Search results for: common random number (CRN)

Authors: Azizul Baten, Kamrul Hossain, Abdullah-Al-Zabir

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The objective of this study is to develop an appropriate stochastic frontier secondary schools efficiency model by ICT Intervention and to examine the impact of ICT challenges on secondary schools efficiency in the Sylhet division in Bangladesh using stochastic frontier analysis. The Translog stochastic frontier model was found an appropriate than the Cobb-Douglas model in secondary schools efficiency by ICT Intervention. Based on the results of the Cobb-Douglas model, it is found that the coefficient of the number of teachers, the number of students, and teaching ability had a positive effect on increasing the level of efficiency. It indicated that these are related to technical efficiency. In the case of inefficiency effects for both Cobb-Douglas and Translog models, the coefficient of the ICT lab decreased secondary school inefficiency, but the online class in school was found to increase the level of inefficiency. The coefficients of teacher’s preference for ICT tools like multimedia projectors played a contributor role in decreasing the secondary school inefficiency in the Sylhet division of Bangladesh. The interaction effects of the number of teachers and the classrooms, and the number of students and the number of classrooms, the number of students and teaching ability, and the classrooms and teaching ability of the teachers were recorded with the positive values and these have a positive impact on increasing the secondary school efficiency. The overall mean efficiency of urban secondary schools was found at 84.66% for the Translog model, while it was 83.63% for the Cobb-Douglas model. The overall mean efficiency of rural secondary schools was found at 80.98% for the Translog model, while it was 81.24% for the Cobb-Douglas model. So, the urban secondary schools performed better than the rural secondary schools in the Sylhet division. It is observed from the results of the Tobit model that the teacher-student ratio had a positive influence on secondary school efficiency. The teaching experiences of those who have 1 to 5 years and 10 years above, MPO type school, conventional teaching method have had a negative and significant influence on secondary school efficiency. The estimated value of σ-square (0.0625) was different from Zero, indicating a good fit. The value of γ (0.9872) was recorded as positive and it can be interpreted as follows: 98.72 percent of random variation around in secondary school outcomes due to inefficiency.

Keywords: efficiency, secondary schools, ICT, stochastic frontier analysis

Procedia PDF Downloads 116

Authors: P. Efstathiou, E. Kouskouni, Z. Manolidou, K. Karageorgou, M. Tseroni, A. Efstathiou, V. Karyoti, I. Agrafa

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Aim: The aim of this prospective comparative study is to evaluate the reduction of microbial flora on the surface of an axillary digital thermometer, made of antimicrobial copper, in relation with a common digital thermometer. Material – Methods: A brand new digital electronic thermometer implemented with antimicrobial copper (Cu 70% - Nic 30%, low lead) on the two edges of the device (top and bottom: World Patent Number WO2013064847 and Register Number by the Hellenic Copper Development Institute No 11/2012) was manufactured and a comparative study with common digital electronic thermometer was conducted on 18 ICU (Intensive Care Unit) patients of three different hospitals. The thermometry was performed in accordance with the projected International Nursing Protocols for body temperature measurement. A total of 216 microbiological samples were taken from the axillary area of the patients, using both of the investigated body temperature devises. Simultaneously the “Halo” phenomenon (phenomenon “Stefanis”) was studied at the non-antimicrobial copper-implemented parts of the antimicrobial digital electronic thermometer. Results: In all samples collected from the surface of the antimicrobial electronic digital thermometer, the reduction of microbial flora (Klebsiella spp, Staphylococcus aureus, Staphylococcus epidermitis, Candida spp, Pneudomonas spp) was progressively reduced to 99% in two hours after the thermometry. The above flora was found in the axillary cavity remained the same in common thermometer. The statistical analysis (SPSS 21) showed a statistically significant reduction of the microbial load (N = 216, < 0.05). Conclusions: The hospital-acquired infections are linked to the transfer of pathogens due to the multi-usage of medical devices from both health professionals and patients, such as axillary thermometers. The use of antimicrobial digital electronic thermometer minimizes microbes' transportation between patients and health professionals while having all the conditions of reliability, proper functioning, security, ease of use and reduced cost.

