab test kit. This includes physical/visual inspection and disintegration test. Thin-layer chromatography (TLC) was carried out for semi-quantitative assessment of active pharmaceutical ingredients. A total of 45 brands, out of which 21 were for CQ, 14 for AL and 10 for AS+SP were tested from Uttar Pradesh (U.P.), Mizoram, Meghalaya and Gujrat states. One out of 45 samples showed variable disintegration and retension factor. The variable disintegration and retention factor which would have been due to substandard quality or other factors including storage. However, HPLC analysis confirms standard active pharmaceutical ingredient, but may be due to humid temperature and moisture in storage may account for the observed result.

Keywords: antimalarial medicines, counterfeit, substandard, TLC

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Authors: Abrar Almutairi, Alyaa Farouk, Amal Gouda

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Background: Social capital is a factor that helps in bonding in a social network. The individual and the neighborhood social capital affect the health status of members of a particular society. In addition, to the influence of social health on the health of the population, social health has a significant effect on women, especially those with pregnancy. Study objective was to assess the impact of the social capital on the health status of pregnant women Design: A descriptive crosssectional correlational design was utilized in this study. Methods: A convenient sample of 210 pregnant women who attended the outpatient antenatal clinicsfor follow-up in King Fahad hospital (Ministry of National Guard Health Affairs/Riyadh) and King Abdullah bin Abdelaziz University Hospital (KAAUH, Ministry of Education /Riyadh) were included in the study. Data was collected using a self-administered questionnaire that was developed by the researchers based on the “World Bank Social Capital Assessment Tool” and SF-36 questionnaire (Short Form Health Survey). The questionnaire consists of 4 parts to collect information regarding socio-demographic data, obstetric and gynecological history, general scale of health status and social activity during pregnancy and the social capital of the study participants, with different types of questions such as multiple-choice questions, polar questions, and Likert scales. Data analysis was carried out by using Statistical Package for the Social Sciences version 23. Descriptive statistic as frequency, percentage, mean, and standard deviation was used to describe the sample characteristics, and the simple linear regression test was used to assess the relationship between the different variables, with level of significance P≤0.005. Result: This study revealed that only 31.1% of the study participants perceived that they have good general health status. About two thirds (62.8%) of the participants have moderate social capital, more than one ten (11.2٪) have high social capital and more than a quarter (26%) of them have low social capital. All dimensions of social capital except for empowerment and political action had positive significant correlations with the health status of pregnant women with P value ranging from 0.001 to 0.010in all dimensions. In general, the social capital showed high statistically significant association with the health status of the pregnant (P=0.002). Conclusion: Less than one third of the study participants had good perceived health status, and the majority of the study participants have moderate social capital, with only about one ten of them perceived that they have high social capital. Finally, neighborhood residency area, family size, sufficiency of income, past medical and surgical history and parity of the study participants were all significantly impacting the assessed health domains of the pregnant women.

Keywords: impact, social capital, health status, pregnant women

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

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The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: corporate reputation, fuzzy logic, fuzzy model, stock market investors

Procedia PDF Downloads 241

Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

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Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

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Authors: Hacer Kobya Bulut, Kıymet Yeşilçiçek Çalık, Birsel Canan Demirbağ, Hacer Erdöl, Songül Aktaş

