Search results for: survival data

Authors: Mamta Rajbhar, Sanjay K. Mohanty

Abstract:

India's progress in achieving replacement level of fertility is largely contingent on fertility reduction in the state of Uttar Pradesh as it accounts 17% of India's population with a low level of development. Though the TFR in the state has declined from 5.1 in 1991 to 3.4 by 2011, it conceals large differences in fertility level across districts. Using data from multiple sources this paper tests the hypothesis that the improvement in human development significantly reduces the fertility levels in districts of Uttar Pradesh. The unit of analyses is district, and fertility estimates are derived using the reverse survival method(RSM) while human development indices(HDI) are are estimated using uniform methodology adopted by UNDP for three period. The correlation and linear regression models are used to examine the relationship of fertility change and human development indices across districts. Result show the large variation and significant change in fertility level among the districts of Uttar Pradesh. During 1991-2011, eight districts had experienced a decline of TFR by 10-20%, 30 districts by 20-30% and 32 districts had experienced decline of more than 30%. On human development aspect, 17 districts recorded increase of more than 0.170 in HDI, 18 districts in the range of 0.150-0.170, 29 districts between 0.125-0.150 and six districts in the range of 0.1-0.125 during 1991-2011. Study shows significant negative relationship between HDI and TFR. HDI alone explains 70% variation in TFR. Also, the regression coefficient of TFR and HDI has become stronger over time; from -0.524 in 1991, -0.7477 by 2001 and -0.7181 by 2010. The regression analyses indicate that 0.1 point increase in HDI value will lead to 0.78 point decline in TFR. The HDI alone explains 70% variation in TFR. Improving the HDI will certainly reduce the fertility level in the districts.

Keywords: Fertility, HDI, Uttar Pradesh

Procedia PDF Downloads 253

Authors: Mei-Ling Chan, Jin-Ming Wu, Konstantin V. Kudryavtsev, Jih-Hwa Guh

Abstract:

Prostate cancer is one of the most common malignant disease in men. KUD983 is an enantiomerically pure β-dipeptide derivative, which may have anti-cancer effects. In the present study, KUD983 exhibits powerful activity against hormone-refractory prostate cancer (HRPC) PC-3 and DU145 cells. The IC50 values of KUD983 in PC-3 and DU145 cells are 0.56±0.07M and 0.50±0.04 M respectively. KUD983 induced G1 arrest of the cell cycle and subsequent apoptosis associated with the down-regulation of several related proteins including cyclin D1, cyclin E and Cdk4, and the de-phosphorylation of RB. The protein expressions of nuclear and total c-Myc protein, which was able to regulate the expression of both cyclin D1 and cyclin E, were significantly suppressed by KUD983. Phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) is an important signaling pathway that influences the energy metabolism, cell cycle, proliferation, survival and apoptosis of cells, and is associated with numerous other signaling pathways. The Western Blot data revealed that KUD983 inhibited PI3K/Akt and mTOR/p70S6K/4E-BP1 pathways. The transient transfection of constitutively active myristylated Akt (myr-Akt) cDNA significantly reversed KUD983-induced caspase activation but did not abolish the suppression of mTOR/p70S6K/4E-BP1 signaling cascade indicating the presence of both Akt-dependent and -independent pathways. Moreover, KUD983-induced effect was collaborated with the down-regulation of anti-apoptotic Bcl-2 members (e.g., Bcl-2, and Mcl-1) and IAP family members (e.g., survivin). Furthermore, KUD983 induced autophagic cell death using confocal microscopic examination, investigating the level of conversion of LC3-I to LC3-II and flow cytometric detection of AVO-positive cells. Taken together, the data suggest that KUD983 is an anticancer β-dipeptide against HRPCs through the inhibition of cell proliferation and induction of apoptotic and autophagic cell death. The suppression of signaling pathways mediated by c-Myc, PI3K/Akt and mTOR/p70S6K/4E-BP1 and the collaboration with down-regulation of Mcl-1 and survivin may indicate the mechanism of KUD983 against HRPC.