Keywords: antimicrobial copper, cross infections, digital thermometers, ICU

Procedia PDF Downloads 375

Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

Procedia PDF Downloads 98

Authors: John Yahng, Hansraj Riteesh Bookun

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Popliteal artery aneurysms (PAAs) are the most common arterial aneurysm of the periphery. It is defined as focal dilation of the artery more than 50% of the normal vessel diameter which usually varies between 7 mm to 11 mm. The most common presentation for PAAs is claudication due to luminal stenosis secondary to mural thrombus or acute limb ischaemia due to occlusive thrombosis or distal thromboembolism. It is less common for patients to present with non-ischaemic symptoms secondary to mass effect and compression of adjacent structures, and of these, presentation with common peroneal nerve compression is particularly uncommon. We present a rare case of a 92-year-old female patient presenting with 4-month history of left foot drop with radiological evidence of common peroneal nerve compression secondary to PAA of 22 mm by 21mm in size. To the best of our knowledge, this is the smallest reported popliteal aneurysm presenting with foot drop. We also present the endovascular treatment option taken in our case.

Keywords: aneurysm, foot drop, peroneal nerve, popliteal

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Authors: Rama Debbarma

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The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

Procedia PDF Downloads 397

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Matěj Kuc

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This paper compares different types of profitability measures of cooperative banks from two developed regions: the European Union and the United States of America together with Canada. We created balanced dataset of more than 200 cooperative banks covering 2011-2016 period. We made series of tests and run Random Effects estimation on panel data. We found that American and Canadian cooperatives are more profitable in terms of return on assets (ROA) and return on equity (ROE). There is no significant difference in net interest margin (NIM). Our results show that the North American cooperative banks accommodated better to the current market environment.

Keywords: cooperative banking, panel data, profitability measures, random effects

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Authors: Supriadi Hardianto, Aditya Daniswara

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Today's workplace, flooded by millennial Generation or known also as Generation Y. A common problem that faced by the company towards Gen Y is a high turnover rate, attitudes problem, communication style, and different work style than the older generation. This is common in private sector. The objective of this study is to get a better understanding of the Gen Y Career Attitude at the workplace. The subject of this study is focusing on 430 respondent of Gen Y which age between 20 – 35 years old who works for a private company. The Questionnaire as primary data source captured 9 aspects of career attitude based on Career Attitudes Strategy Inventory (CASI). This Survey distributes randomly among Gen Y in the IT Industry (125 Respondent) and Manufacture Company (305 Respondent). A Random deep interview was conducted to get the better understanding of the etiology of their primary obstacles. The study showed that most of Indonesia Gen Y have a moderate score on Job satisfaction but in the other aspects, Gen Y has the lowest score on Skill Development, Career Worries, Risk-Taking Style, Dominant Style, Work Involvement, Geographical Barrier, Interpersonal Abuse, and Family Commitment. The top 5 obstacles outside that 9 aspects that faced by Gen Y are 1. Lower communication & networking support; 2. Self-confidence issues; 3. Financial Problem; 4. Emotional issues; 5. Age. We also found that parent perspective toward the way they are nurturing their child are not aligned with their child’s real life. This research fundamentally helps the organization and other Gen Y’s Stakeholders to have a better understanding of Gen Y Career Attitude at the workplace.

Keywords: career attitudes, CASI, Gen Y, career attitude at workplace

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Authors: Mudafara Bengleil

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Estimation of the magnitude and causes of poisoning was the objective of the current study. A retrospective study of medical records of all poisoning children admitted to Benghazi Children Hospital in Libya from January 2008 up to December 2010. Number of children admitted was 244; the age ranged from less than one to 13 years old. Most of cases were admitted with mild symptom and the majority of them were boys. Only few cases admitted to intensive care unit and there was no mortality recorded through the period of study. Age group 1 to 3 years (50.8%) had the highest frequency of admission and the peak of admission was during summer. The most common cause of admission was due to ingestion of medication (53.69%), House hold product exposure (26.64%) was the second causes of admission while, 19.67% of admissions were due to Food poisoning. Almost all admitted cases were accidental and medicines were the most consumed substances in addition, improper storage of toxic agents were the first risk factor of poisoning. Present results indicated that, children poisoning seems to be a common pediatric care problem which need to control and prevent.

