Search results for: statistical data analysis

Authors: Ethan Petersen

Abstract:

In this paper, we analyze the volatility of Apple’s stock beginning January 3, 2005 up to October 9, 2014, then focus on a range from 30 days prior to each product announcement until 30 days after. Product announcements are filtered; announcements whose 60 day range is devoid of other events are separated. This filtration is chosen to isolate, and study, a potential cross-effect. Concerning Apple keynotes, there are two significant dates: the day the invitations to the event are received and the day of the event itself. As such, the statistical analysis is conducted for both invite-centered and event-centered time frames. A comparison to the VIX is made to determine if the trend is simply following the market or deviating. Regardless of the filtration, we find that there is a clear deviation from the market. Comparing these data sets, there are significantly different trends: isolated events have a constantly decreasing, erratic trend in volatility but an increasing, linear trend is observed for clustered events. According to the Efficient Market Hypothesis, we would expect a change when new information is publicly known and the results of this study support this claim.

Keywords: efficient market hypothesis, event study, volatility, VIX

Procedia PDF Downloads 278

Authors: Muhammad Luqman, Mujahid Karim

Abstract:

Agricultural journalism considered an effective tool in the diffusion of agricultural technologies among the members of farming communities. Various agricultural journalism forms are used by the different organization in order to address the community problems and provide solutions to them. The present study was conducted for analyzing the role of agricultural journalism in the dissemination of agricultural information. The universe of the study was district Sargodha from which a sample of 100 was collected through a validating and pre-tested questionnaire. Statistical analysis of collected data was done with the help of SPSS. It was concluded that majority (64.6%) of the respondent were middle-aged (31-50) years, also indicates a high (73.23%) literacy rate above middle-level education, most (78.3%) of the respondents were connected with the occupation of farming. In various forms of agricultural journalism “Radio/T.V./F.M) is used by 99.4% of the respondent, Mobile phones (96%), Magazine/ Newspaper/ periodical (66.4%) and social media (60.9%). Regarding majors areas focused on agriculture journalism “Help farmers to enhance their productivity is on the highest level with a mean of ( =3.98/5.00). The regression model of farmer's education and various forms of agricultural journalism facilities used was found to be significant.

Keywords: agricultural information, journalism, farming community, technology diffusion and adoption

Procedia PDF Downloads 193

Authors: Som Pal Baliyan

Abstract:

The purpose of this quantitative study was to analyze farm management skills in broiler poultryproducers in Botswana. The study adopted a descriptive and correlation research design. The population of the study was the poultry farm operators who had been in broiler poultry farming at least for two years. Based on the information from literature, a questionnaire was constructed for data collection on seven areas of farm management skills namely; planning skills, accounting and financial management skills, production management skills, product procurement and marketing skills, decision making skills, risk management skills, and specific technical skills. The validity and reliability of the questionnaire were accomplished by a panel of experts and by calculating the Cronbach’s alpha coefficient, respectively. Data were collected through a survey of 60 randomly sampled poultry farm operators in Botswana. Data were analyzed through descriptive statistical tools whereby the level of farm management skills were determined by calculating means and standard deviations of the management skills among the broiler producers. The level of farm management skills in broilers producers was discussed. All the seven farm management skills were ranked based on their calculated means. The specific technical skills and risk management skills were the highest and the lowest ranked farm management skills, respectively.Findings revealed that the broiler producers had skills above the average level only in specific technical skills whereas the skill levels in the remaining six farm management skills under study were found below the average level. This prevailing low level of farm management skills can be justified asthe cause of failure or poor performance of the broiler poultry farms in Botswana. Therefore, in order to improve the efficiency and productivityin broiler production in the country, it was recommended that the broiler poultry producers should be adequately trained in areas of planning skills, financial management skills, production management skills, product procurement and marketing skills, decision making skills and risk management skills.

Keywords: poultry production, broiler production, management skills, levels of skills

Procedia PDF Downloads 398

Authors: Yumei Wu, Xiaoyan Dang, Shenglong Yang, Shengmao Zhang

Abstract:

The East China Sea is one of four main seas in China, where there are many fishery resources. Some important fishing grounds, such as Zhousan fishing ground important to society. But the eco-environment is destroyed seriously due to the rapid developing of industry and economy these years. In this paper, about twenty-year satellite data from MODIS and the statistical information of marine environment from the China marine environmental quality bulletin were applied to do the research. The chlorophyll-a concentration data from MODIS were dealt with in the East China Sea and then used to analyze the features and variations of plankton biomass in recent years. The statistics method was used to obtain their spatial and temporal features. The plankton biomass in the Yangtze River estuary and the Taizhou region were highest. The high phytoplankton biomass usually appeared between the 88th day to the 240th day (end-March - August). In the peak time of phytoplankton blooms, the Taizhou islands was the earliest, and the South China Sea was the latest. The intensity and period of phytoplankton blooms were connected with the global climate change. This work give us confidence to use satellite data to do more researches about the China Sea, and it also provides some help for us to know about the eco-environmental variation of the East China Sea and regional effect from global climate change.