Keywords: β-dipeptide, hormone-refractory prostate cancer, mTOR, PI3K/Akt

Procedia PDF Downloads 286

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

Abstract:

Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

Procedia PDF Downloads 89

Authors: A. Kolendo

Abstract:

Pacific Islands are one of the most vulnerable areas to climate change. Sea level rise and accelerating storm surge continuously threaten the communities' habitats on low-lying atolls. With scientific predictions of encroaching tides on their land, the Islanders have been informed about the need for future relocation planning. However, some communities oppose such retreat strategies through the reasoning that comprehends current climatic changes through the lenses of the biblical ark of Noah. This parable states God's promise never to flood the Earth again and never deprive people of their land and habitats. Several interpretations of this parable emerged in Oceania, prompting either climate action or denial. Resistance to relocation planning expressed through Christian thoughts led religion to be perceived as a barrier to dialogue between the Islanders and scientists. Since climate change concerns natural processes, the attitudes towards environmental stewardship prompt the communities' responses to it; some Christian teachings indicate humanity's responsibility over the environment, whereas others ascertain the people's dominion, which prompts resistance and sometimes denial. With church denominations and their various environmental standpoints, competing responses to climate change emerged in Oceania. Before miss-ionization, traditional knowledge had guided the environmental sphere, influencing current Christian teachings. Each atoll characterizes a distinctive manner of traditional knowledge; however, the unique relationship with nature unites all islands. The interconnectedness between the land, sea and people indicates the integrity between the communities and their environments. Such a factor influences the comprehension of Noah's story in the context of climate change that threatens their habitats. Pacific Islanders experience climate change through the slow disappearance of their homelands. However, the Western world perceives it as a global issue that will affect the population in the long-term perspective. Therefore, the Islanders seek to comprehend this global phenomenon in a local context that reads climate change as the Great Deluge. Accordingly, the safety measures that this parable promotes compensate for the danger of climate change. The rainbow covenant gives hope in God's promise never to flood the Earth again. At the same time, Noah's survival relates to the Islanders' current situation. Since these communities have the lowest carbon emissions rate, their contribution to anthropogenic climate change is scarce. Therefore, the lack of environmental sin would contextualize them as contemporary Noah with the ultimate survival of sea level rise. This study aims to defy religion constituting a barrier through secondary data analysis from a risk compensation perspective. Instead, religion is portrayed as a source of knowledge that enables comprehension of the communities' situation. By demonstrating that the Pacific Islanders utilize Noah's story as a vessel for coping with the danger of climate change, the study argues that religion provides safety measures that compensate for the future projections of land's disappearance. The purpose is to build a bridge between religious communities and scientific bodies and ultimately bring an understanding of two diverse perspectives. By addressing the practical challenges of interdisciplinary research with faith-based systems, this study uplifts the voices of communities and portrays their experiences expressed through Christian thoughts.

Keywords: Christianity, climate change, existential threat, Pacific Islands, story of Noah

Procedia PDF Downloads 100

Authors: Hatem Radwan Ibrahim Radwan

Abstract:

Leadership is crucial for hotel survival and success. It enables hotels to develop and compete effectively. This research intends to explore the implementation of six leadership styles by frontline hotel managers in four star hotels in Cairo and assess its impact on employees’ creativity and organizational commitment. The leadership patterns considered in this study includes: democratic, autocratic, laissez-faire, transformational, transactional, and ethical leaderships. Questionnaire was used as a research method to gather data. A structured survey was established and distributed on employees in Cairo’s four star hotels. A total of 284 questionnaire forms were returned and usable for statistical analysis. The results of this study identified that transactional and autocratic leadership were the prevalent styles used in four star hotels in Cairo. Two leadership styles proved to have significant high correlation and impact on employees’ creativity and organizational commitment including: transformational and democratic leadership. Besides, laissez-faire leadership was found had a smaller effect on employees’ creativity and ethical leadership had a lesser influence on employees’ commitment. The autocratic leadership had strong negative correlation and significant impact on both dependent variables. This research concludes that frontline hotel managers should adopt transformational and/or democratic leadership style in managing their subordinates.