Keywords: poisoning, children, hospital, medical

Procedia PDF Downloads 385

Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: Nur Irmawati, H. A. Mohammed

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In the present study, mixed convection in a horizontal rectangular duct using Al2O3 is numerically investigated. The effects of different Rayleigh number, Reynolds number and radiation on flow and heat transfer characteristics were studied in detail. This study covers Rayleigh number in the range of 2×106≤Ra≤2×107 and Reynolds number in the range of 100≤Re≤1100. Results reveal that the Nusselt number increases as Reynolds and Rayleigh numbers increase. It was also found that the dimensionless temperature distribution increases as Rayleigh number increases.

Keywords: numerical simulation, mixed convection, horizontal rectangular duct, nanofluids

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Authors: Eirini Konstanta, Cedric Gouedard, Aggeliki Delimitsou, Stefania Patera, Samuel Murray

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Introduction: Quality reference DNA standards (QRS) for molecular testing by next-generation sequencing (NGS) are essential for accurate quantitation of copy number variations (CNV) for germline and variant allelic frequencies (VAF) for somatic analyses. Objectives: Presently, several molecular analytics for oncology patients are reliant upon quantitative metrics. Test validation and standardisation are also reliant upon the availability of surrogate control materials allowing for understanding test LOD (limit of detection), sensitivity, specificity. We have developed a dual calibration platform allowing for QRS pairs to be included in analysed DNA samples, allowing for accurate quantitation of CNV and VAF metrics within and between patient samples. Methods: QRS™ blocks up to 500nt were designed for common NGS panel targets incorporating ≥ 2 identification tags (IDTDNA.com). These were analysed upon spiking into gDNA, somatic, and ctDNA using a proprietary CalSuite™ platform adaptable to common LIMS. Results: We demonstrate QRS™ calibration reproducibility spiked to 5–25% at ± 2.5% in gDNA and ctDNA. Furthermore, we demonstrate CNV and VAF within and between samples (gDNA and ctDNA) with the same reproducibility (± 2.5%) in a clinical sample of lung cancer and HBOC (EGFR and BRCA1, respectively). CNV analytics was performed with similar accuracy using a single pair of QRS calibrators when using multiple single targeted sequencing controls. Conclusion: Dual paired QRS™ calibrators allow for accurate and reproducible quantitative analyses of CNV, VAF, intrinsic sample allele measurement, inter and intra-sample measure not only simplifying NGS analytics but allowing for monitoring clinically relevant biomarker VAF across patient ctDNA samples with improved accuracy.

Keywords: calibrator, CNV, gene copy number, VAF

Procedia PDF Downloads 122

Authors: Mohammed G. Alotaibi, Sameer Albahkaly, Salwa M. Bahkali, Abdullah M. Alghamdi, Raseel S. Alswidan, Maha Bin Shafi, Sarah Almaiman

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Introduction: Rhinitis is common in Saudi Arabia. Therefore, our study was designed to evaluate the prevalence, triggering factors, severity and progression of rhinitis during pregnancy. Methods: Prospective cross-sectional study was conducted in eight governmental and private medical centers in Riyadh, Saudi Arabia, during June and July 2014. Validated Arabic language self-administered questionnaire was used. Sample size of 260 Saudi pregnant women was calculated by Raosoft sample size calculator. Random sampling was achieved by choosing one and skipping every five patients in the clinic list. Data were coded and entered manually into spreadsheets then transferred to SPSS statistical package version 16.0 for Windows. Consent, Privacy and confidentiality of information were assured. Results: Pregnancy rhinitis was reported 31.2% (CI 25.6 - 37.2%). Symptoms arising in first trimester appeared in 79.2% of PR cases and mostly worsen. The most prevalent symptoms were nasal pruritis (67.5%), followed by sneezing (57.1%), congestion (50.6%), and post nasal drip (46.7%). The major triggering factor was dust (71.4%), followed by Tobacco/Shisha smoke (57.6%) and perfume(47%). Preexisting allergic diseases were markedly associated with developing pregnancy rhinitis. Conclusion: Rhinitis during pregnancy manifested in one third of Saudi pregnant ladies. Nasal pruritus was the most common symptom and dust was the widespread triggering factor.