Keywords: the East China Sea, phytoplankton biomass, temporal and spatial variation, phytoplankton bloom

Procedia PDF Downloads 328

Authors: Habtamu Wolde Engudai

Abstract:

Background: Sedation can be provided to facilitate a procedure or to stabilize patients admitted in pediatric intensive care unit (PICU). Sedation is often necessary to maintain optimal care for critically ill children requiring mechanical ventilation. However, if sedation is too deep or too light, it has its own adverse effects, and hence, it is important to monitor the level of sedation and maintain an optimal level. Objectives: The objective is to assess the level of sedation and associated factors among intubated critically ill children admitted to PICU of JUMC, Jimma. Methods: A prospective observation study was conducted in the PICU of JUMC in September 2021 in 105 patients who were going to be admitted to the PICU aged less than 14 and with GCS >8. Data was collected by residents and nurses working in PICU. Data entry was done by Epi data manager (version 4.6.0.2). Statistical analysis and the creation of charts is going to be performed using SPSS version 26. Data was presented as mean, percentage and standard deviation. The assumption of logistic regression and the result of the assumption will be checked. To find potential predictors, bi-variable logistic regression was used for each predictor and outcome variable. A p value of <0.05 was considered as statistically significant. Finally, findings have been presented using figures, AOR, percentages, and a summary table. Result: in this study, 105 critically ill children had been involved who were started on continuous or intermittent forms of sedative drugs. Sedation level was assessed using a comfort scale three times per day. Based on this observation, we got a 44.8% level of suboptimal sedation at the baseline, a 36.2% level of suboptimal sedation at eight hours, and a 24.8% level of suboptimal sedation at sixteen hours. There is a significant association between suboptimal sedation and duration of stay with mechanical ventilation and the rate of unplanned extubation, which was shown by P < 0.05 using the Hosmer-Lemeshow test of goodness of fit (p> 0.44).

Keywords: level of sedation, critically ill children, Pediatric intensive care unit, Jimma university

Procedia PDF Downloads 59

Authors: Medan Isaeva, Anna Degtyareva

Abstract:

Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

Procedia PDF Downloads 53

Authors: Ibrahim Umar, S Chindo, A Rajab

Abstract:

Background: TB remains a disease of public health concern in Nigeria with an estimated incidence rate of 219/100,000. Kano has the second highest TB burden in Nigeria and is the leading state with the highest consistent yearly TB notification. House-to-house (H2H) active case search in the community was found to have major contribution to the total TB notification in the state. Aims and Objective: To showcase the impact of H2H community active TB case search (ACF) to yearly TB notification in Kano State, Northern Nigeria from 2012 to 2022. Methodology: This is a retrospective descriptive study based on the analysis of data collected during the routine quarterly and yearly TB data collected in the state. Data was analyzed using the Power BI with statistical alpha level of significance <0.05. Results: Between 2012 and 2013 there was no House-to-house active TB case search in Nigeria and Kano had zero contribution to TB notification from the community in those years. However, in 2014 with the introduction of H2H Active TB Case Search Kano notified 6,014 TB cases out of which 113 came from the community ACF that translated to 2% contribution to total TB notification. From 2014 to 2022 there was progressive increase in community contribution to TB case notification from 113 out of 6,014 total TB patients notified (2012) to 11,799 out of 26,371 TB patients notified (2022) in Kano State. This translated to 45% increase in community contribution to total TB case notification. Discussion: Remarkable increase in community contribution to total TB case notification in Kano State was achieved in 2022 with 11,799 TB cases notified from the community Active TB case search to the total of 26,731 TB cases notified in Kano State, Nigeria. Conclusion: in research has shown that Community-based H2H Active TB Case Search through Community TB Workers (CTWs) is an excellent strategy in finding the missing TB cases towards Ending TB in the world.