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Introduction: As an expression of an emotion which always exists in life, crying is regarded as one of the problematic behaviors of patients by nurses. Towards such patients, nurses may exhibit emotional and behavioral reactions such as feeling helpless, anger, indifferent, defense, and opposition. However crying either meets a need, reduces the tension to cope with problems or helps patient to gain strength. Therefore, nurses must accept that crying is a normal mechanism that reduces emotional tension and should approach a crying patient accordingly. Objective: This study was carried out to evaluate the communicational behaviors of the nurses towards ‘crying patient’. Methods: This descriptive study was conducted with the nurses working at a university hospital in a city in the Eastern Black Sea in June-September 2015. The entire universe was tried to be reached without sampling. 90% of the population was reached and the study was completed with 309 nurses who volunteered to participate in the study. Data were collected through a questionnaire which was prepared reviewing the literature by researchers. Data were evaluated in SPSS analysis program using percentages, numbers and chi-square test with the 95% confidence interval and p <0.05significance level. Findings: The findings showed that the average age of nurses was 31.52 ± 7.96, work experience was 10:09 ± 7.69 and only 22.7% had training about ‘approach to crying patient’ during their education. 97.1% of the nurses often faced with crying patients in their professional lives, 62.8% stated that they faced crying women patients. When they see crying patients, 84.8% of the nurses ‘do not want the patient to cry’, 80.9% wonder ‘why they are crying’, % 79.6 ‘feel uneasiness’,% 79.3 ‘feel sorry’ and 41.4% ‘ feel helpless’. The question ‘Why do you think the patient is crying?’ was answered by 93.5% nurses as ‘they are suffering’, by 86.1% ‘they are helpless’, 80.9% ‘they are sad’, 79.6% ‘they need help’, 54.4% ‘because they feel inadequate,’ and 44.7% ‘they fail to control their crying behavior. ‘How do you approach to your patient when she/he is crying?’ question was answered by 82.5% of nurses as ‘I would console’, 77.3% as ‘I would ask the reason’, 63.1% as ‘I would try to stop her from crying’ all of which are actually inappropriate nursing approaches. However, 92.2% of the nurses stated that ‘I do not judge the crying patient’, ‘87.1% said ‘I allocate time to crying patients’ and 85.8% said ‘ I ask patient whether they want to cry alone’. The study showed that educational background and work experience of the nurses affected the appropriate approach to crying patients (P <0.05). Conclusion: As a result of the study, it was found out that nurses do not want patients to cry, so they exhibit inappropriate approach such as consoling the patients and they have difficulty in approaching crying patients.

Keywords: approach to patient, communication, crying patient, nurse, Turkey

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Authors: Devyani Shete, Sudeep Rai

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Background: The COVID-19 pandemic has caused one of the highest disruptions to the NHS (National Health Service), especially to the fundamental cervical cancer screening service. To prioritize screening response effectively, it is vital to understand the underlying disease risks amongst groups of women who are less likely to resume their screening/follow up at General Practices. The current government target is to have>=80% of women have an adequate test within the previous 3.5 years (ages 25-49) or 5.5 years (ages 50-64). Aims/Objectives: To increase the number of eligible people aged 25-49 attending cervical screening by 5% at Lakeside Healthcare (a General Practice in Corby). Methods: An online survey was posted on the Lakeside Healthcare website to find out what the barriers towards cervical screening were. It was apparent that patients needed more information catered to their responses. 6 informational videos and a “Cervical Screening Guide” were created for Lakeside patients about cervical screening, which were posted on the Healthcare website. Lakeside also started sending reminder texts to those eligible, with a link to a booking form. Results: On 18th January 2022, 69.7% of patients aged 25-49 years (7207) had an adequate cervical screening test in the last 3.5 years. There were 80 total responders to the online survey. In response to “which of the following are reasons why you have not attended screening”, 30% ticked “I kept putting it off/did not get around to it,” and 13% ticked “I was worried it would be painful or daunting.” In response to “which of the following would make you more likely to book an appointment”, 23% ticked “More detailed explanations of what the risks are if I don’t have screening,” and 20% ticked “I would like more information about the test and what the smear entails.” 10% of responders had previous trauma, whilst 28% of responders said the pandemic had impacted them getting a smear. Survey results were used to carry out interventions to increase smear uptake. On 23rdMarch 2022 (after a 2-month period), 75%of patients aged 25-49 (7119) attended the screening, which was a 5.3% increase from January. Discussion/Conclusion: The survey was vital in carrying out the exact interventions that were required for patients to increase screening uptake, as it is important to know what the populations’ needs are in order to create personalized invitations. This helps to optimise response during a pandemic. A HPV self-sample kit at home could be a popular method of dealing with further outbreaks.

Keywords: gynaecology, cervical screening, public health, COVID-19

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Authors: Le-Quyen Nguyen, Hoang Van Bui, Ngoc Thi Tran, Binh Thanh Le, Linus Olson, Thanh Quang Le

