Search results for: logistic costs
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3027

Search results for: logistic costs

2907 An Analysis of Classification of Imbalanced Datasets by Using Synthetic Minority Over-Sampling Technique

Authors: Ghada A. Alfattni

Abstract:

Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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2906 Comparing Performance Indicators among Mechanistic, Organic, and Bureaucratic Organizations

Authors: Benchamat Laksaniyanon, Padcharee Phasuk, Rungtawan Boonphanakan

Abstract:

With globalization, organizations had to adjust to an unstable environment in order to survive in a competitive arena. Typically within the field of management, different types of organizations include mechanistic, bureaucratic and organic ones. In fact, bureaucratic and mechanistic organizations have some characteristics in common. Bureaucracy is one type of Thailand organization which adapted from mechanistic concept to develop an organization that is suitable for the characteristic and culture of Thailand. The objective of this study is to compare the adjustment strategies of both organizations in order to find key performance indicators (KPI) suitable for improving organization in Thailand. The methodology employed is binary logistic regression. The results of this study will be valuable for developing future management strategies for both bureaucratic and mechanistic organizations.

Keywords: mechanistic, bureaucratic and organic organization, binary logistic regression, key performance indicators (KPI)

Procedia PDF Downloads 359
2905 Algorithm for Recognizing Trees along Power Grid Using Multispectral Imagery

Authors: C. Hamamura, V. Gialluca

Abstract:

Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

Procedia PDF Downloads 499
2904 The Labor Participation–Fertility Trade-off: The Case of the Philippines

Authors: Daphne Ashley Sze, Kenneth Santos, Ariane Gabrielle Lim

Abstract:

As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences.

Keywords: multinomial logistic function, tobit, fertility, women employment status, fecundity

Procedia PDF Downloads 606
2903 Paraoxonase 1 (PON 1) Arylesterase Activity and Apolipoprotein B: Predictors of Myocardial Infarction

Authors: Mukund Ramchandra Mogarekar, Pankaj Kumar, Shraddha Vilas More

Abstract:

Background: Myocardial infarction (MI) is defined as myocardial cell death due to prolonged ischemia as a consequence of atherosclerosis. TC, low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol (VLDL-C), Apo B, and lipoprotein(a) was found as atherogenic factors while high-density lipoprotein cholesterol (HDL-C) was anti-atherogenic. Methods and Results: The study group consists of 40, MI subjects and 40 healthy individuals in control group. PON 1 Arylesterase activity (ARE) was measured by using phenylacetate. Phenotyping was done by double substrate method, serum AOPP by using chloramine T and Apo B by Turbidimetric immunoassay. PON 1 ARE activities were significantly lower (p< 0.05) and AOPPs & Apo B were higher in MI subjects (p> 0.05). Trimodal distribution of QQ, QR, and RR phenotypes of study population showed no significant difference among cases and controls (p> 0.05). Univariate binary logistic regression analysis showed independent association of TC, HDL, LDL, AOPP, Apo B, and PON 1 ARE activity with MI and multiple forward binary logistic regression showed PON 1 ARE activity and serum Apo B as an independent predictor of MI. Conclusions: Decrease in PON 1 ARE activity in MI subjects than in controls suggests increased oxidative stress in MI which is reflected by significantly increased AOPP and Apo B. PON1 polymorphism of QQ, QR and RR showed no significant difference in protection against MI. Univariate and multiple binary logistic regression showed PON1 ARE activity and serum Apo B as an independent predictor of MI.

Keywords: advanced oxidation protein product, apolipoprotein B, PON 1 arylesterase activity, myocardial infarction

Procedia PDF Downloads 265
2902 The Labor Participation-Fertility Trade-Off: Exploring Fecundity and Its Consequences to Women's Employment in the Philippines

Authors: Ariane C. Lim, Daphne Ashley L. Sze, Kenneth S. Santos

Abstract:

As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child-rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences.

Keywords: multinomial logistic function, tobit, fertility, women employment status, fecundity

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2901 Political Determinants of Sovereign Spread: The Great East-West Divide

Authors: Maruska Vizek, Josip Glaurdic, Marina Tkalec, Goran Vuksic

Abstract:

We empirically explore whether and how taxation affects bilateral real exchange rates in the euro area – relative unit labor costs and relative consumer price indices. We find that employers’ social security contributions and the value added tax changes have the expected effects put forward in the fiscal devaluation literature and simulations. Increases in employers’ contributions appreciate the relative unit labor costs in the short- and the long-run, while value added tax hike appreciates the relative consumer prices. Somewhat surprisingly, for personal income tax increases, we find a short-run depreciating impact on the relative unit labor costs, while increases in employees’ contributions depreciate both measures of real exchange rates in the short-run.