Keywords: tuberculosis(TB), active case search (ACF), house-to-house (H2H), community TB workers (CTWs)

Procedia PDF Downloads 88

Authors: Samson Olusegun Apantaku, Adetayo K. Aromolaran, Giyatt Hammed

Abstract:

The study assessed the use of participatory research methods among Federal University of Agriculture Abeokuta, Nigeria (FUNAAB) researchers. Simple random sampling technique was used to select one hundred and twenty respondents from the study area. Data were collected using a questionnaire. Data collected were subjected to descriptive and inferential statistical analyses. Results showed that 75.8% of the respondents were males while only 21.3% were female. The mean age of the respondents was 38.8 years and most (77.5%) of them were married. 15% of the respondents were in professorial cadre, 21.7% and 20% of the respondents were senior lecturers/fellow and lecturer/research fellow I&II respectively. The results further revealed that 93.3% of the respondents were aware of participatory research methods and 82.5% of the respondents have utilized it before. The average period of usage was 2.7 years and participation by consultation (86.7%) and interactive participation (76.7%) were mostly used. Most (94.2%) indicated that fund was the major hindrance to the use of participatory research methods. The result of correlation analysis showed that there was significant relationship between the years of research experience, designation post (status) of the respondents and usage of participatory research methods (r = 0.034, 0.031, p < 0.05). The study concluded that most of the researchers were aware of and used participatory research methods, which could influence the quality of their research or make it acceptable to the end users. It was recommended that more funds should be made available and accessible for participatory research. All researchers should be trained and encouraged to make use of participatory research methods in their research activities so as to achieve effective research and capacity building that could enhance adoption of technologies and increase agricultural production in the country. Farmers’ capacity to participate in agricultural research should also be enhanced.

Keywords: participatory research, participatory research methods, awareness, utilization

Procedia PDF Downloads 419

Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

Abstract:

Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

Procedia PDF Downloads 207

Authors: Riccardo Pasquali, Keith Harlin, Mark Muller

Abstract:

The ShallowTherm project is focussed on developing and applying a methodology for extrapolating relatively sparsely sampled thermal conductivity measurements across Ireland using mapped Litho-Electrical (LE) units. The primary data used consist of electrical resistivities derived from the Geological Survey Ireland Tellus airborne electromagnetic dataset, GIS-based maps of Irish geology, and rock thermal conductivities derived from both the current Irish Ground Thermal Properties (IGTP) database and a new programme of sampling and laboratory measurement. The workflow has been developed across three case-study areas that sample a range of different calcareous, arenaceous, argillaceous, and volcanic lithologies. Statistical analysis of resistivity data from individual geological formations has been assessed and integrated with detailed lithological descriptions to define distinct LE units. Thermal conductivity measurements from core and hand samples have been acquired for every geological formation within each study area. The variability and consistency of thermal conductivity measurements within each LE unit is examined with the aim of defining a characteristic thermal conductivity (or range of thermal conductivities) for each LE unit. Mapping of LE units, coupled with characteristic thermal conductivities, provides a method of defining thermal conductivity properties at a regional scale and facilitating the design of ground source heat pump closed-loop collectors.

Keywords: thermal conductivity, ground source heat pumps, resistivity, heat exchange, shallow geothermal, Ireland

Procedia PDF Downloads 177

Authors: Farouk Lawan Gambo

Abstract:

Data compression shrinks files into fewer bits then their original presentation. It has more advantage on internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature therefore making them difficult to digest by some students (Engineers in particular). To determine the best approach toward learning data compression technique, this paper first study the learning preference of engineering students who tend to have strong active, sensing, visual and sequential learning preferences, the paper also study the advantage that mobility of learning have experienced; Learning at the point of interest, efficiency, connection, and many more. A survey is carried out with some reasonable number of students, through random sampling to see whether considering the learning preference and advantages in mobility of learning will give a promising improvement over the traditional way of learning. Evidence from data analysis using Ms-Excel as a point of concern for error-free findings shows that there is significance different in the students after using learning content provided on smart phone, also the result of the findings presented in, bar charts and pie charts interpret that mobile learning has to be promising feature of learning.

Keywords: data analysis, compression techniques, learning content, traditional learning approach

Procedia PDF Downloads 345

Authors: Chimeri Muzano Leonard

Abstract:

The study was carried out to investigate the perceptions of male and female Ordinary Level students on the effects of alcohol abuse at Gatsi Secondary School. The study showed that alcohol abuse has academic, social, psychological and health effects on Ordinary Level students. The negative effects comprises of death, dropping out, poor grades, poor concentration, risky behaviors, impairment of the brain and central nervous system , risky behaviors and Impairment of reproductive functioning Only students who enrolled for Ordinary Level in the 2014 academic year participated in this study. Fifty students (25 males and 25 females) were randomly selected to participate in the study. A formal survey questionnaire was used to collect data. The respondents were asked to use a scale of 0 (totally disagree) to 10 (completely agree) to indicate the extent to which they agreed with each perception. The Statistical Package for Social Sciences (SPSS) version 19.0 was used for data analysis. The Mann Whitney U test was used to test for the significance of differences in the perceptions of male and female students. No statistically significant differences were detected between males and females in most of their perceptions regarding the effects of alcohol abuse on Ordinary Level students. However, there were three perceptions found to be significantly different between male and female. They comprises of “Peers influence one to drink alcohol”, “Alcohol abuse is a major problem among male students compared to their female peers” and “ Female students should not drink beer”.It was evident from this study that Gatsi Secondary School needs to implement more effective interventions that combat alcohol abuse. A deeper analysis of the issues that predispose Ordinary Level students to alcohol abuse should inform the interventions. Consequently, unravelling the problem of negative effects of alcohol abuse was desirable because of its potential usefulness in developing strategies that might help curb the problem and presumably improve the performance of Ordinary Level students and above all the quality of education at Gatsi Secondary School.

Keywords: perceived effects, alcohol, Gatsi Secondary School, alcohol abuse

Procedia PDF Downloads 239

Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

Abstract:

Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

Procedia PDF Downloads 503

Authors: Befekadu Urga Wakayo

Abstract:

Introduction: Bacterial infections represent major human and animal health problems in Ethiopia. In the face of poor antibiotic regulatory mechanisms, development of antimicrobial resistance (AMR) to commonly used drugs has become a growing health and livelihood threat in the country. Monitoring and control of AMR demand close coloration between human and veterinary services as well as other relevant stakeholders. However, risk of AMR transfer from animal to human population’s remains poorly explored in Ethiopia. This systematic research literature review attempted to give an overview on AMR challenges of bovine mastitis bacteria in Ethiopia. Methodology: A web based research literature search and analysis strategy was used. Databases are considered including; PubMed, Google Scholar, Ethiopian Veterinary Association (EVA) and Ethiopian Society of Animal Production (ESAP). The key search terms and phrases were; Ethiopia, dairy, cattle, mastitis, bacteria isolation, antibiotic sensitivity and antimicrobial resistance. Ultimately, 15 research reports were used for the current analysis. Data extraction was performed using a structured Microsoft Excel format. Frequency AMR prevalence (%) was registered directly or calculated from reported values. Statistical analysis was performed on SPSS – 16. Variables were summarized by giving frequencies (n or %), Mean ± SE and demonstrative box plots. One way ANOVA and independent t test were used to evaluate variations in AMR prevalence estimates (Ln transformed). Statistical significance was determined at p < 0.050). Results: AMR in bovine mastitis bacteria was investigated in a total of 592 in vitro antibiotic sensitivity trials involving 12 different mastitis bacteria (including 1126 Gram positive and 77 Gram negative isolates) and 14 antibiotics. Bovine mastitis bacteria exhibited AMR to most of the antibiotics tested. Gentamycin had the lowest average AMR in both Gram positive (2%) and negative (1.8%) bacteria. Gram negative mastitis bacteria showed higher mean in vitro resistance levels to; Erythromycin (72.6%), Tetracycline (56.65%), Amoxicillin (49.6%), Ampicillin (47.6%), Clindamycin (47.2%) and Penicillin (40.6%). Among Gram positive mastitis bacteria higher mean in vitro resistance was observed in; Ampicillin (32.8%), Amoxicillin (32.6%), Penicillin (24.9%), Streptomycin (20.2%), Penicillinase Resistant Penicillin’s (15.4%) and Tetracycline (14.9%). More specifically, S. aurues exhibited high mean AMR against Penicillin (76.3%) and Ampicillin (70.3%) followed by Amoxicillin (45%), Streptomycin (40.6%), Tetracycline (24.5%) and Clindamycin (23.5%). E. coli showed high mean AMR to Erythromycin (78.7%), Tetracycline (51.5%), Ampicillin (49.25%), Amoxicillin (43.3%), Clindamycin (38.4%) and Penicillin (33.8%). Streptococcus spp. demonstrated higher (p =0.005) mean AMR against Kanamycin (> 20%) and full sensitivity (100%) to Clindamycin. Overall, mean Tetracycline (p = 0.013), Gentamycin (p = 0.001), Polymixin (p = 0.034), Erythromycin (p = 0.011) and Ampicillin (p = 0.009) resistance increased from the 2010’s than the 2000’s. Conclusion; the review indicated a rising AMR challenge among bovine mastitis bacteria in Ethiopia. Corresponding, public health implications demand a deeper, integrated investigation.