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Objective: We compared of outcomes between infected and non-infected COVID-19 pregnant at the largest obstetrics and gynecology hospital in southern Vietnam. Materials and Methods: A retrospective study was conducted at gestational age (GA) 28-42 weeks, who terminated pregnancy and had a real-time PCR test for SARS-CoV-2 at Tu Du Hospital. Demographic, clinical, laboratory, and epidemiological data were collected from hospital electronic-medical-records. Diagnosis and screening of SARS-CoV-2 used Real-time-PCR. Results: From July to October 2021, 9,246 pregnant with GA of 28-42 weeks were delivered, including 664 infected with COVID-19 and 8,582 non-infected. The cesarean section (CS) rates of pregnant with and without COVID-19 were 47.3% and 46.0%. At GA 32-34 weeks, the rate of CS with COVID-19 was 5.07 times higher than without. The rate of postpartum hemorrhage (PPH) and the Apgar score between these two groups were similar. The mortality rate of infected pregnants was 2.26%. Conclusions: COVID-19 infection increased the CS rate in the group of preterm pregnancies from 32 to less than 34 weeks. COVID-19 did not increase the risk of complications related to adverse pregnancy outcomes such as PPH, Apgar scores, the ratio of stillbirths, deaths due to malformation, and fetal deaths in labor.

Keywords: COVID-19, SARS-CoV-2, pregnancy, outcome, vietnam

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Authors: H. Aksas, S. Boughrara, K. Louhab

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The goal of this study was the use of life cycle assessment (LCA) methodology to assess the environmental impact of pharmaceutical product (four kinds of syrup form and tree kinds of pomade form), which are produced in one leader manufactory in Algeria town that is SAIDAL Company. The impacts generated have evaluated using SimpaPro7.1 with CML92 Method for syrup form and EPD 2007 for pomade form. All impacts evaluated have compared between them, with determination of the compound contributing to each impacts in each case. Data needed to conduct Life Cycle Inventory (LCI) came from this factory, by the collection of theoretical data near the responsible technicians and engineers of the company, the practical data are resulting from the assay of pharmaceutical liquid, obtained at the laboratories of the university. This data represent different raw material imported from European and Asian country necessarily to formulate the drug. Energy used is coming from Algerian resource for the input. Outputs are the result of effluent analysis of this factory with different form (liquid, solid and gas form). All this data (input and output) represent the ecobalance.

Keywords: pharmaceutical product, drug residues, LCA methodology, environmental impacts

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Authors: Rajeev Kumar Bedi, Jaswinder Singh, Sunil Kumar Gupta

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Cloud storage is a model of online data storage where data is stored in virtualized pool of servers hosted by third parties (CSPs) and located in different geographical locations. Cloud storage revolutionized the way how users access their data online anywhere, anytime and using any device as a tablet, mobile, laptop, etc. A lot of issues as vendor lock-in, frequent service outage, data loss and performance related issues exist in single cloud storage systems. So to evade these issues, the concept of multi cloud storage introduced. There are a lot of multi cloud storage systems exists in the market for mobile devices. In this article, we are providing comparison of four multi cloud storage systems for mobile devices Otixo, Unclouded, Cloud Fuze, and Clouds and evaluate their performance on the basis of CPU usage, battery consumption, time consumption and data usage parameters on three mobile phones Nexus 5, Moto G and Nexus 7 tablet and using Wi-Fi network. Finally, open research challenges and future scope are discussed.

Keywords: cloud storage, multi cloud storage, vendor lock-in, mobile devices, mobile cloud computing

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Authors: M. Zayoud, S. Oueida, S. Ionescu, P. AbiChar

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Background: Wireless sensor network is encompassed of diversified tools of information technology, which is widely applied in a range of domains, including military surveillance, weather forecasting, and earthquake forecasting. Strengthened grounds are always developed for wireless sensor networks, which usually emerges security issues during professional application. Thus, essential technological tools are necessary to be assessed for secure aggregation of data. Moreover, such practices have to be incorporated in the healthcare practices that shall be serving in the best of the mutual interest Objective: Aggregation of encrypted data has been assessed through homomorphic stream cipher to assure its effectiveness along with providing the optimum solutions to the field of healthcare. Methods: An experimental design has been incorporated, which utilized newly developed cipher along with CPU-constrained devices. Modular additions have also been employed to evaluate the nature of aggregated data. The processes of homomorphic stream cipher have been highlighted through different sensors and modular additions. Results: Homomorphic stream cipher has been recognized as simple and secure process, which has allowed efficient aggregation of encrypted data. In addition, the application has led its way to the improvisation of the healthcare practices. Statistical values can be easily computed through the aggregation on the basis of selected cipher. Sensed data in accordance with variance, mean, and standard deviation has also been computed through the selected tool. Conclusion: It can be concluded that homomorphic stream cipher can be an ideal tool for appropriate aggregation of data. Alongside, it shall also provide the best solutions to the healthcare sector.