Keywords: allergy, pregnancy, Rhinitis, sneezing

Procedia PDF Downloads 226

Authors: Pei Yi Lin

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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 37

Authors: David Armany, Matthew Allaway, Preet Gosal, Senarath Edirimanne

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A potentially devastating complication of routine laparoscopic cholecystectomy includes iatrogenic bile duct injuries, which represent a stable incidence rate of 0.3% over the past three decades. Whilst related to several relative risks such as surgeon experience and patient factors (older age, male sex), misinterpretation of biliary tree anatomy remains the most common cause, accounting for 80% of iatrogenic Common Bile Duct injuries. Whilst extremely rare, a duplicate common bile duct anomaly remains a potential variation to encounter during biliary surgery, with 30 recognised cases in the worldwide literature, of which type Vb accounts for 4. We report the case of a rare type Vb variation encountered during intra-operative laparoscopic cholecystectomy and confirmed on cholangiogram. To our knowledge, this is the first documented Type Vb case encountered in an Australian population. Given these anomalies are asymptomatic and can perpetuate iatrogenic common bile duct injuries, awareness of all subtypes is crucial. Irrevocably, preoperative Magnetic Resonance Cholangiopancreatography can help recognise these anomalies before the operating theatre; however, their widespread adoption is limited by expensive and availability.

Keywords: duplicated common bile duct, type Vb, cholecystitis, MRCP, cholangiogram, iatrogenic CBD

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Authors: Xizhen Zhou, Yanjie Ji

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The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Farha Ibrahim, Ely Zarina Samsudin, Ahmad Razali Ishak, Jeyanthini Sathasivam

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Introduction: Indoor air quality (IAQ) has recently gained substantial traction as the airborne transmission of infectious respiratory disease has become an increasing public health concern. Public hospital outpatient department (OPD). IAQ warrants special consideration as it is the most visited department in which patients and staff are all directly impacted by poor IAQ. However, there is limited evidence on IAQ in these settings. Moreover, occupants’ behavior like occupant’s movement and operation of door, windows and appliances, have been shown to significantly affect IAQ, yet the influence of these determinants on IAQ in such settings have not been established. Objectives: This study aims to examine IAQ in Malaysian public hospitals OPD and assess its relationships with occupants’ behavior. Methodology: A multicenter cross-sectional study in which stratified random sampling of Johor public hospitals OPD (n=6) according to building age was conducted. IAQ measurements include indoor air temperature, relative humidity (RH), air velocity (AV), carbon dioxide (CO2), total bacterial count (TBC) and total fungal count (TFC). Occupants’ behaviors in Malaysian public hospital OPD are assessed using observation forms, and results were analyzed. Descriptive statistics were performed to characterize all study variables, whereas non-parametric Spearman Rank correlation analysis was used to assess the correlation between IAQ and occupants’ behavior. Results: After adjusting for potential cofounder, the study has suggested that occupants’ movement in new building, like seated quietly, is significantly correlated with AV in new building (r 0.642, p-value 0.010), CO2 in new (r 0.772, p-value <0.001) and old building (r -0.559, p-value 0.020), TBC in new (r 0.747, p-value 0.001) and old building (r -0.559, p-value 0.020), and TFC in new (r 0.777, p-value <0.001) and old building (r -0.485, p-value 0.049). In addition, standing relaxed movement is correlated with indoor air temperature (r 0.823, p-value <0.001) in new building, CO2 (r 0.559, p-value 0.020), TBC (r 0.559, p-value 0.020), and TFC (r -0.485, p-value 0.049) in old building, while walking is correlated with AV in new building (r -0.642, p-value 0.001), CO2 in new (r -0.772, p-value <0.001) and old building (r 0.559, p-value 0.020), TBC in new (r -0.747, p-value 0.001) and old building (r 0.559, p-value 0.020), and TFC in old building (r -0.485, p-value 0.049). The indoor air temperature is significantly correlated with number of doors kept opened (r 0.522, p-value 0.046), frequency of door adjustments (r 0.753, p-value 0.001), number of windows kept opened (r 0.522, p-value 0.046), number of air-conditioned (AC) switched on (r 0.698, p-value 0.004) and frequency of AC adjustment (r 0.753, p-value 0.001) in new hospital OPD building. AV is found to be significantly correlated with number of doors kept opened (r 0.642, p-value 0.01), frequency of door adjustments (r 0.553, p-value 0.032), number of windows kept opened (r 0.642, p-value 0.01), and frequency of AC adjustment, number of fans switched on, and frequency of fans adjustment(all with r 0.553, p-value 0.032) in new building. In old hospital OPD building, the number of doors kept opened is significantly correlated with CO₂, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), frequency of door adjustment is significantly correlated with CO₂, TBC (both r-0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of windows kept opened is significantly correlated with CO₂, TBC (both r 0.559, p-value 0.020) and TFC (r 0.495, p-value 0.049), frequency of window adjustment is significantly correlated with CO₂,TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of AC switched on is significantly correlated with CO₂, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049),, frequency of AC adjustment is significantly correlated with CO2 (r 0.559, p-value 0.020), TBC (0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of fans switched on is significantly correlated with CO2, TBC (both r 0.559, p-value 0.020) and TFC (r 0.495, p-value 0.049), and frequency of fans adjustment is significantly correlated with CO2, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049). Conclusion: This study provided evidence on IAQ parameters in Malaysian public hospitals OPD and significant factors that may be effective targets of prospective intervention, thus enabling stakeholders to develop appropriate policies and programs to mitigate IAQ issues in Malaysian public hospitals OPD.