Keywords: antimicrobial resistance, dairy cattle, Ethiopia, Mastitis bacteria

Procedia PDF Downloads 245

Authors: S. C. Sharma, Ankit Gambhir, Rajeev Arya

Abstract:

In today’s era data security is an important concern and most demanding issues because it is essential for people using online banking, e-shopping, reservations etc. The two major techniques that are used for secure communication are Cryptography and Steganography. Cryptographic algorithms scramble the data so that intruder will not able to retrieve it; however steganography covers that data in some cover file so that presence of communication is hidden. This paper presents the implementation of Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) Algorithm with Image and Audio Steganography and Data Encryption Standard (DES) Algorithm with Image and Audio Steganography. The coding for both the algorithms have been done using MATLAB and its observed that these techniques performed better than individual techniques. The risk of unauthorized access is alleviated up to a certain extent by using these techniques. These techniques could be used in Banks, RAW agencies etc, where highly confidential data is transferred. Finally, the comparisons of such two techniques are also given in tabular forms.

Keywords: audio steganography, data security, DES, image steganography, intruder, RSA, steganography

Procedia PDF Downloads 287

Authors: Nadia Obaed, Lexi Frankel, Amalia Ardeljan, Denis Nigel, Anniki Witter, Omar Rashid

Abstract:

Breast cancer is the most common cancer among women, with a lifetime risk of one in eight of all women in the United States. Although breast cancer is prevalent throughout the world, the uneven distribution in incidence and mortality rates is shaped by the variation in population structure, environment, genetics and known lifestyle risk factors. Furthermore, the bacterial profile in healthy and cancerous breast tissue differs with a higher relative abundance of bacteria capable of causing DNA damage in breast cancer patients. Previous bacterial infections may change the composition of the microbiome and partially account for the environmental factors promoting breast cancer. One study found that higher amounts of Staphylococcus, Bacillus, and Enterobacteriaceae, of which Escherichia coli (E. coli) is a part, were present in breast tumor tissue. Based on E. coli’s ability to damage DNA, it is hypothesized that there is an increased risk of breast cancer associated with previous E. coli infection. Therefore, the purpose of this study was to evaluate the correlation between E. coli infection and the incidence of breast cancer. Holy Cross Health, Fort Lauderdale, provided access to the Health Insurance Portability and Accountability (HIPAA) compliant national database for the purpose of academic research. International Classification of Disease 9th and 10th Codes (ICD-9, ICD-10) was then used to conduct a retrospective analysis using data from January 2010 to December 2019. All breast cancer diagnoses and all patients infected versus not infected with E. coli that underwent typical E. coli treatment were investigated. The obtained data were matched for age, Charlson Comorbidity Score (CCI score), and antibiotic treatment. Standard statistical methods were applied to determine statistical significance and an odds ratio was used to estimate the relative risk. A total of 81286 patients were identified and analyzed from the initial query and then reduced to 31894 antibiotic-specific treated patients in both the infected and control group, respectively. The incidence of breast cancer was 2.51% and present in 2043 patients in the E. coli group compared to 5.996% and present in 4874 patients in the control group. The incidence of breast cancer was 3.84% and present in 1223 patients in the treated E. coli group compared to 6.38% and present in 2034 patients in the treated control group. The decreased incidence of breast cancer in the E. coli and treated E. coli groups was statistically significant with a p-value of 2.2x10-16 and 2.264x10-16, respectively. The odds ratio in the E. coli and treated E. coli groups was 0.784 and 0.787 with a 95% confidence interval, respectively (0.756-0.813; 0.743-0.833). The current study shows a statistically significant decrease in breast cancer incidence in association with previous Escherichia coli infection. Researching the relationship between single bacterial species is important as only up to 10% of breast cancer risk is attributable to genetics, while the contribution of environmental factors including previous infections potentially accounts for a majority of the preventable risk. Further evaluation is recommended to assess the potential and mechanism of E. coli in decreasing the risk of breast cancer.