Keywords: sovereign bonds, European Union, developing countries, political determinants

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2900 An Optimal Algorithm for Finding (R, Q) Policy in a Price-Dependent Order Quantity Inventory System with Soft Budget Constraint

Authors: S. Hamid Mirmohammadi, Shahrazad Tamjidzad

Abstract:

This paper is concerned with the single-item continuous review inventory system in which demand is stochastic and discrete. The budget consumed for purchasing the ordered items is not restricted but it incurs extra cost when exceeding specific value. The unit purchasing price depends on the quantity ordered under the all-units discounts cost structure. In many actual systems, the budget as a resource which is occupied by the purchased items is limited and the system is able to confront the resource shortage by charging more costs. Thus, considering the resource shortage costs as a part of system costs, especially when the amount of resource occupied by the purchased item is influenced by quantity discounts, is well motivated by practical concerns. In this paper, an optimization problem is formulated for finding the optimal (R, Q) policy, when the system is influenced by the budget limitation and a discount pricing simultaneously. Properties of the cost function are investigated and then an algorithm based on a one-dimensional search procedure is proposed for finding an optimal (R, Q) policy which minimizes the expected system costs .

Keywords: (R, Q) policy, stochastic demand, backorders, limited resource, quantity discounts

Procedia PDF Downloads 641
2899 Covid-19 Pandemic: Another Lesson Learned by a Military Hospital

Authors: Mariana Floria, Elena-Diana Năfureanu, Diana-Mihaela Gălăţanu, Anca-Ecaterina Grumeza, Cristina Gorea-Bocîncă, Diana-Elena Iov, Aurelian-Corneliu Moraru, Dragoș-Marian Popescu

Abstract:

SARS-CoV-2 is the most deadly and devastating virus of the last one hundred years, being more highly contagious than EBOLA, HIV, Swine Influenza, Severe Acute Respiratory Syndrome, or Middle Eastern Respiratory Syndrome. After two years of pandemic, planning and budgeting for use of healthcare resources and services is very important. The aim of this study was to analyze the costs for hospital stay in patients with predominantly moderate forms of COVID-19 in a support military hospital located in Nord-East of Romania. Inpatient COVID-19 hospitalizations costs, regardless of ICD-10 procedure codes (DRG payment), in a Covid-19 support military hospital were analyzed. From August 2020 through June 2021, 241 patientswere hospitalized. Our national protocol for the treatment of Covid-19 infection was applied. The main COVID-19 manifestations were: 69% respiratory (18% with severe pneumonia, 2.9% with pulmonary embolism, diagnosed by angio-computed tomography), 3.3% cardiac, 28% digestive, and 33% psychiatric (most common anxiety) manifestations. According to COVID-19 severity, most of the patients had moderate (104 patients – 43%) and severe (50 patients - 21%) forms. Seven patients with severe form died because of multiple comorbidities, and 30 patients were transferred in hospitals with COVID-19 intensive care units.Only two patients have had procalcitonin>10 ng/mL (high probability of severe sepsis or septic shock), and 1 patient had moderate risk for septic shock (0.5 - 2 ng/mL). The average estimated costs were about 3000€/patient, without significantly differences depending on disease severity. Equipment costs were 2 times higher than for drugs and 4 times than for laboratory tests. In a Covid-19 support military hospital that took care for predominantly moderate forms of COVID-19, the costs for equipment were much higher than that for treatment. Therefore, new criteria for hospitalization of these forms of COVID-19 deserve to be analyzed to avoid useless costs.

Keywords: Covid-19, costs, hospital stay, military hospital

Procedia PDF Downloads 178
2898 Healthcare Utilization and Costs of Specific Obesity Related Health Conditions in Alberta, Canada

Authors: Sonia Butalia, Huong Luu, Alexis Guigue, Karen J. B. Martins, Khanh Vu, Scott W. Klarenbach

Abstract:

Obesity-related health conditions impose a substantial economic burden on payers due to increased healthcare use. Estimates of healthcare resource use and costs associated with obesity-related comorbidities are needed to inform policies and interventions targeting these conditions. Methods: Adults living with obesity were identified (a procedure-related body mass index code for class 2/3 obesity between 2012 and 2019 in Alberta, Canada; excluding those with bariatric surgery), and outcomes were compared over 1-year (2019/2020) between those who had and did not have specific obesity-related comorbidities. The probability of using a healthcare service (based on the odds ratio of a zero [OR-zero] cost) was compared; 95% confidence intervals (CI) were reported. Logistic regression and a generalized linear model with log link and gamma distribution were used for total healthcare cost comparisons ($CDN); cost ratios and estimated cost differences (95% CI) were reported. Potential socio-demographic and clinical confounders were adjusted for, and incremental cost differences were representative of a referent case. Results: A total of 220,190 adults living with obesity were included; 44% had hypertension, 25% had osteoarthritis, 24% had type-2 diabetes, 17% had cardiovascular disease, 12% had insulin resistance, 9% had chronic back pain, and 4% of females had polycystic ovarian syndrome (PCOS). The probability of hospitalization, ED visit, and ambulatory care was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (hospitalization: 1.8-times [OR-zero: 0.57 [0.55/0.59]] / ED visit: 1.9-times [OR-zero: 0.54 [0.53/0.56]] / ambulatory care visit: 2.4-times [OR-zero: 0.41 [0.40/0.43]]), cardiovascular disease (2.7-times [OR-zero: 0.37 [0.36/0.38]] / 1.9-times [OR-zero: 0.52 [0.51/0.53]] / 2.8-times [OR-zero: 0.36 [0.35/0.36]]), osteoarthritis (2.0-times [OR-zero: 0.51 [0.50/0.53]] / 1.4-times [OR-zero: 0.74 [0.73/0.76]] / 2.5-times [OR-zero: 0.40 [0.40/0.41]]), type-2 diabetes (1.9-times [OR-zero: 0.54 [0.52/0.55]] / 1.4-times [OR-zero: 0.72 [0.70/0.73]] / 2.1-times [OR-zero: 0.47 [0.46/0.47]]), hypertension (1.8-times [OR-zero: 0.56 [0.54/0.57]] / 1.3-times [OR-zero: 0.79 [0.77/0.80]] / 2.2-times [OR-zero: 0.46 [0.45/0.47]]), PCOS (not significant / 1.2-times [OR-zero: 0.83 [0.79/0.88]] / not significant), and insulin resistance (1.1-times [OR-zero: 0.88 [0.84/0.91]] / 1.1-times [OR-zero: 0.92 [0.89/0.94]] / 1.8-times [OR-zero: 0.56 [0.54/0.57]]). After fully adjusting for potential confounders, the total healthcare cost ratio was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (1.54-times [1.51/1.56]), cardiovascular disease (1.45-times [1.43/1.47]), osteoarthritis (1.36-times [1.35/1.38]), type-2 diabetes (1.30-times [1.28/1.31]), hypertension (1.27-times [1.26/1.28]), PCOS (1.08-times [1.05/1.11]), and insulin resistance (1.03-times [1.01/1.04]). Conclusions: Adults with obesity who have specific disease-related health conditions have a higher probability of healthcare use and incur greater costs than those without specific comorbidities; incremental costs are larger when other obesity-related health conditions are not adjusted for. In a specific referent case, hypertension was costliest (44% had this condition with an additional annual cost of $715 [$678/$753]). If these findings hold for the Canadian population, hypertension in persons with obesity represents an estimated additional annual healthcare cost of $2.5 billion among adults living with obesity (based on an adult obesity rate of 26%). Results of this study can inform decision making on investment in interventions that are effective in treating obesity and its complications.

Keywords: administrative data, healthcare cost, obesity-related comorbidities, real world evidence

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2897 Logistics Support as a Key Success Factor in Gastronomy

Authors: Hanna Zietara

Abstract:

Gastronomy is one of the oldest forms of commercial activity. It is currently one of the most popular and still dynamically developing branches of business. Socio-economic changes, its widespread occurrence, new techniques, or culinary styles affect the almost unlimited possibilities of its development. Importantly, regardless of the form of business adopted, food service is strongly related to logistics processes, and areas of food service that are closely linked to logistics are of strategic importance. Any inefficiency in logistics processes results in reduced chances for success and achieving competitive advantage by companies belonging to the catering industry. The aim of the paper is to identify the areas of logistic support occurring in the catering business, affecting the scope of the logistic processes implemented. The aim of the paper is realized through a plural homogeneous approach, based on: direct observation, text analysis of current documents, in-depth free targeted interviews.