Keywords: outpatient department, iaq, occupants practice, public hospital

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Authors: Jian Cao

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This paper describes a novel watermarking technique which we call the random direction embedding (RDE) watermarking. Unlike traditional watermarking techniques, the watermark energy after the RDE embedding does not focus on a fixed direction, leading to the security against the traditional unauthorized watermark removal attack. In addition, the experimental results show that when compared with the existing secure watermarking, namely natural watermarking (NW), the RDE watermarking gains significant improvement in terms of robustness. In fact, the security of the RDE watermarking is not at the cost of low robustness, and it can even achieve more robust than the traditional spread spectrum watermarking, which has been shown to be very insecure.

Keywords: robustness, spread spectrum watermarking, watermarking security, random direction embedding (RDE)

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Authors: Ayaz Ahmad

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In this work, we present the effect of noise on the solution of a partial differential equation (PDE) in three different setting. We shall first consider random initial condition for two nonlinear dispersive PDE the non linear Schrodinger equation and the Kortteweg –de vries equation and analyse their effect on some special solution , the soliton solutions.The second case considered a linear partial differential equation , the wave equation with random initial conditions allow to substantially decrease the computational and data storage costs of an algorithm to solve the inverse problem based on the boundary measurements of the solution of this equation. Finally, the third example considered is that of the linear transport equation with a singular drift term, when we shall show that the addition of a multiplicative noise term forbids the blow up of solutions under a very weak hypothesis for which we have finite time blow up of a solution in the deterministic case. Here we consider the problem of wave propagation, which is modelled by a nonlinear dispersive equation with noisy initial condition .As observed noise can also be introduced directly in the equations.

Keywords: drift term, finite time blow up, inverse problem, soliton solution

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Authors: Michael Tunde Ajayi, Oluwakemi Enitan Fapojuwo

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The study assessed employees’ perception of organizational communication in Oyo State Agricultural Development Programme and its effect on their job performance. A simple random sampling technique was used to select 120 employees using a structured questionnaire for data collection. Findings showed that 66.7% of the respondents were males and 60.4% were between the ages of 31-40 years. Most (87.5%) of the respondents had tertiary education and majority of the respondents (73.9%) had working experience of 5 years or less. Major perceived leadership styles used in communicating to the employees were that employees were not allowed to send feedbacks (X=3.23), information was usually inadequately passed across to the employees (X=2.52), information are given with explanation (X=2.04), leaders rarely gave information on innovation (X=1.91) and information are usually passed in form of order (X=1.89). However, majority (61.5%) of the respondents perceived that the common communication flow used is downward communication system. Respondents perceived that the effects of organizational communication on their job performance were that they were able to know the constraints within the organization (X= 4.89), solve the problem occurring in the organization (X=4.70) and achieve organization objectives (X= 4.40). However, major constraints affecting organizational communication were that there were no cordial relationship among workers (X=3.33), receivers had poor listening skills (X=3.32) and information were not in simple forms (X=3.29). There was a significant relationship between organizational communication (r= 0.984, p<0.05) and employees’ job performance. The study suggested that managers should encourage cordial relationship among workers in other to ease communication flow in organizations and also use adequate medium of communication in other to make information common within organizations.