Keywords: creativity, hotels, leadership styles, organizational commitment

Procedia PDF Downloads 150

Authors: Hakan Duger, Alparslan Ersoy, Canan Ersoy

Abstract:

The improvement of surgical techniques in recent years has reduced the frequency of postoperative complications in kidney transplant recipients. Novel immunosuppressive agents have reduced rates of graft loss due to acute rejection to less than 1%. However, surgical complications may still lead graft loss and morbidity in recipients. Because of potent immunosuppression, impaired wound healing and complications are frequent after transplantation. We compared the frequency of post-operative surgical complications in diabetic and non-diabetic patients after kidney transplantation. Materials and Methods: This retrospective study conducted in consecutive patients (213 females, 285 males, median age 39 years) who underwent kidney transplant surgery at our center between December 2005 and October 2015. The patients were divided into two groups: diabetics (46 ± 10 year, 26 males, 16 females) and non-diabetics (39 ± 12 year, 259 males, 197 females). Characteristics of both groups were obtained from medical records. Results: We performed 225 living and 273 deceased donor transplantations. Renal replacement type was hemodialysis in 60.8%, peritoneal dialysis in 17.3% and preemptive in 12%. The mean body mass indexes of the recipients were 24 ± 4.6 kg/m², donor age was 48.6 ± 14.3 years, cold ischemic time was 11.3 ± 6.1 hours, surgery time was 4.9 ± 1.2 hours, and recovery time was 54±31 min. The mean hospitalization duration was 19.1 ± 13.5 days. The frequency of postoperative surgical complications was 43.8%. There was no significant difference between the ratios of post-operative surgical complications in non-diabetic (43.5%) and diabetic (47.4%) groups (p=0.648). Post-operative surgical complications were lymphocele (24.6% vs. 23.7%), delayed wound healing (13.2% vs. 7.6%), hematoma (7.8% vs.15.8 %), urinary leak (4.6% vs. 5.3%), hemorrhage (5.1% vs. 0%), hydronephrosis (2.2% vs. 0%), renal artery thrombosis (1.5% vs. 0%), renal vein thrombosis (1% vs. 2.6%), urinoma (0.7% vs. 0%), urinary obstruction (0.5% vs. 0%), ureteral stenosis (0.5% vs. 0%) and ureteral reflux (0.2% vs. 0%) in non-diabetic and diabetic groups, respectively (p > 0.05). Mean serum creatinine levels in non-diabetics and diabetics were 1.43 ± 0.81 and 1.61 ± 0.96 mg/dL at 1st month (p=0.198). At the 6th month, the mean graft and patient survival times in patients with post-operative surgical complications were significantly lower than in those who did not (162.9 ± 3.4 vs. 175.6 ± 1.5 days, p=0.008, and 171 ± 2.9 vs. 176.1 ± 1.6 days, p=0.047, respectively). However, patient survival durations of non-diabetic (173 ± 27) and diabetic (177 ± 13 day) groups were comparable (p=0.396). Conclusion: As a result, we concluded that surgical complications such as lymphocele and delayed wound healing were common and that frequency of these complications in diabetic recipients did not differ from non-diabetic one. All persons involved in the postoperative care of kidney transplant recipients be aware of the potential surgical complications for rapid diagnosis and treatment.