Keywords: gastronomy, competitive advantage, logistics, logistics support

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2896 Monocytic Paraoxonase 2 (PON 2) Lactonase Activity Is Related to Myocardial Infarction

Authors: Mukund Ramchandra Mogarekar, Pankaj Kumar, Shraddha V. More

Abstract:

Background: Total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol (VLDL-C), Apo B, and lipoprotein(a) was found as atherogenic factors while high-density lipoprotein cholesterol (HDL-C) was anti-atherogenic. Methods and Results: The study group consists of 40 MI subjects as cases and 40 healthy as controls. Monocytic PON 2 Lactonase (LACT) activity was measured by using Dihydrocoumarine (DHC) as substrate. Phenotyping was done by method of Mogarekar MR et al, serum AOPP by modified method of Witko-Sarsat V et al and Apo B by Turbidimetric immunoassay. PON 2 LACT activities were significantly lower (p< 0.05) and AOPPs & Apo B were higher in MI subjects (p> 0.05). Trimodal distribution of QQ, QR & RR phenotypes of study population showed no significant difference among cases and controls (p> 0.05). Univariate binary logistic regression analysis showed independent association of TC, HDL, LDL, AOPP, Apo B, and PON 2 LACT activity with MI and multiple forward binary logistic regression showed PON 2 LACT activity and serum Apo B as an independent predictor of MI. Conclusions- Decrease in PON 2 LACT activity in MI subjects than in controls suggests increased oxidative stress in MI which is reflected by significantly increased AOPP and Apo B. PON 1 polymorphism of QQ, QR and RR showed no significant difference in protection against MI. Univariate and multiple forward binary logistic regression showed PON 2 LACT activity and serum Apo B as an independent predictor of MI.

Keywords: advanced oxidation protein products, apolipoprotein-B, myocardial infarction, paraoxonase 2 lactonase

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2895 Construction of a Supply Chain Model Using the PREVA Method: The Case of Innovative Sargasso Recovery Projects in Ther Lesser Antilles

Authors: Maurice Bilioniere, Katie Lanneau

Abstract:

Suddenly appeared in 2011, invasions of sargasso seaweeds Fluitans and Natans are a climatic hazard which causes many problems in the Caribbean. Faced with the growth and frequency of the phenomenon of massive sargasso stranding on their coasts, the French West Indies are moving towards the path of industrial recovery. In this context of innovative projects, we will analyze the necessary requirements for the management and performance of the supply chain, taking into account the observed volatility of the sargasso input. Our prospective approach will consist in studying the theoretical framework of modeling a hybrid supply chain by coupling the discreet event simulation (DES) with a valuation of the process costs according to the "activity-based costing" method (ABC). The PREVA approach (PRocess EVAluation) chosen for our modeling has the advantage of evaluating the financial flows of the logistic process using an analytical model chained with an action model for the evaluation or optimization of physical flows.

Keywords: sargasso, PREVA modeling, supply chain, ABC method, discreet event simulation (DES)

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2894 Applying the Regression Technique for ‎Prediction of the Acute Heart Attack ‎

Authors: Paria Soleimani, Arezoo Neshati

Abstract:

Myocardial infarction is one of the leading causes of ‎death in the world. Some of these deaths occur even before the patient ‎reaches the hospital. Myocardial infarction occurs as a result of ‎impaired blood supply. Because the most of these deaths are due to ‎coronary artery disease, hence the awareness of the warning signs of a ‎heart attack is essential. Some heart attacks are sudden and intense, but ‎most of them start slowly, with mild pain or discomfort, then early ‎detection and successful treatment of these symptoms is vital to save ‎them. Therefore, importance and usefulness of a system designing to ‎assist physicians in the early diagnosis of the acute heart attacks is ‎obvious.‎ The purpose of this study is to determine how well a predictive ‎model would perform based on the only patient-reportable clinical ‎history factors, without using diagnostic tests or physical exams. This ‎type of the prediction model might have application outside of the ‎hospital setting to give accurate advice to patients to influence them to ‎seek care in appropriate situations. For this purpose, the data were ‎collected on 711 heart patients in Iran hospitals. 28 attributes of clinical ‎factors can be reported by patients; were studied. Three logistic ‎regression models were made on the basis of the 28 features to predict ‎the risk of heart attacks. The best logistic regression model in terms of ‎performance had a C-index of 0.955 and with an accuracy of 94.9%. ‎The variables, severe chest pain, back pain, cold sweats, shortness of ‎breath, nausea, and vomiting were selected as the main features.‎

Keywords: Coronary heart disease, Acute heart attacks, Prediction, Logistic ‎regression‎

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2893 Onco@Home: Comparing the Costs, Revenues, and Patient Experience of Cancer Treatment at Home with the Standard of Care

Authors: Sarah Misplon, Wim Marneffe, Johan Helling, Jana Missiaen, Inge Decock, Dries Myny, Steve Lervant, Koen Vaneygen

Abstract:

The aim of this study was twofold. First, we investigated whether the current funding from the national health insurance (NHI) of home hospitalization (HH) for oncological patients is sufficient in Belgium. Second, we compared patient’s experiences and preferences of HH to the standard of care (SOC). Two HH models were examined in three Belgian hospitals and three home nursing organizations. In a first HH model, the blood draw and monitoring prior to intravenous therapy were performed by a trained home nurse at the patient’s home the day before the visit to the day hospital. In a second HH model, the administration of two subcutaneous treatments was partly provided at home instead of in the hospital. Therefore, we conducted (1) a bottom-up micro-costing study to compare the costs and revenues for the providers (hospitals and home care organizations), and (2) a cross-sectional survey to compare patient’s experiences and preferences of the SOC group and the HH group. Our results show that HH patients prefer HH and none of them wanted to return to SOC, although the satisfaction of patients was not significantly different between the two categories. At the same time, we find that costs associated to HH are higher overall. Comparing revenues with costs, we conclude that the current funding from NHI of HH for oncological patients is insufficient.