Keywords: breast cancer, escherichia coli, incidence, infection, microbiome, risk

Procedia PDF Downloads 252

Authors: Sakul Jariyachansit

Abstract:

The purposes of this research were to investigate and to compare the factors affecting the decision for Tourism in Thailand by ASEAN Tourists and among ASEAN community tourists. Samples in this research were 400 ASEAN Community Tourists who travel in Thailand at Suvarnabhumi Airport during November 2016 - February 2016. The researchers determined the sample size by using the formula Taro Yamane at 95% confidence level tolerances 0.05. The English questionnaire, research instrument, was distributed by convenience sampling, for gathering data. Descriptive statistics was applied to analyze percentages, mean and standard deviation and used for hypothesis testing. The statistical analysis by multiple regression analysis (Multiple Regression) was employed to prove the relationship hypotheses at the significant level of 0.01. The results showed that majority of the respondents indicated the factors affecting the decision for Tourism in Thailand by ASEAN Tourists, in general there were a moderate effects and the mean of each side is moderate. Transportation was the most influential factor for tourism in Thailand. Therefore, the mode of transport, information, infrastructure and personnel are very important to factor affecting decision making for tourism in Thailand by ASEAN tourists. From the hypothesis testing, it can be predicted that the decision for choosing Tourism in Thailand is at R2 = 0.449. The predictive equation is decision for choosing Tourism in Thailand = 1.195 (constant value) + 0.425 (tourist attraction) +0.217 (information received) and transportation factors, tourist attraction, information, human resource and infrastructure at the significant level of 0.01.

Keywords: factor, decision making, ASEAN tourists, tourism in Thailand

Procedia PDF Downloads 206

Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

Abstract:

This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

Procedia PDF Downloads 62

Authors: Benjamin Osae Agyei, Hypolite Bayor

Abstract:

This present experiment was carried out during the 2012 cropping season, at the Farming for the Future Experimental Field of the University for Development Studies, Nyankpala Campus in the Northern Region of Ghana. The objective of the experiment was to determine the carrot growth and yield responses to poultry manure and N.P.K (15:15:15). Six treatments (Control (no amendment), 20 t/ha poultry manure (PM), 40 t/ha PM, 70 t/ha PM, 35 t/ha PM + 0.11t/ha N.P.K and 0.23 t/ha N.P.K) with three replications for each were laid in a Randomized Complete Block Design (RCBD). Data were collected on plant height, number of leaves per plant, canopy spread, root diameter, root weight, and root length. Microsoft Excel and Genstat Statistical Package (9^th edition) were used for the data analysis. The treatment means were compared by using Least Significant Difference at 10%. Generally, the results showed that there were no significant differences (P>0.1) among the treatments with respect to number of leaves per plant, root diameter, root weight, and root length. However, significant differences occurred among plant heights and canopy spreads. Plant height treated with 40 t/ha PM at the fourth week after planting and canopy spread at eight weeks after planting and ten weeks after planting by 70 t/ha PM and 20 t/ha PM respectively showed significant difference (P<0.1). The study recommended that any of the amended treatments can be applied at their recommended rates to plots for carrot production, since there were no significant differences among the treatments.

Keywords: poultry manure, N.P.K., soil amendment, growth, yield, carrot

Procedia PDF Downloads 471

Authors: Bushra Zafar, Usman Qamar

Abstract:

Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

Procedia PDF Downloads 315

Authors: Thiago M. R. Dias, Patrícia M. Dias, Gray F. Moita

Abstract:

The production and publication of scientific works have increased significantly in the last years, being the Internet the main factor of access and distribution of these works. Faced with this, there is a growing interest in understanding how scientific research has evolved, in order to explore this knowledge to encourage research groups to become more productive. Therefore, the objective of this work is to explore repositories containing data from scientific publications and to characterize keyword networks of these publications, in order to identify the most relevant keywords, and to highlight those that have the greatest impact on the network. To do this, each article in the study repository has its keywords extracted and in this way the network is  characterized, after which several metrics for social network analysis are applied for the identification of the highlighted keywords.

Keywords: bibliometrics, data analysis, extraction and data integration, scientometrics

Procedia PDF Downloads 257

Authors: Biniam Tedros Kahsay, Yohannes Yebabe Tesfay

Abstract:

Eritrea is a country in the East of Africa. The country is a neighbor of Djibouti, Ethiopia, and Sudan and is bordered by the Red Sea. The country declared its independence from Ethiopia in 1993. Thus, Eritrea has a lot of commonalities with the Northern Part of Ethiopia's tradition, religion, and languages. Many economists suggested that Eritrea is in a very strategic position for world trade roots and has an impact on geopolitics. This study focused on identifying the most important factor in boosting the Eritrean Economy. The paper collected big secondary data from the World Bank, International Trade and Tariff Data (WTO), East African Community (EAC), Ethiopian Statistical Agency (ESA), and the National Statistics Office (Eritrea). Economists consider economic and population growth in determining trade belts in East Africa. One of the most important Trade Belt that will potentially boost the Eritrean economy is the root of Eritrea (Massawa)->Eritea, (Asmara)->Tigray, (Humora)->Tigray, (Dansha)-> Gondar-> Gojjam-> Benshangual Gumuz => {Oromia, South Sudan}->Uganda. The estimate showed that this is one of the biggest trade roots in East Africa and has a participation of more than 150 million people. We employed various econometric analyses to predict the GDP of Eritrea, considering the future trade belts in East Africa. The result showed that the economy of Eritrea from the Trade Belt will have an elasticity estimate of 65.87% of the GDP of Ethiopia, 3.32% of the GDP of South Sudan, and 0.09% of the GDP of Uganda. The result showed that the existence of war has an elasticity of -93% to the GDP of the country. Thus, if Eritrea wants to strengthen its economy from the East African Trade Belt, the country needs to permanently avoid war in the region. Essentially, the country needs to establish a collaborative platform with the Northern part of Ethiopia (Tigray). Thus, establishing a mutual relationship with Tigray will boost the Eritrean economy. In that regard, Eritrean scholars and policymakers need to work on establishing the East African Trade Belt to boost their economy.