Keywords: kidney transplantation, diabetes mellitus, surgery, complication

Procedia PDF Downloads 181

Authors: Djamila Benhaddouche, Abdelkader Benyettou

Abstract:

In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

Procedia PDF Downloads 564

Authors: Usama Ahmed

Abstract:

Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

Procedia PDF Downloads 152

Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

Abstract:

Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

Procedia PDF Downloads 88

Authors: Yaser Ghasemi Aryan, Firoozeh Moghiminejad, Mohammadreza Shahraki

Abstract:

Background: The cooperative institution is considered the first and most essential pillar of strengthening social capital, whose sustainability is the main guarantee of survival and continued participation of local communities in natural resource management projects. The Village Development Group and the Microcredit Fund are two important social and economic institutions in the implementation of the International Project for the Restoration of Degraded Forest Lands (RFLDL) in Sarayan City, South Khorasan Province, which has learned positive lessons from the participation of the beneficiaries in the implementation. They have brought more effective projects to deal with desertification. However, the low activity or liquidation of some of these institutions has become one of the important challenges and concerns of project executive experts. The current research was carried out with the aim of explaining the main components of the instability of these institutions. Materials and Methods: This research is descriptive-analytical in terms of method, practical in terms of purpose, and the method of collecting information is two documentary and survey methods. The statistical population of the research included all the members of the village development groups and microcredit funds in the target villages of the RFLDL project of Sarayan city, based on the Kochran formula and matching with the Karjesi and Morgan table. Net people were selected as a statistical sample. After confirming the validity of the expert's opinions, the reliability of the questionnaire was 0.83, which shows the appropriate reliability of the researcher-made questionnaire. Data analysis was done using SPSS software. Results: The results related to the extraction of obstacles to the stability of social and economic networks were classified and prioritized in the form of 5 groups of social-cultural, economic, administrative, educational-promotional and policy-management factors. Based on this, in the socio-cultural factors, the items ‘not paying attention to the structural characteristics and composition of groups’, ‘lack of commitment and moral responsibility in some members of the group,’ and ‘lack of a clear pattern for the preservation and survival of groups’, in the disciplinary factors, The items ‘Irregularity in holding group meetings’ and ‘Irregularity of members to participate in meetings’, in the economic factors of the items "small financial capital of the fund’, ‘the low amount of loans of the fund’ and ‘the fund's inability to conclude contracts and attract capital from other sources’, in the educational-promotional factors of the items ‘non-simultaneity of job training with the granting of loans to create jobs’ and ‘insufficient training for the effective use of loans and job creation’ and in the policy-management factors of the item ‘failure to provide government facilities for support From the funds, they had the highest priority. Conclusion: In general, the results of this research show that policy-management factors and social factors, especially the structure and composition of social and economic institutions, are the most important obstacles to their sustainability. Therefore, it is suggested to form cooperative institutions based on network analysis studies in order to achieve the appropriate composition of members.

Keywords: cooperative institution, social capital, network analysis, participation, Sarayan.

Procedia PDF Downloads 61

Authors: Jeongyeob Hong, Myeonghoon Park, Taeson Yoon

Abstract:

After the advent of Achaeans which utilize different metabolism pathway and contain conspicuously different cellular structure, they have been recognized as possible materials for developing quality of human beings. Among diverse Achaeans, in this paper, we compared 16s RNA Sequences of four different species of Thermococcus: Achaeans genus specialized in sulfur-dealing metabolism. Four Species, Barophilus, Kodakarensis, Hydrothermalis, and Onnurineus, live near the hydrothermal vent that emits extreme amount of sulfur and heat. By comparing ribosomal sequences of aforementioned four species, we found similarities in their sequences and expressed protein, enabling us to expect that certain ribosomal sequence or proteins are vital for their survival. Apriori algorithms and Decision Tree were used. for comparison.