Keywords: cost analysis, health insurance, preference, home hospitalization

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2892 A Relational View for Financial Metrics in Logistics Service Providers

Authors: Paulo Sergio Altman Ferreira

Abstract:

Relationship development plays an essential role in every logistics company. Logistics companies are service-based businesses essentially performing the flow of materials, housing, and inventory management for a wide range of customers. The service encounter between the logistics provider’s personnel and the customers may form a connection that will demonstrate a strong impact, not only to the customers' overall satisfaction but may also provide the perception of individualized services. Logistics services must drive value. It also shows a close influence on the quality and costs of client-centered services. If we describe logistics value creation as the function of quality perception of the client divided by service costs, there is a requirement to better outline and explain the measures and analytics for logistics costs and relationship performance. This critical shift to understand logistics services is a relevant contribution to capture how relationship value can be quantified. This might involve changing our current perspective on logistics providers beyond uniquely measuring the services in terms of activities, personnel levels, and financial/costs ratios. This paper argues that measuring value creation accomplishments of logistics services needs to consider the relational improvements for the wider range of logistics companies. Accurate logistics value requires a description of the financial impact of the relational perspective of the service.

Keywords: logistics services providers, financial metrics, relationship management, value creation

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2891 Naïve Bayes: A Classical Approach for the Epileptic Seizures Recognition

Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

Abstract:

Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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2890 Using Linear Logistic Regression to Evaluation the Patient and System Delay and Effective Factors in Mortality of Patients with Acute Myocardial Infarction

Authors: Firouz Amani, Adalat Hoseinian, Sajjad Hakimian

Abstract:

Background: The mortality due to Myocardial Infarction (MI) is often occur during the first hours after onset of symptom. So, for taking the necessary treatment and decreasing the mortality rate, timely visited of the hospital could be effective in this regard. The aim of this study was to investigate the impact of effective factors in mortality of MI patients by using Linear Logistic Regression. Materials and Methods: In this case-control study, all patients with Acute MI who referred to the Ardabil city hospital were studied. All of died patients were considered as the case group (n=27) and we select 27 matched patients without Acute MI as a control group. Data collected for all patients in two groups by a same checklist and then analyzed by SPSS version 24 software using statistical methods. We used the linear logistic regression model to determine the effective factors on mortality of MI patients. Results: The mean age of patients in case group was significantly higher than control group (75.1±11.7 vs. 63.1±11.6, p=0.001).The history of non-cardinal diseases in case group with 44.4% significantly higher than control group with 7.4% (p=0.002).The number of performed PCIs in case group with 40.7% significantly lower than control group with 74.1% (P=0.013). The time distance between hospital admission and performed PCI in case group with 110.9 min was significantly upper than control group with 56 min (P=0.001). The mean of delay time from Onset of symptom to hospital admission (patient delay) and the mean of delay time from hospital admissions to receive treatment (system delay) was similar between two groups. By using logistic regression model we revealed that history of non-cardinal diseases (OR=283) and the number of performed PCIs (OR=24.5) had significant impact on mortality of MI patients in compare to other factors. Conclusion: Results of this study showed that of all studied factors, the number of performed PCIs, history of non-cardinal illness and the interval between onset of symptoms and performed PCI have significant relation with morality of MI patients and other factors were not meaningful. So, doing more studies with a large sample and investigated other involved factors such as smoking, weather and etc. is recommended in future.

Keywords: acute MI, mortality, heart failure, arrhythmia

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2889 A Sensitivity Analysis on the Production of Potable Water, Green Hydrogen and Derivatives from South-West African Seawater

Authors: Shane David van Zyl, A. J. Burger

Abstract:

The global green energy shift has placed significant value on the production of green hydrogen and its derivatives. The study examines the impact on capital expenditure (CAPEX), operational expenditure (OPEX), levelized cost, and environmental impact, depending on the relationship between various production capacities of potable water, green hydrogen, and green ammonia. A model-based sensitivity analysis approach was used to determine the relevance of various process parameters in the production of potable water combined with green hydrogen or green ammonia production. The effects of changes on CAPEX, OPEX and levelized costs of the products were determined. Furthermore, a qualitative environmental impact analysis was done to determine the effect on the environment. The findings indicated the individual process unit contribution to the overall CAPEX and OPEX while also determining the major contributors to changes in the levelized costs of products. The results emphasize the difference in costs associated with potable water, green hydrogen, and green ammonia production, indicating the extent to which potable water production costs become insignificant in the complete process, which, therefore, can have a large social benefit through increased potable water production resulting in decreased water scarcity in the south-west African region.