Keywords: Eritrea, east Africa trade belt, GDP, cointegration analysis, critical path analysis

Procedia PDF Downloads 56

Authors: Abdolmajid Mosleh, Afzal Ghasimi

Abstract:

The purpose of this research is to investigate and identify effective factors that can improve the quality of personal performance in industrial companies. In the present study, it was assumed that the hidden variables of talent management could be explained by an important part of the variance in improving the quality of employee performance. This research is targeted in terms of applied research. The statistical population of the research is SAIPA automobile company with a number (N=10291); the sample of 380 people was selected based on the Cochran formula in a random sampling method among employed people. The measurement tool in this research was a questionnaire of 33 items with a control questionnaire that included two talent management departments (talent identification and talent exploitation) and improvements in staff performance (enhancement of technical and specialized capabilities, managerial capability, organizational interaction, and communication). The reliability of the internal consistency method was confirmed by the Cronbach's alpha coefficient and the two half-ways. In order to determine the validity of the questionnaire structure, confirmatory factor analysis was used. Based on the results of the data analysis, the effect of talent management on improving the quality of staff performance was confirmed. Based on the results of inferential statistics and structural equations of the proposed model, it had high fitness.

Keywords: employee performance, talent management, performance improvement, SAIPA automobile manufacturing company

Procedia PDF Downloads 90

Authors: Subir Gupta, Subhas Ganguly

Abstract:

In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

Procedia PDF Downloads 197

Authors: J. R. Wang, Y. Chiang, W. S. Hsu, S. H. Chen, J. H. Yang, S. W. Chen, C. Shih, Y. F. Chang, Y. H. Huang, B. R. Shen

Abstract:

In this research, the RASCAL code was used to simulate and analyze the postulated UF₆ fire accident which may occur in the Institute of Nuclear Energy Research (INER). There are four main steps in this research. In the first step, the UF₆ data of INER were collected. In the second step, the RASCAL analysis methodology and model was established by using these data. Third, this RASCAL model was used to perform the simulation and analysis of the postulated UF₆ fire accident. Three cases were simulated and analyzed in this step. Finally, the analysis results of RASCAL were compared with the hazardous levels of the chemicals. According to the compared results of three cases, Case 3 has the maximum danger in human health.

Keywords: RASCAL, UF₆, safety, hydrogen fluoride

Procedia PDF Downloads 221

Authors: Esther Mafunda, Simbarashe Muparangi

Abstract:

The present paper tests the applicability of the Regression Hypothesis on the pathological language dissolution of a Shona male adult with Broca’s aphasia. It particularly assesses the prediction of the Regression Hypothesis, which states that the process according to which language is forgotten will be the reversal of the process according to which it will be acquired. The main aim of the paper is to find out whether mirror symmetries between L1 acquisition and L1 dissolution of tense in Shona and, if so, what might cause these regression patterns. The paper also sought to highlight the practical contributions that Linguistic theory can make to solving language-related problems. Data was collected from a 46-year-old male adult with Broca’s aphasia who was receiving speech therapy at St Giles Rehabilitation Centre in Harare, Zimbabwe. The primary data elicitation method was experimental, using the probe technique. The TART (Test for Assessing Reference Time) Shona version in the form of sequencing pictures was used to access tense by Broca’s aphasic and 3.5-year-old child. Using the SPSS (Statistical Package for Social Studies) and Excel analysis, it was established that the use of the future tense was impaired in Shona Broca’s aphasic whilst the present and past tense was intact. However, though the past tense was intact in the male adult with Broca’s aphasic, a reference to the remote past was made. The use of the future tense was also found to be difficult for the 3,5-year-old speaking child. No difficulties were encountered in using the present and past tenses. This means that mirror symmetries were found between L1 acquisition and L1 dissolution of tense in Shona. On the basis of the results of this research, it can be concluded that the use of tense in a Shona adult with Broca’s aphasia supports the Regression Hypothesis. The findings of this study are important in terms of speech therapy in the context of Zimbabwe. The study also contributes to Bantu linguistics in general and to Shona linguistics in particular. Further studies could also be done focusing on the rest of the Bantu language varieties in terms of aphasia.