Keywords: Achaeans, Thermococcus, apriori algorithm, decision tree

Procedia PDF Downloads 293

Authors: Lukman Abiodun Nafiu

Abstract:

This study examines the impact evaluation of vaccination against eight-child-killer diseases on under-five children mortality at Mbale District. It was driven by three specific objectives which are to determine the proportion of under-five children mortality due to the eight-child-killer diseases to the total under-five children mortality; establish the cause-effect relationship between the eight-child-killer diseases and under-five children mortality; as well as establish the dependence of under-five children mortality in the location at Mbale District. A community based cross-sectional and longitudinal (panel) study design involving both quantitative and qualitative (focus group discussion and in-depth interview) approaches was employed over a period of 36 months. Multi-stage cluster design involving Health Sub-District (HSD), Forms of Ownership (FOO) and Health Facilities Centres (HFC) as the first, second and third stages respectively was used. Data was collected regarding the eight-child-killer diseases namely: measles, pneumonia, pertussis (whooping cough), diphtheria, poliomyelitis (polio), tetanus, haemophilus influenza, rotavirus gastroenteritis and mortality regarding immunized and non-immunized children aged 0-59 months. We monitored the children over a period of 24 months. The study used a sample of 384 children out of all the registered children for each year at Mbale Referral Hospital and other Primary Health Care Centres (HCIV, HCIII and HCII) at Mbale District between 2015 and 2019. These children were followed from birth to their current state (living or dead). The data collected in this study was analysed using cross tabulation and the chi-square test. The study concluded that majority of mothers at Mbale district took their children for immunization and thus reducing the occurrence of under-five children mortality. Overall, 2.3%, 4.6%, 3.1%, 5.4%, 1.5%, 3.8%, 0.0% and 0.0% of under-five children had polio, tetanus, diphtheria, measles, pertussis, pneumonia, haemophilus influenzae and rotavirus gastroenteritis respectively across all the sub counties at Mbale district during the period considered. Also, different locations (sub counties) do not have significant influence on the occurrence of these eight-child-killer diseases among the under-five children at Mbale district. Therefore, the study recommended that government and agencies should continue to work together to implement measures of vaccination programs and increasing access to basic health care with a continuous improvement on the social interventions to progress child survival.

Keywords: Diseases, Mortality, Children, Vaccination

Procedia PDF Downloads 127

Authors: Maier Dorin, Maier Andreea

Abstract:

Today, any organization - regardless of the specific activity - must be prepared to face continuous radical changes, innovation thus becoming a condition of survival in a globalized market. Not all managers have an overall view on the real size of necessary innovation potential. Unfortunately there is still no common (and correct) understanding of the term of innovation among managers. Moreover, not all managers are aware of the need for innovation. This article highlights and analyzes a series of models of innovation processes and their evolution. The models analyzed encompass both the strategic level and the operational one within an organization, indicating performance innovation on each landing. As the literature review shows, there are no easy answers to the innovation process as there are no shortcuts to great results. Successful companies do not have a silver innovative bullet - they do not get results by making one or few things better than others, they make everything better.

Keywords: innovation, innovation process, business success, models of innovation

Procedia PDF Downloads 407

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

Procedia PDF Downloads 279

Authors: Christopher Muhawe, Masooda Bashir

Abstract:

With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

Procedia PDF Downloads 201

Authors: Al-Saboonchi Azhar

Abstract:

The effects of Iraqi crude oil on growth of three freshwater algae (Chlorella vulgaris Beij., Scenedesmus acuminatus (Lag.) Chodat. and Oscillatoria princeps Vauch.) were investigated, basing on it's biomass expressed as Chl.a. Growth rate and doubling time of the cell were calculated. Results showed that growth rate and species survival varied with concentrations of crude oil and species type. Chlorella vulgaris and Scenedesmus acuminatus were more sensitive in culture containing crude oil as compared with Oscillatoria princeps cultures. The growth of green algae were significantly inhibited in culture containing (5 mg/l) crude oil, while the growth of Oscillatoria princeps reduced in culture containing (10 mg/l) crude oil.