Keywords: CAPEX and OPEX, desalination, green hydrogen and green ammonia, sensitivity analysis

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2888 The Effect of Sustainable Land Management Technologies on Food Security of Farming Households in Kwara State, Nigeria

Authors: Shehu A. Salau, Robiu O. Aliu, Nofiu B. Nofiu

Abstract:

Nigeria is among countries of the world confronted with food insecurity problem. The agricultural production systems that produces food for the teaming population is not endurable. Attention is thus being given to alternative approaches of intensification such as the use of Sustainable Land Management (SLM) technologies. Thus, this study assessed the effect of SLM technologies on food security of farming households in Kwara State, Nigeria. A-three stage sampling technique was used to select a sample of 200 farming households for this study. Descriptive statistics, Shriar index, Likert scale, food security index and logistic regression were employed for the analysis. The result indicated that majority (41%) of the household heads were between the ages of 51 and 70 years with an average of 60.5 years. Food security index revealed that 35% and 65% of the households were food secure and food insecure respectively. The logistic regression showed that SLM technologies, estimated income, household size, gender and age of the household heads were the critical determinants of food security among farming households. The most effective coping strategies adopted by households geared towards lessening the effects of food insecurity are reduced quality of food consumed, employed off-farm jobs to raise household income and diversion of money budgeted for other uses to purchase foods. Governments should encourage the adoption and use of SLM technologies at all levels. Policies and strategies that reduce household size should be enthusiastically pursued to reduce food insecurity.

Keywords: agricultural practices, coping strategies, farming households, food security, SLM technologies, logistic regression

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2887 Faults in the Projects, Deviation in the Cost

Authors: S. Ahmed, P. Dlask, B. Hasan

Abstract:

There are several ways to estimate the cost of the construction project: simple and detailed. The process of estimating cost is usually done during the design stage, which should take long-time and the designer must give attention to all details. This paper explain the causes of the deviations occurring in the cost of the construction project, and determines the reasons of these differences between contractual cost and final cost of the construction project, through the study of literature review related to this field, and benefiting from the experience of workers in the field of building (owners, contractors) through designing a questionnaire, and finding the most ten important reasons and explain the relation between the contractual cost and the final cost according to these reasons. The difference between those values will be showed through diagrams drawn using the statistical program. In addition to studying the effects of overrun costs on the advancing of the project, and identify the most five important effects. According to the results, we can propose the right direction for the final cost evaluation and propose some measures that would help to control and adjust the deviation in the costs.

Keywords: construction projects, building, cost, estimating costs, delay, overrun

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2886 Linking Milk Price and Production Costs with Greenhouse Gas Emissions of Luxembourgish Dairy Farms

Authors: Rocco Lioy, Tom Dusseldorf, Aline Lehnen, Romain Reding

Abstract:

A study concerning both the rentability and ecological performance of dairy production in Luxembourg was carried out for the years 2017, 2018 and 2019. The data of 100 dairy farms, referring to the Greenhouse gas emissions (ecology) and the profitability (economy) of dairy production, were evaluated, and the average was compared to the corresponding figures of 80 Luxembourgish dairy farms evaluated in the years 2014, 2015 and 2016. The ecological evaluation could confirm that farm efficiency (especially defined as the lowest ratio between used feedstuff and produced milk) is the key driver for significantly reducing the level of emissions in dairy farms. In both farm groups and in the two periods, the efficient farms show almost the same level of emissions per kg ECM (1,17 kg CO2-eq) in comparison with intensive farms (1,13 kg CO2-eq), and at the same time a by far lowest level of emissions related to the production surface (9,9 vs. 13,9 t CO2-eq/ha). Concerning the economic performances, it could be observed that in the years 2017, 2018 and 2019, the intensive farms (we define intensity in the first place in terms of produced milk pro ha) reached a higher profit (incomes minus costs, only consideration for subsidies) than the efficient farms (4,8 vs. 2,6 €-cent/kg ECM), in contradiction with the observation of the years 2014, 2015 and 2015 (1,5 vs. 3,7 €-cent/kg ECM). The most important reason for this divergent behavior was a change in income and cost structure in the considered periods. In the last period (2017, 2018 and 2019), the milk price was considerably higher than in the previous period, and the production costs were lower. This was of advantage for intensive farms, which produce the highest quantity of milk with a high amount of production means. In the period 2014, 2015 and 2016, with lower milk prices but comparable production costs, the advantage was with efficient farms. In conclusion, we expect that in the next future, when especially the production costs will presumably be much higher than in the last years, the profitableness of dairy farming will decrease. In this case, we assume that efficient farms will provide not only an ecologically but also an economically better performance than production-intensive farms. High milk prices and low production costs are no good incentives for carbon-smart farming.