Keywords: Broca’s Aphasia, regression hypothesis, Shona, language dissolution

Procedia PDF Downloads 94

Authors: Mohammad Hosein Panahi, Naser Yazdani

Abstract:

we present a technical trading strategy that leverages the FinBERT language model and financial news analysis with a focus on news related to a subset of Nasdaq 100 stocks. Our approach surpasses the baseline Range Break-out strategy in the Bitcoin market, yielding a remarkable 24.8% increase in the win ratio for all Friday trades and an impressive 48.9% surge in short trades specifically on Fridays. Moreover, we conduct rigorous hypothesis testing to establish the statistical significance of these improvements. Our findings underscore considerable potential of our NLP-driven approach in enhancing trading strategies and achieving greater profitability within financial markets.

Keywords: quantitative finance, technical analysis, bitcoin market, NLP, language models, FinBERT, technical trading

Procedia PDF Downloads 73

Authors: Guebli Abdelkader, Zerf Mohammed, Mekkades Moulay Idriss, BenGoua Ali, Atouti Nouredinne, Habchi Nawel

Abstract:

The paper aims to show the influence of angles in the results of triple jump. Whereas our background confirms that a series of motions are characterized by complex angles in the properties phase (hop, step, and jump) as a combination of the pushed phase on ultimate phases in the result. For the purpose, our results are obtained from the National Athletics Championship 2013, which was filmed and analysis by the software kinovea. Based on the statistical analysis we confirm: there is a positive relationship between angle of the leg, hip angle, angle of the trunk in the collision during (hop, step, and jump), and there is a negative correlation to the angle of the knee relationship in a collision during.

Keywords: kinematics variables, the triple jump, the finale results, digital achievement

Procedia PDF Downloads 325

Authors: Ahmed Saeed, Sadok Sassi, Mohammad Roshun

Abstract:

Gears are important components with a vital role in many rotating machines. One of the common gear failure causes is tooth fatigue crack; however, its early detection is still a challenging task. The objective of this study is to develop a numerical model that simulates the effect of teeth cracks on the resulting gears vibrations and permits consequently to perform an early fault detection. In contrast to other published papers, this work incorporates the possibility of multiple simultaneous cracks with different depths. As cracks alter significantly the stiffness of the tooth, finite element software is used to determine the stiffness variation with respect to the angular position, for different combinations of crack orientation and depth. A simplified six degrees of freedom nonlinear lumped parameter model of a one-stage spur gear system is proposed to study the vibration with and without cracks. The model developed for calculating the stiffness with the crack permitted to update the physical parameters of the second-degree-of-freedom equations of motions describing the vibration of the gearbox. The vibration simulation results of the gearbox were by obtained using Simulink/Matlab. The effect of one crack with different levels was studied thoroughly. The change in the mesh stiffness and the vibration response were found to be consistent with previously published works. In addition, various statistical time domain parameters were considered. They showed different degrees of sensitivity toward the crack depth. Multiple cracks were also introduced at different locations and the vibration response along with the statistical parameters were obtained again for a general case of degradation (increase in crack depth, crack number and crack locations). It was found that although some parameters increase in value as the deterioration level increases, they show almost no change or even decrease when the number of cracks increases. Therefore, the use of any statistical parameters could be misleading if not considered in an appropriate way.

Keywords: Spur gear, cracked tooth, numerical simulation, time-domain parameters

Procedia PDF Downloads 265

Authors: Dongxu Chen, Yipeng Li

Abstract:

This paper presents an information geometry NonlocalMeans(NLM) algorithm for Poisson denoising. NLM estimates a noise-free pixel as a weighted average of image pixels, where each pixel is weighted according to the similarity between image patches in Euclidean space. In this work, every pixel is a Poisson distribution locally estimated by Maximum Likelihood (ML), all distributions consist of a statistical manifold. A NLM denoising algorithm is conducted on the statistical manifold where Fisher information matrix can be used for computing distribution geodesics referenced as the similarity between patches. This approach was demonstrated to be competitive with related state-of-the-art methods.

Keywords: image denoising, Poisson noise, information geometry, nonlocal-means

Procedia PDF Downloads 284