Keywords: algae, crude oil, green algae, Cyanobacteria

Procedia PDF Downloads 563

Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

Abstract:

This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

Procedia PDF Downloads 46

Authors: Mandisi Matyana

Abstract:

Although the South African local government is doing all the best in ensuring improved service delivery for the citizens, service delivery disparity still remains the real challenge for other municipalities. The unequal distribution of services within municipal wards is causing unequal happiness among the citizens; hence others do enjoy different provided municipal services, while others do not. It is acknowledged that less access to municipal services infringes one’s rights, such as the right to human dignity and the right to life. Some of the municipal services are basic services and they are the mainstay of human survival, such as water, housing, etc. It is quite evident that the service delivery disparity could be caused by the various factors within the local municipality affairs, including both administrative and political factors. Therefore, this study is undertaken to check and evaluate the main foundations of service delivery disparity in ensuring equal development of the state, particularly for local communities. The study used the qualitative method to collect the data from the citizens of Winnie Madikizela Mandela Local Municipality. An extensive literature was also conducted in understanding the causes of service delivery disparity. Study findings prove that the service delivery disparity could be caused by factors such as political interference in administration, corruption and fraud, elevated unemployment levels, inadequate institutional capacity, etc. Therefore, the study recommends strong community participation and constant external supervision in the local government so as to encourage openness in local government to ensure fair administration towards services to be provided.

Keywords: administration, development, municipal services, service delivery disparity, Winnie Madikizela Mandela local municipality

Procedia PDF Downloads 114

Authors: Chuping Lo

Abstract:

This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

Procedia PDF Downloads 71

Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

Abstract:

Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

Procedia PDF Downloads 415

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 260

Authors: P. Uma Devi, S. Sujith, K. Rahul, T. S. Dipu, V. Anil Kumar , Vidya Menon

Abstract:

Introduction: Candida is an important cause of bloodstream infections (BSIs), causing significant mortality and morbidity. The epidemiology of Candida infection is also changing, mainly in relation to the number of episodes caused by species Candida non-albicans. However, in India, the true burden of candidemia is not clear. Thus, this study was conducted to evaluate the clinical characteristics, species distribution, antifungal susceptibility and outcome of candidemia at our hospital. Methodology: Between January 2012 and April 2014, adult patients with at least one positive blood culture for Candida species were identified through the microbiology laboratory database (for each patient only the first episode of candidemia was recorded). Patient data was collected by retrospective chart review of clinical characteristics including demographic data, risk factors; species distribution, resistance to antifungals and survival. Results: A total of 165 episodes of Candida BSI were identified, with 115 episodes occurring in adult patients. Most of the episodes occurred in males (69.6%). Nearly 82.6% patients were between 41 to 80 years and majority of the patients were in the intensive care unit (65.2%) at the time of diagnosis. On admission, 26.1% and 18.3% patients had pneumonia and urinary tract infection, respectively. Majority of the candidemia episodes were found in the general medicine department (23.5%) followed by gastrointestinal surgery (13.9%) and medical oncology & haematology (13%). Risk factors identified were prior hospitalization within one year (83.5%), antibiotic therapy within the last one month (64.3%), indwelling urinary catheter (63.5%), central venous catheter use (59.1%), diabetes mellitus (53%), severe sepsis (45.2%), mechanical ventilation (43.5%) and surgery (36.5%). C. tropicalis (30.4%) was the leading cause of infection followed by C. parapsilosis (28.7%) and C. albicans (13%). Other non-albicans species isolated included C. haemulonii (7.8%), C. glabrata (7%), C. famata (4.3%) and C. krusei (1.7%). Antifungal susceptibility to fluconazole was 87.9% (C. parapsilosis), 100% (C. tropicalis) and 93.3% (C. albicans). Mortality was noted in 51 patients (44.3%). Early mortality (within 7 days) was noted in 32 patients while late mortality (between 7 and 30 days) was noted in 19 patients. Conclusion: In recent years, candidemia has been flourishing in critically ill patients. Comparison of data from our own hospital from 2005 shows a doubling of the incidence. Rapid changes in the rate of infection, potential risk factors, and emergence of non-albicans Candida demand continued surveillance of this serious BSI. High index of suspicion and sensitive diagnostics are essential to improve outcomes in resource limited settings with emergence of non-albicans Candida.