Keywords: aggregation, cipher, homomorphic stream, encryption

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Authors: Nirere Martine

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Purpose –The purpose of this study aims to understand the intention of customers to adopt sustainable packaging and the impact of sustainable packaging on customers’ willingness to buy a product using sustainable packaging. Design/methodology/approach – A new research model based on the technology acceptance model (TAM) and structural equation modeling are used to examine causality and test relationship based on the data collected from 251 Rwanda samples. Findings – The findings indicated that perceived ease of use positively affects perceived usefulness. However, perceived usefulness and perceived ease of use positively affect the intention to adopt sustainable packaging. However, perceived risk and perceived cost negatively affect the intention to adopt sustainable packaging. The intention to adopt sustainable packaging positively affects the willingness to buy a product using sustainable packaging. Originality/value – Many researchers have investigated the issue of a consumers’ behavior to purchase a product. In particular, they have examined whether customers are willing to pay extra for a packaging product. There has been no study that has examined the impact of sustainable packaging on customers’ willingness to buy. The results of this study can help manufacturers form a better understanding of customers’ willingness to purchase a product using sustainable packaging.

Keywords: consumers’ behavioral, sustainable packaging, TAM, Rwanda

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Authors: Omar Al Ali

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The current study was aimed to explore the relationships between emotional intelligence, cognitive ability, and leader's performance. Data were collected from 260 senior managers from UAE. The results showed that there are significant relationships between emotional intelligence and leadership performance as measured by the annual internal evaluations of each participant (r = .42, p < .01). Data from regression analysis revealed that both variables namely emotional intelligence (beta = .31, p < .01), and cognitive ability (beta = .29, p < .01), predicted leadership competencies, and together explained 26% of its variance. Data suggests that EI and cognitive ability are significantly correlated with leadership performance. In depth implications of the present findings for human resource development theory and practice are discussed.

Keywords: emotional intelligence, cognitive ability, leadership, performance

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Authors: M. Shahin Alam, Satoru Takahashi, Mariko Itoh, Miyuki Komura, Mayuko Suzuki, Natthanan Sangsriratanakul, Kazuaki Takehara

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Cleaning and disinfection are key components of routine biosecurity in livestock farming and food processing industry. The usage of suitable disinfectants and their proper concentration are important factors for a successful biosecurity program. Disinfectants have optimum bactericidal and virucidal efficacies at temperatures above 20°C, but very few studies on application and effectiveness of disinfectants at low temperatures have been done. In the present study, the bactericidal efficacies of food additive grade calcium hydroxide (FdCa(OH)), quaternary ammonium compound (QAC) and their mixture, were investigated under different conditions, including time, organic materials (fetal bovine serum: FBS) and temperature, either in suspension or in carrier test. Salmonella Infantis and Escherichia coli, which are the most prevalent gram negative bacteria in commercial poultry housing and food processing industry, were used in this study. Initially, we evaluated these disinfectants at two different temperatures (4°C and room temperature (RT) (25°C ± 2°C)) and 7 contact times (0, 5 and 30 sec, 1, 3, 20 and 30 min), with suspension tests either in the presence or absence of 5% FBS. Secondly, we investigated the bactericidal efficacies of these disinfectants by carrier tests (rubber, stainless steel and plastic) at same temperatures and 4 contact times (30 sec, 1, 3, and 5 min). Then, we compared the bactericidal efficacies of each disinfectant within their mixtures, as follows. When QAC was diluted with redistilled water (dW2) at 1: 500 (QACx500) to obtain the final concentration of didecyl-dimethylammonium chloride (DDAC) of 200 ppm, it could inactivate Salmonella Infantis within 5 sec at RT either with or without 5% FBS in suspension test; however, at 4°C it required 30 min in presence of 5% FBS. FdCa(OH)2 solution alone could inactivate bacteria within 1 min both at RT and 4°C even with 5% FBS. While FdCa(OH)2 powder was added at final concentration 0.2% to QACx500 (Mix500), the mixture could inactivate bacteria within 30 sec and 5 sec, respectively, with or without 5% FBS at 4°C. The findings from the suspension test indicated that low temperature inhibited the bactericidal efficacy of QAC, whereas Mix500 was effective, regardless of short contact time and low temperature, even with 5% FBS. In the carrier test, single disinfectant required bit more time to inactivate bacteria on rubber and plastic surfaces than on stainless steel. However, Mix500 could inactivate S. Infantis on rubber, stainless steel and plastic surfaces within 30 sec and 1 min, respectively, at RT and 4°C; but, for E. coli, it required only 30 sec at both temperatures. So, synergistic effects were observed on different carriers at both temperatures. For a successful enhancement of biosecurity during winter, the disinfectants should be selected that could have short contact times with optimum efficacy against the target pathogen. The present study findings help farmers to make proper strategies for application of disinfectants in their livestock farming and food processing industry.