Keywords: employees’ perception, organizational communication, effects, job performance

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Authors: Akbarnejad Neda

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A foreign language acquisition occurs when we can tell a joke and understand it. Most jokes are told in slang and common language. In the process of foreign language acquisition, an autonomous learner try to learn the standard language. But there is a colossal divergence between the usage of the different types of language in society. Here, we investigate the french slang and common language and examine the accurate perception of their usage. We illuminate the slang language in the french literature that provide considerably different types of language for an autonomous learner. We provide furthermore evidence from the french novels that demonstrate properly the different types of language and give in one sentence its social meanings. For example, the famous Queneau expression « Doukipudonktant » present the impact of slang language in society. The characters in the novel transfer the slang and the common language and their accurate usages. We present that the language of the autonomous learner depends on the language of the text that is read. Because literature is a vehicle of the culture and the expression demonstrate their real significations and usage in the culture, slang and common language have a crucial role in the culture and all of them are manifested in the oral language.

Keywords: common language, french, humor, slang language

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Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

Procedia PDF Downloads 200

Authors: Mawuli M. Sedegah, Emmanuel O. Sarpong, Ernest Y. Acheampong

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Sports injuries among student-athletes in high schools have become prevalent in most developing countries. The study explores the risk factors influencing sports injuries and identify those sustained among high schools’ competitions in the Akuapem Municipality. Drawing on literature from sports injuries, 610 student-athletes were used to understand how they sustained various injuries during schools’ sports and games. Using a cross-sectional survey, the study reveals how wounds, knee injury, muscle cramps, and thigh injury are common injuries in the municipality. The physiological factor was rampant, resulting from the number of games played by student-athletes, which significantly influenced sprain, strain, dislocation, and nose bleeding injuries among them. Results recorded a low correlation accounting for 9% occurrence of sports injuries in the Akuapem Municipality. Further study can be done in the other districts to have a general approach to remedy some of these sports injuries.

Keywords: common injuries, physiological factors, sports injuries, student-athletes

Procedia PDF Downloads 130

Authors: L. M. Al-Harbi, A. M. Shokry, J. S. M. Sabir, A. Chaudhary, J. Manikandan, K. S. Saini

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Breast cancer is the second most common cause of cancer death worldwide and is the most common malignancy among Saudi females. During breast carcinogenesis, a wide-array of cytogenetic changes involving deletions, or amplification, or translocations, of part or whole of chromosome regions have been observed. Because of the limitations of various earlier technologies, newer tools are developed to scan for changes at the genomic level. Recently, Array Comparative Genomic Hybridization (aCGH) technique has been applied for detecting segmental genomic alterations at molecular level. In this study, aCGH was performed on twenty breast cancer tumors and their matching non-tumor (normal) counterparts using the Agilent 2x400K. Several regions were identified to be either amplified or deleted in a tumor-specific manner. Most frequent alterations were amplification of chromosome 1q, chromosome 8q, 20q, and deletions at 16q were also detected. The amplification of genetic events at 1q and 8q were further validated using FISH analysis using probes targeting 1q25 and 8q (MYC gene). The copy number changes at these loci can potentially cause a significant change in the tumor behavior, as deletions in the E-Cadherin (CDH1)-tumor suppressor gene as well as amplification of the oncogenes-Aurora Kinase A. (AURKA) and MYC could make these tumors highly metastatic. This study validates the use of aCGH in Saudi breast cancer patients and sets the foundations necessary for performing larger cohort studies searching for ethnicity-specific biomarkers and gene copy number variations.