Keywords: antifungal susceptibility, candida albicans, candidemia, non-albicans candida

Procedia PDF Downloads 459

Authors: R Palson Kennedy, P.Kiran Sai

Abstract:

This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

Procedia PDF Downloads 140

Authors: Nita Rukminasari

Abstract:

The aim of this study is to select microalgae strains, which were isolated from agriculture and municipal wastewater drain, Reno, Nevada that has highest growth rate and lipid contents. The experiments in this study were carried out in two consecutive stages. The first stage is aimed at testing the survival capability of all isolated microalgae strains and determining the best candidates to grow in centrate cultivation system. The second stage was targeted at determination the highest growth rate and highest lipid content of the selected top performing algae strain when cultivated on centrate wastewater. 26 microalgae strains, which were isolated from municipal and agriculture waste water, were analyzed using Flow cytometer for FACS of lipid with BODIPY and Nile Red as a lipid dyes and they grew on 96 wells plate for 31 days to determine growth rate as a based line data for growth rate. The result showed that microalgae strains which showed a high mean of fluorescence for BODIPY and Nile Red were F3.BP.1, F3.LV.1, T1.3.1, and T1.3.3. Five microalgae strains which have high growth rate were T1.3.3, T2.4.1. F3.LV.1, T2.12.1 and T3.3.1. In conclusion, microalgae strain which showed the highest starch content was F3.LV.1. T1.3.1 had the highest mean of fluorescence for Nile Red and BODIPY. Microalgae strains were potential for biofuel feedstock such as F3.LV.1 and T1.3.1, those microalgae strains showed a positive correlation between growth rate at stationary phase, biomass and meant of fluorescence for Nile Red and BODIPY.

Keywords: agriculture and municipal wastewater, biofuel, centrate, microalgae

Procedia PDF Downloads 321

Authors: Teklebrhan Kidane

Abstract:

The aim of this study is to investigate the species diversity and relative abundance of migratory waterbirds in Abijata Lake, an Important Bird Area and potential Ramsar site located in the Central Rift Valley of Ethiopia. The study was carried out, using line transect method along the shoreline and open area of the Lake. The data was analyzed with different diversity indices; t-Test and descriptive statistics. Thirty-two migratory waterbird species grouped into twelve families consisting of globally threatened birds were identified and recorded. Family Scolopacidae (12 species) had the highest number of species. The lowest number of species was observed under the families Ciconidae, Accipitridae, Laridae and Falconidae with one species each. The recorded bird species comprised 19 Palearctic, 5 Intra-African, 2 local migrants as well as 6 resident Palearctic migratory waterbird species. The dry season had higher species diversity (H'=1.01) compared to the wet season (H'=0.76). The highest and lowest diversity of migratory waterbirds were recorded during January (H'= 1.28) and June (H'= 0.52), respectively. However, the highest evenness (E) of bird species was recorded during wet season (E=0.21) and lower during the dry season (E=0.09). The computed seasonal effect reveals that there is significant effect of seasons on species diversity (t=2.80, P < 0.05), but the effect of seasons on individuals of migratory bird species was not significant (t=1.42, P > 0.05). Even though Lake Abijata is the sanctuary of several migratory waterbirds, anthropogenic activities are rigorously threatening their survival. Therefore, it needs an urgent conservation concern.