Keywords: carrier, food additive grade calcium hydroxide (FdCa(OH)₂), quaternary ammonium compound, synergistic effects

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Authors: Tisciane Perpetuo e Oliveira, Dante Inga Narvaez, Marcelo Gradella Villalva

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Installations of solar photovoltaic systems have increased considerably in the last decade. Therefore, it has been noticed that monitoring of meteorological data (solar irradiance, air temperature, wind velocity, etc.) is important to predict the potential of a given geographical area in solar energy production. In this sense, the present work compares two computational tools that are capable of estimating the energy generation of a photovoltaic system through correlation analyzes of solar radiation data: PVsyst software and an algorithm based on the PVlib package implemented in MATLAB. In order to achieve the objective, it was necessary to obtain solar radiation data (measured and from a solarimetric database), analyze the decomposition of global solar irradiance in direct normal and horizontal diffuse components, as well as analyze the modeling of the devices of a photovoltaic system (solar modules and inverters) for energy production calculations. Simulated results were compared with experimental data in order to evaluate the performance of the studied methods. Errors in estimation of energy production were less than 30% for the MATLAB algorithm and less than 20% for the PVsyst software.

Keywords: energy production, meteorological data, irradiance decomposition, solar photovoltaic system

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: Joshua W. Edefo, Shafiul Azam, Murray D. Smith

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Introduction: In April 2022, the Welsh Government introduced the six goals for urgent and emergency care programs. One of these goals was to provide access to clinically safe alternatives, leading to the establishment of the Same Day Emergency Care (SDEC) program. The SDEC initiative aims to offer viable options that maintain patient safety while avoiding unnecessary hospital stays. The aim of the study is to determine the duration of patient stay in SDEC and compare it with that of Emergency department (ED) stay to ascertain if one of the objectives of SDEC is achieved. Methods: Patient stays and attendance datasets were constructed from Withybush SDEC and ED patient records. These records were provided by Hywel Dda University Health Board Informatics. Some hypothetical pathways were identified, notably SDEC visits involving a single attendance and ED visits then immediately transferred to SDEC. Descriptive statistics were used to summarise the data, and hypothesis tests for mean differences used the student t-test. Propensity scoring was employed to match a set of ED patient stays to SDEC patient stays which were then used to determine the average treatment effect (ATE) to compare durations of stay in SDEC with ED. Regression methods were used to model the natural logarithm of the duration of SDEC attendance, and the level of statistical significance was set to 0.05. Results: SDEC visits involving a single attendance (170 of 384; 44.3%) is the most frequently observed pathway with patient length of stay at 256 minutes (95%CI 237.4 - 275.1). The next most frequently observed pathway of patient stay was SDEC attendance after presenting to ED (80 of 384; 20.8%) and gave the length of stay of 440 minutes (95%CI 351.6 - 529.2). Time spent in this pathway significantly increased by 184 minutes (95%CI 118.0 - 250.2, support for no difference p<0.001) compared to the most seen pathway. When SDEC data were compared with ED, the estimate for the ATE from SDEC single attendance was -272 minutes (95%CI -334.1 - -210.5; p<0.001), while that of ED then SDEC pathway was -50.6 min (95%CI -182.7-81.5; p=0.453). Conclusion: When patients are admitted to SDEC and successfully discharged, their stays are significantly shorter, approximately 4.5 hours, compared to patients who spend their entire stay in the Emergency Department. That difference vanishes when the patient stay includes a period spent previously in ED before transfer to SDEC.