Keywords: efficiency, intensity, dairy, emissions, prices, costs

Procedia PDF Downloads 96
2885 Breast Cancer Detection Using Machine Learning Algorithms

Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

Abstract:

In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

Procedia PDF Downloads 52
2884 Lean Implementation Analysis on the Safety Performance of Construction Projects in the Philippines

Authors: Kim Lindsay F. Restua, Jeehan Kyra A. Rivero, Joneka Myles D. Taguba

Abstract:

Lean construction is defined as an approach in construction with the purpose of reducing waste in the process without compromising the value of the project. There are numerous lean construction tools that are applied in the construction process, which maximizes the efficiency of work and satisfaction of customers while minimizing waste. However, the complexity and differences of construction projects cause a rise in challenges on achieving the lean benefits construction can give, such as improvement in safety performance. The objective of this study is to determine the relationship between lean construction tools and their effects on safety performance. The relationship between construction tools applied in construction and safety performance is identified through Logistic Regression Analysis, and Correlation Analysis was conducted thereafter. Based on the findings, it was concluded that almost 60% of the factors listed in the study, which are different tools and effects of lean construction, were determined to have a significant relationship with the level of safety in construction projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety

Procedia PDF Downloads 186
2883 Recovery of an Area Degraded by Gullies in the Municipality of Monte Alto (SP), Brazil

Authors: Layane Sara Vieira, Paulo Egidio Bernardo, Roberto Saverio Souza Costa

Abstract:

Anthropogenic occupations and agricultural explorations without concern for the preservation and sustainability of the activity result in soil degradation that can make rural activity unfeasible. The objective of this work was to characterize and evaluate the recovery costs of an area degraded by major erosion (gully) in the municipality of Monte Alto (SP). Topographic characterization was carried out by means of a planialtimetric survey with a total station. The contours of the gully, internal area, slope height, contribution area, volume, and costs of operations for the recovery of the gully were delimited. The results obtained showed that the gully has a length of 145.56 m, a maximum width of 36.61 m, and a gap of 19.48 m. The external area of the gully is 1,039.8741 m², and the internal area is 119.3470 m². The calculated volume was 3,282.63 m³. The intervention area for breaking slopes was measured at 8,471.29 m², requiring the construction of 19 terraces in this area, vertically spaced at 2.8 m. The estimated costs for mechanical recovery of the gully were R$ 19,167.84 (US$ 3.657,98).

Keywords: erosion, volumetric assessment, soil degradation, terraces

Procedia PDF Downloads 106
2882 Heart Ailment Prediction Using Machine Learning Methods

Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

Abstract:

The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

Procedia PDF Downloads 49
2881 Real-World Economic Burden of Musculoskeletal Disorders in Nigeria

Authors: F. Fatoye, C. E. Mbada, T. Gebrye, A. O. Ogunsola, C. Fatoye, O. Oyewole

Abstract:

Musculoskeletal disorders (MSDs) such as low back pain (LBP), cervical spondylosis (CSPD), sprain, osteoarthritis (OA), and post immobilization stiffness (PIS) have a major impact on individuals, health systems and society in terms of morbidity, long-term disability, and economics. This study estimated the direct and indirect costs of common MSDs in Osun State, Nigeria. A review of medical charts for adult patients attending Physiotherapy Outpatient Clinic at the Obafemi Awolowo University Teaching Hospitals Complex, Osun State, Nigeria between 2009 and 2018 was carried out. The occupational class of the patients was determined using the International Labour Classification (ILO). The direct and indirect costs were estimated using a cost-of-illness approach. Physiotherapy related health resource use, and costs of the common MSDs, including consultation fee, total fee charge per session, costs of consumables were estimated. Data were summarised using descriptive statistics mean and standard deviation (SD). Overall, 1582 (Male = 47.5%, Female = 52.5%) patients with MSDs population with a mean age of 47.8 ± 25.7 years participated in this study. The mean (SD) direct costs estimate for LBP, CSPD, PIS, sprain, OA, and other conditions were $18.35 ($17.33), $34.76 ($17.33), $32.13 ($28.37), $35.14 ($44.16), $37.19 ($41.68), and $15.74 ($13.96), respectively. The mean (SD) indirect costs estimate of LBP, CSPD, PIS, sprain, OA, and other MSD conditions were $73.42 ($43.54), $140.57 ($69.31), $128.52 ($113.46), sprain $140.57 ($69.31), $148.77 ($166.71), and $62.98 ($55.84), respectively. Musculoskeletal disorders contribute a substantial economic burden to individuals with the condition and society. The unacceptable economic loss of MSDs should be reduced using appropriate strategies. Further research is required to determine the clinical and cost effectiveness of strategies to improve health outcomes of patients with MSDs. The findings of the present study may assist health policy and decision makers to understand the economic burden of MSDs and facilitate efficient allocation of healthcare resources to alleviate the burden associated with these conditions in Nigeria.