Keywords: migration, important bird area, species diversity, wetland birds

Procedia PDF Downloads 211

Authors: Anjum-Zubair, Muhammad, Muhammad Shoaib Alam, Muhammad Samee Mubarik, Iftikhar Ahmad

Abstract:

The aim of present research was to evaluate the effect of dietary protein (soybean) formulated feed on the growth performance of carp fish seed (Rohu, Mori, Grass, and Gulfam) in ponds under polyculture system. Keeping in view the protein requirements of these four carps, they were fed with formulated feed contains 30% of crude protein. The fingerlings were fed once on daily basis at 5% of their wet body weight. A 90 days experiment was conducted in two cemented ponds situated at Fish Seed Hatchery and Research Centre, Rawal Town, Islamabad, Pakistan. Pond1 contain major carps i.e. Rohu and Mori while pond 2 was stocked with Chinese carps i.e. Grass carp and Gulfam. Random sampling of five individuals of each species was done fortnightly to measure the body weight and total body length. Maximum growth was observed in fingerling of Grass carp followed by Mori, Rohu and Gulfam. Total fish production was recorded as Grass 623.45 gm followed by Mori 260.3 gm, Rohu 243.08 gm and Gulfam 181.165 gm respectively. Significantly results were obtained among these four fish species when the corresponding data was subjected to statistical analysis by using two sample t-test. The survival rate was 100%. Study shows that soybean as plant based protein can be easily used as substitute to fish meal without any adverse effect on fish health and fish production.

Keywords: carps, fry growth, poly culture, soybean meal

Procedia PDF Downloads 501

Authors: Mehrnoosh Askarizadeh

Abstract:

To meet the challenges of the new global environment, companies have started paying great attention towards quality management as an integral part of their strategic business plans. The purpose of this article is to investigate the relationship between total quality management (TQM) and knowledge management (KM). Successful total quality management implementation throughout the organizations requires major changes in the main four aspects of knowledge management, namely: Creating, storage, sharing and application. Skill, knowledge and productivity are important factors in organization’s success and have important role. Therefore, TQM management system pays special attention to it. However, knowledge as the source is essential for organization’s survival. Our study points out how the quality management and knowledge management have been incorporated into each other for the development of the quality culture within the organization.

Keywords: knowledge management (KM), total quality management (TQM), organizational performance (OP), deming cycle

Procedia PDF Downloads 485

Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

Abstract:

Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

Procedia PDF Downloads 140

Authors: Ryan Kelvin Ford

Abstract:

For individuals and organizations, significant potential benefits were assured by sharing the data in a secure, trusted, and standardized environment. Technical trust and standards help each participant to use data space securely to share and access data. Sharing data in a safe environment helps acquire new business opportunities. Data sovereignty, interoperability, and trust were considered key factors to evaluate data spaces. Businesses and policymakers assure a fair data economy by integrating data space in organizations. A collaborative environment was needed to facilitate data sharing among organizations, satisfied with the implementation of different architectures using data spaces such as Eclipse Data Space Components (EDC), International Data Space Association (IDSA), Gaia-X, and Gaia-X Federation Services (GXFS). The last 15 years of application were reviewed and compared based on the architectures and implementations of different data spaces such as IDSA, EDC, Gaia-X and GXFS, EDC framework, IDSA, GXFS, data connector, data space architecture, characteristics of data space connectors, federated data spaces initiatives, data spaces overview, eclipse data space connector, designing data spaces, building data spaces based on technical overview, European future digital ecosystem based on Gaia-Vision and strategy of Gaia-Architecture. Empirical research based on an organized view was conducted. The current discussion elaborates on the systematic review of the impact of data space technology from various perspectives. The systematic review uses multiple databases such as IEEE Explore, Taylor & Francis, Science Direct, and Google Scholar to pursue publications on the impact of Data space from January 2019 to December 2024. The search results showcased a comparative review of 150 articles, out of which 20 were related to the IDSA, Gaia‑X, and EDC architecture and implementation.

Keywords: IDSA, Gaia-X, Gaia-X architecture, EDC, EDC architecture, GXFS architecture, IDSA, data space connector

Procedia PDF Downloads 10

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

Procedia PDF Downloads 440