Keywords: attendance, emergency-department, patient-stay, same-day-emergency-care

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Authors: Sara Canas Pedrosa, Esther Moraleda SepuLveda

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Angelman Syndrome (AS) and Prader-Willi Syndrome (PWS) are considered rare genetic disorders that share the same chromosomal region: 15q11.2-q13. This is why both share some common characteristics, such as, delay in language development. However, there is still little research that specifically focuses on the linguistic profile in these populations. Therefore, the objective of this study was to know the characteristics of oral and written language that Angelman Syndrome and Prader-Willi Syndrome present from the point of view of parents. The sample consisted of 36 families (with children between 6 and 17 years old), of which 23 had children with AS and 13 had children with PWS. All of them answered the Language Assessment Scale of the standardized test CELF-4, Spanish Clinical Evaluation of Language Fundamentals-4 (Wiig, Secord & Semel, 2006). The scale is made up of 40 items that assesses the perception of parents in areas such as: difficulty of listening, speaking, reading and writing. The results indicate that the majority of parents manifest problems in almost all the sub-areas related to oral language and written language, taking into account that many do not achieve a literacy level, with similar results in comparison with both syndromes. These data support the importance of working on oral language delay and its relationship with the subsequent learning of literacy throughout its development.

Keywords: Angelman Syndrome , development, language, Prader-Willi Syndrome

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Authors: Shaan Khosla, Jon Krohn

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In a recruiting context, machine learning models are valuable for recommendations: to predict the best candidates for a vacancy, to match the best vacancies for a candidate, and compile a set of similar candidates for any given candidate. While useful to create these models, validating their accuracy in a recommendation context is difficult due to a sparsity of data. In this report, we use network graph data to generate useful representations for candidates and vacancies. We use candidates and vacancies as network nodes and designate a bi-directional link between them based on the candidate interviewing for the vacancy. After using node2vec, the embeddings are used to construct a validation dataset with a ranked order, which will help validate new recommender systems.

Keywords: AI, machine learning, NLP, recruiting

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Authors: S. Sharma, U. Batra, S. Kapoor, A. Dua

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In this study, the effects and interactions of reaction time and capping agent assistance during sol-gel synthesis of magnesium substituted hydroxyapatite nanopowder (MgHA) on hydroxyapatite (HA) to β-tricalcium phosphate (β-TCP) ratio, Ca/P ratio and mean crystallite size was examined experimentally as well as through statistical analysis. MgHA nanopowders were synthesized by sol-gel technique at room temperature using aqueous solution of calcium nitrate tetrahydrate, magnesium nitrate hexahydrate and potassium dihydrogen phosphate as starting materials. The reaction time for sol-gel synthesis was varied between 15 to 60 minutes. Two process routes were followed with and without addition of triethanolamine (TEA) in the solutions. The elemental compositions of as-synthesized powders were determined using X-ray fluorescence (XRF) spectroscopy. The functional groups present in the as-synthesized MgHA nanopowders were established through Fourier Transform Infrared Spectroscopy (FTIR). The amounts of phases present, Ca/P ratio and mean crystallite sizes of MgHA nanopowders were determined using X-ray diffraction (XRD). The HA content in biphasic mixture of HA and β-TCP and Ca/P ratio in as-synthesized MgHA nanopowders increased effectively with reaction time of sols (p < 0.0001, two way Anova), however, these were independent of TEA addition (p > 0.15, two way Anova). The MgHA nanopowders synthesized with TEA assistance exhibited 14 nm lower crystallite size (p < 0.018, 2 sample t-test) compared to the powder synthesized without TEA assistance.

Keywords: capping agent, hydroxyapatite, regression analysis, sol-gel, 2- sample t-test, two-way analysis of variance (ANOVA)

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Authors: Jihene Bettaieb, Ghassen kharroubi, Rym mallekh, Ines Cherif, Taoufik Atawa, Kaouther Harrabech

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Brucellosis is a major worldwide zoonosis. It is a reportable condition in Tunisia where the disease remains endemic, especially in rural areas. The aim of this study was to describe the epidemiological, clinical, and bacteriological profile of human brucellosis cases notified in the district of Tunis. It was a retrospective descriptive study of cases reported in the district of Tunis through the national surveillance system between the 1st January and 31th December 2017. During the study period, 133 brucellosis confirmed cases were notified. The mean age was 37.5 ± 18.0 years, and 54.9% of cases were males. More than four-fifths (82.7%) of cases were reported in spring and summer with a peak in the month of May (36 cases). Fever and sweats were the most common symptoms; they occurred in 95% and 72% of cases, respectively. Osteoarticular complications occurred in 10 cases, meningitis in one case and endocarditis in one other case. Wright agglutination test and Rose Bengale test were positive in 100% and 91% of cases, respectively. While blood culture was positive in 9 cases and PCR in 2 cases. Brucella melitensis was the only identified specie (9 cases). Almost all cases (99.2%) reported the habit of consuming raw dairy products. Only 5 cases had a suspect contact with animals; among them, 3 persons were livestock breeders. The transmission was essentially due to raw dairy product consumption. It is important to enhance preventive measures to control animal Brucellosis and to educate the population regarding the risk factors of the disease.