Keywords: breast cancer, molecular biology, ecology, environment

Procedia PDF Downloads 349

Authors: A. M. Nasr, W. R. Azzam, K. E. Ebeed

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For bored piles, careful cleaning must be used to reduce the amount of material trapped in the drilled hole; otherwise, the debris' presence might cause the soft toe effect, which would affect the axial resistance. There isn't much comprehensive research on bored piles with debris. In order to investigate the behavior of a single pile, a pile composite foundation, a two pile group, a three pile group and a four pile group investigation conducts, forty-eight numerical tests in which the debris is simulated using foam rubber.1m pile diameter and 10m length with spacing 3D and depth of foundation 1m used in this study. It is found that the existence of debris causes a reduction of bearing capacity by 64.58% and 33.23% for single pile and pile composite foundation, respectively, 23.27% and 24.24% for the number of defective piles / total number of pile =1/2 and 1 respectively for two group pile, 10.23%, 19.42% and 28.47% for the number of defective piles / total number of pile =1/3,2/3 and 1 respectively for three group pile and, this reduction increase with the increase in a number of defective piles / a total number of piles and 7.1%, 13.32%,19.02% and 26.36 for the number of defective piles / total number of pile =1/4,2/4,3/4 and 1 respectively for four group pile and decreases with an increase of number of pile duo to interaction effect.

Keywords: debris, Foundation, defective, interaction, board pile

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Authors: H. Amellal, Y. Noui, A. Djouab, S. Benamara

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Mech-Degla, Degla-Beida, and Frezza are the date (Phoenix dactylifera L.) common varieties with a more or less good availability and feeble trade value. Some morphologic and physicochemical factors were determined. Results show that the whole date weight is significantly different (P= 95%) concerning Mech-Degla and Degla-Beida which are more commercialised than Frezza whereas the pulp/kernel ratio for this last is highest (above 7) since it represents almost the double of that found for the two other varieties. The water content for all fruits is below 15g/100g (wet basis) what confers a dried consistence for common date. Some other morphologic and chemical proprieties of the whole pulps and their two constitutive parts (brown or pigmented and white) are also investigated. The predominance of phenolics in Mech-Degla (4.01g/100g, w.b) and Frezza (4.96 g/100g, w.b) pulps brown part is the main result revealed in this study.

Keywords: common dates, phenolics, sugars, tissues

Procedia PDF Downloads 382

Authors: Jayaprakash Kar, Daniyal M. Alghazzawi

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The article proposes a novel construction of signcryption scheme with provable security which is most suited to implement on smart card. It is secure in random oracle model and the security relies on Decisional Bilinear Diffie-Hellmann Problem. The proposed scheme is secure against adaptive chosen ciphertext attack (indistiguishbility) and adaptive chosen message attack (unforgebility). Also, it is inspired by zero-knowledge proof. The two most important security goals for smart card are Confidentiality and authenticity. These functions are performed in one logical step in low computational cost.

Keywords: random oracle, provable security, unforgebility, smart card

Procedia PDF Downloads 568

Authors: Laissa Mae Francisco, John Rolex Ingreso, Anna Krizel Menguito, Criselda Robrigado, Rej Maegan Tuazon

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This study aims to determine and describe the existing relationship between number sense proficiency and problem-solving performance of grade seven students from Victorino Mapa High School, Manila. A paper pencil exam containing of 50-item number sense test and 5-item problem-solving test which measures their number sense proficiency and problem-solving performance adapted from McIntosh, Reys, and Bana were used as the research instruments. The data obtained from this study were interpreted and analyzed using the Pearson – Product Moment Coefficient of Correlation to determine the relationship between the two variables. It was found out that students who were low in number sense proficiency tend to be the students with poor problem-solving performance and students with medium number sense proficiency are most likely to have an average problem-solving performance. Likewise, students with high number sense proficiency are those who do excellently in problem-solving performance.

Keywords: number sense, performance, problem solving, proficiency

Procedia PDF Downloads 397

Authors: Behnaz Moradijamei, Michael Higgins

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Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

Procedia PDF Downloads 115