Keywords: economic burden, low back pain, musculoskeletal disorders, real-world

Procedia PDF Downloads 221
2880 Public Preferences and Willingness to Pay for Social Health Insurance in Iran: A Discrete Choice Experiment

Authors: Mohammad Ranjbar, Mohammad Bazyar, Blake Angell, Thomas Lung, Yibeltal Assefa

Abstract:

Background: Current health insurance programs in Iran suffer from low enrolment and are not sufficient to attain the country to universal health coverage (UHC). We hypothesize that improving the enrollment rate and moving towards a more sustainable UHC can be achieved by improving the benefits package and providing new incentives. The objective of this study is to assess public preferences and willingness to pay (WTP) for social health insurance (SHI) in Iran. Methods: A discrete choice experiment (DCE) was conducted in 2021, using a self-administered questionnaire on 500 participants to estimate WTP and determine individual preferences for the SHI in Yazd, Iran. Respondents were presented with an eight-choice set and asked to select their preferred one. In each choice set, scenarios were described by eight attributes with varying levels. The conditional logit regression model was used to analyze the participants' preferences. Willingness to pay for each attribute was also calculated. Results: Most included attributes were significant predictors of the choice of a health insurance package. The maximum coverage of hospitalization costs in the private sector, ancillary services such as glasses, canes, etc., as well as coverage for hospitalization costs in the public sector and drug costs, were the most important determining factors for this choice. Coverage of preventive dental care did not significantly influence respondent choices. Estimating WTP showed that individuals are willing to pay more for higher financial protection, particularly against private sector costs; the WTP to increase the coverage of hospitalization costs in the private sector from 50% to 90% is estimated at 362,068 IR, Rials per month. Conclusion: This study identifies the key factors that the population value with regard to health insurance and the tradeoffs they are willing to make between them. Hospitalization, drugs, and ancillary services were the most important determining factors for their choice. The data suggest that additional resources coming into the Iranian health system might best be prioritized to cover hospitalization and drug costs and those associated with ancillary services.

Keywords: social health insurance, preferences, discrete choice experiment, willingness to pay

Procedia PDF Downloads 89
2879 The Effects of Cost-Sharing Contracts on the Costs and Operations of E-Commerce Supply Chains

Authors: Sahani Rathnasiri, Pritee Ray, Sardar M. N. Isalm, Carlos A. Vega-Mejia

Abstract:

This study develops a cooperative game theory-based cost-sharing contract model for a business to consumer (B2C) e-commerce supply chain to minimize the overall supply chain costs and the individual costs within an information asymmetry scenario. The objective of this study is to address the issues of strategic interactions among the key players of the e-commerce supply chain operation, which impedes the optimal operational outcomes. Game theory has been included in the field of supply chain management to resolve strategic decision-making issues; however, most of the studies are limited only to two-echelons of the supply chains. Multi-echelon supply chain optimizations based on game-theoretic models are less explored in the previous literature. This study adopts a cooperative game model to focus on the common payoff of operations and addresses the issues of information asymmetry and coordination of a three-echelon e-commerce supply chain. The cost-sharing contract model integrates operational features such as production, inventory management and distribution with the contract related constraints. The outcomes of the model highlight the importance of maintaining lower operational costs by all players to obtain benefits from the cost-sharing contract. Further, the cost-sharing contract ensures true cost revelation, and hence eliminates the information asymmetry issues among the players. Comparing the results of the contract model with the de-centralized e-commerce supply chain operation further emphasizes that the cost-sharing contract derives Pareto-improved outcomes and minimizes the costs of overall e-commerce supply chain operation.

Keywords: cooperative game theory, cost-sharing contract, e-commerce supply chain, information asymmetry

Procedia PDF Downloads 128
2878 Prediction of Coronary Artery Stenosis Severity Based on Machine Learning Algorithms

Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

Abstract:

Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

Procedia PDF Downloads 228