Keywords: brucellosis, risk factors, surveillance system, Tunisia

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Authors: Felermino D. M. A. Ali, S. C. Ng

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E-learning is an evolutionary form of distance learning and has become better over time as new technologies emerged. Today, efforts are still being made to embrace E-learning systems with emerging technologies in order to make them better. Among these advancements, Educational Data Mining (EDM) is one that is gaining a huge and increasing popularity due to its wide application for improving the teaching-learning process in online practices. However, even though EDM promises to bring many benefits to educational industry in general and E-learning environments in particular, its principal drawback is the lack of easy to use tools. The current EDM tools usually require users to have some additional technical expertise to effectively perform EDM tasks. Thus, in response to these limitations, this study intends to design and implement an EDM application framework which aims at automating and simplify the development of EDM in E-learning environment. The application framework introduces a Service-Oriented Architecture (SOA) that hides the complexity of technical details and enables users to perform EDM in an automated fashion. The framework was designed based on abstraction, extensibility, and interoperability principles. The framework implementation was made up of three major modules. The first module provides an abstraction for data gathering, which was done by extending Moodle LMS (Learning Management System) source code. The second module provides data mining methods and techniques as services; it was done by converting Weka API into a set of Web services. The third module acts as an intermediary between the first two modules, it contains a user-friendly interface that allows dynamically locating data provider services, and running knowledge discovery tasks on data mining services. An experiment was conducted to evaluate the overhead of the proposed framework through a combination of simulation and implementation. The experiments have shown that the overhead introduced by the SOA mechanism is relatively small, therefore, it has been concluded that a service-oriented architecture can be effectively used to facilitate educational data mining in E-learning environments.

Keywords: educational data mining, e-learning, distributed data mining, moodle, service-oriented architecture, Weka

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Authors: Vikram Singh, Parmod Kumar Sethi

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The objective of the study was to study the effectiveness of common yoga protocol on reaction time (choice visual reaction time, measured in milliseconds/seconds) of male football players in the age group of 16 to 21 years. The 40 boys were measured initially on parameters of years of experience, level of participation. They were randomly assigned into two groups i.e. control and experimental. CVRT for both the groups was measured on day-1 and post intervention (common yoga protocol here) was measured after 45 days of training to the experimental group after they had finished with their regular fitness and soccer skill training. One way ANOVA (Univariate analysis) and Independent t-test using SPSS 23 statistical package were applied to get and analyze the results. The experimental yoga protocol group showed a significant reduction in CVRT, whereas the insignificant difference in reaction times was observed for control group after 45 days. The effect size was more than 52% for CVRT indicating that the effect of treatment was large. Power of the study was also found to be high (> .80). There was a significant difference after 45 days of yoga protocol in choice visual reaction time of experimental group (p = .000), t (21.93) = 6.410, p = .000 (two-tailed). The null hypothesis (that there would be no difference in reaction times of control and experimental groups) was rejected. Where p< .05. Therefore alternate hypothesis was accepted.

Keywords: reaction time, yoga protocol, t-test, soccer players

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Authors: Bimrisha Mali

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The present study investigates the type of errors English as a second language (ESL) learners produce using the definite article ‘the’. The participants were provided a questionnaire on the learner's ability test. The questionnaire consists of three cloze tests and two free composition tests. Each participant's response was received in the form of written data. A total of 78 participants from three government schools participated in the study. The participants are high-school students from Rural Assam. Assam is a north-eastern state of India. Their age ranged between 14-15. The medium of instruction and the communication among the students take place in the local language, i.e., Assamese. Pit Corder’s steps for conducting error analysis have been followed for the analysis procedure. Four types of errors were found (1) deletion of the definite article, (2) use of the definite article as modifiers as adjectives, (3) incorrect use of the definite article with singular proper nouns, (4) substitution of the definite article by the indefinite article ‘a’. Classifiers in Assamese that express definiteness is used with nouns, adjectives, and numerals. It is found that native language (L1) transfer plays a pivotal role in the learners’ errors. The analysis reveals the learners' inability to acquire the semantic connotation of definiteness in English due to native language (L1) interference.

Keywords: definite article error, l1 transfer, error analysis, ESL

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Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Gadinga Walter Forje, Martin Ngankam Tchamba, Nyong Princely Awazi, Barnabas Neba Nfornka

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Ecotourism is viewed as a double edge sword for the enhancement of conservation and local livelihood within a protected landscape. The Campo Ma’an National Park (CMNP) adopted ecotourism in its management plan as a strategic axis for better management of the park. The growing importance of ecotourism as a strategy for the sustainable management of CMNP and its environs requires adequate information to bolster the sector. This study was carried out between November 2018 and September 2021, with the main objective to contribute to the sustainable management of the CMNP through suggestions for enhancing the capacity of ecotourism in and around the park. More specifically, the study aimed at; 1) Analyse the governance of ecotourism in the CMNP and its surrounding; 2) Assessing the impact of ecotourism on local livelihood around the CMNP; 3) Evaluating the contribution of ecotourism to biodiversity conservation in and around the CMNP; 4) Evaluate the determinants of ecotourism possibilities in achieving sustainable livelihood and biodiversity conservation in and around the CMNP. Data were collected from both primary and secondary sources. Primary data were obtained from household surveys (N=124), focus group discussions (N=8), and key informant interviews (N=16). Data collected were coded and imputed into SPSS (version 19.0) software and Microsoft Excel spreadsheet for both quantitative and qualitative analysis. Findings from the Chi-square test revealed overall poor ecotourism governance in and around the CMNP, with benefit sharing (X2 = 122.774, p <0.01) and conflict management (X2 = 90.839, p<0.01) viewed to be very poor. For the majority of the local population sampled, 65% think ecotourism does not contribute to local livelihood around CMNP. The main factors influencing the impact of ecotourism around the CMNP on the local population’s livelihood were gender (logistic regression (β) = 1.218; p = 0.000); and level of education (logistic regression (β) = 0.442; p = 0.000). Furthermore, 55.6% of the local population investigated believed ecotourism activities do not contribute to the biodiversity conservation of CMNP. Spearman correlation between socio-economic variables and ecotourism impact on biodiversity conservation indicated relationships with gender (r = 0.200, p = 0.032), main occupation (r = 0.300 p = 0.012), time spent in the community (r = 0.287 p = 0.017), and number of children (r =-0.286 p = 0.018). Variables affecting ecotourism impact on biodiversity conservation were age (logistic regression (β) = -0.683; p = 0.037) and gender (logistic regression (β) = 0.917; p = 0.045). This study recommends the development of ecotourism-friendly policies that can accelerate Public Private Partnership for the sustainable management of the CMNP as a commitment toward good governance. It also recommends the development of gender-sensitive ecotourism packages, with fair opportunities for rural women and more parity in benefit sharing to improve livelihood and contribute more to biodiversity conservation in and around the Park.

Keywords: biodiversity conservation, Campo Ma’an national park, ecotourism, ecotourism governance, rural livelihoods, protected area management

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Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

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Authors: Hamid Rostami, Ali Fallah Yeznabad, Mohammad H. Baziar

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The energy-based method for evaluating seismic soil liquefaction has two main sections. First is the demand energy, which is dissipated energy of earthquake at a site, and second is the capacity energy as a representation of soil resistance against liquefaction hazard. In this study, using a statistical analysis of recorded data by 14 down-hole array sites in California, an empirical equation was developed to estimate the demand energy at sites. Because determination of capacity energy at a site needs to calculate several site calibration factors, which are obtained by experimental tests, in this study the standard penetration test (SPT) N-value was assumed as an alternative to the capacity energy at a site. Based on this assumption, the empirical equation was employed to calculate the demand energy for 193 liquefied and no-liquefied sites and then these amounts were plotted versus the corresponding SPT numbers for all sites. Subsequently, a discrimination analysis was employed to determine the equations of several boundary curves for various liquefaction likelihoods. Finally, a comparison was made between the probabilistic model and the commonly used stress method. As a conclusion, the results clearly showed that energy-based method can be more reliable than conventional stress-based method in evaluation of liquefaction occurrence.

Keywords: energy demand, liquefaction, probabilistic analysis, SPT number

Procedia PDF Downloads 365