Search results for: Cox proportional hazard regression

Authors: Lalith Edirisinghe, Zhihong Jin, A.W. Wijeratne, Hansa Edirisinghe, Lakshmi Ranwala Rashika Mudunkotuwa

Abstract:

A paradigm shift in container inventory management (CIM) is a long-awaited industry need. Virtual container yard (VCY) is a concept developed in 2013 and its primary objective is to minimize shipping transport cost through implementing container exchange between carriers. Shipping lines always try to maintain lower container idle time and provide higher customer satisfaction. However, it is disappointing to note that carriers turn a blind eye to the escalating cost resulted from the present inefficient CIM mechanism. The cost of empty container management is simply transferred to the importers and exporters as freight adjustments. It also creates an environmental hazard. Therefore, it has now become a problem for the society. Therefore, a paradigm shift may be required as the present CIM system is not working for common interests of human beings as it should be.

Keywords: collaboation, inventory, shipping, virtual container yard

Procedia PDF Downloads 263

Authors: Guillaume Craveur

Abstract:

This study highlights the impact of an onboard fire for the evacuation of a rolling stock. Two fires models are achieved. The first one is a zone model realized with the CFAST software. Then, this fire is imported in a building EXODUS model in order to determine the evacuation time with effects of fire effluents (temperature, smoke opacity, smoke toxicity) on passengers. The second fire is achieved with Fire Dynamics Simulator software. The fire defined is directly imported in the FDS+Evac model which will permit to determine the evacuation time and effects of fire effluents on passengers. These effects will be compared with tenability criteria defined in some standards in order to see if the situation is acceptable. Different power of fire will be underlined to see from what power source the hazard become unacceptable.

Keywords: fire safety engineering, numerical tools, rolling stock, evacuation

Procedia PDF Downloads 201

Authors: A. El-S. Makled, M. K. Al-Tamimi

Abstract:

A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters

Procedia PDF Downloads 313

Authors: Anita Sadat Sadati Rostami, Reza Almasi Ghaleh

Abstract:

Surface electromyography (sEMG) offers important insights into muscle activation and has applications in fields including rehabilitation and human-computer interaction. The purpose of this work is to predict the degree of activation of two joints in the index finger using an LSTM-Transformer architecture trained on sEMG data from the Ninapro DB8 dataset. We apply advanced preprocessing techniques, such as multi-band filtering and customizable rectification methods, to enhance the encoding of sEMG data into features that are beneficial for regression tasks. The processed data is converted into spike patterns and simulated using Leaky Integrate-and-Fire (LIF) neuron models, allowing for neuromorphic-inspired processing. Our findings demonstrate that adjusting filtering parameters and neuron dynamics and employing the LSTM-Transformer model improves joint angle prediction performance. This study contributes to the ongoing development of deep learning frameworks for sEMG analysis, which could lead to improvements in motor control systems.

Keywords: surface electromyography, LSTM-transformer, spiking neural networks, hand kinematics, leaky integrate-and-fire neuron, band-pass filtering, muscle activity decoding

Procedia PDF Downloads 18

Authors: Tsion Tekalegn

Abstract:

In Ethiopia, improved potato varieties are essential for food security, but smallholders' adoption of improved technologies limits their productivity. For this study, data was collected based on a structured questionnaire randomly collected from the 329 sample farmers (158 adopters and 171 non-adopters). We estimate the adoption of improved variety and causal impact using Endogenous Switching Regression (ESR), and a propensity Score Matching (PSM) was used to test the treatment effect. This helps us estimate the effect of improved potato variety on smallholder farmer income by controlling for the role of the selection bias problem stemming from both observed and unobserved heterogeneity. According to the result, key determinants influencing adoption include livestock ownership, access to extension services, and farming experience, which positively affect the likelihood of adopting improved varieties. In contrast, access to irrigation negatively correlates with adoption, suggesting that farmers with reliable water sources perceive less need for improved varieties. The ESR model result confirmed that improved potato variety adoption increases the smallholder farmer income with an estimated gain of 8.77%. Thus, to improve the potato variety of the farming households, the government should give due emphasis to potato production, and the extension services need to be strengthened.

Keywords: adoption, improved potato varieties, endogenous switching regression, Ethiopia

Procedia PDF Downloads 38

Authors: Basan Shrestha

Abstract:

The relationship between the household size and the poverty is not well understood. Malthus followers advocate that the increasing population add pressure to the dwindling resource base due to increasing demand that would lead to poverty. Others claim that bigger households are richer due to availability of household labour for income generation activities. Facts from Nepal were analyzed to examine the relationship between the household size and poverty rate. The analysis of data from 3,968 Village Development Committee (VDC)/ municipality (MP) located in 75 districts of all five development regions revealed that the average household size had moderate positive correlation with the poverty rate (Karl Pearson's correlation coefficient=0.44). In a regression analysis, the household size determined 20% of the variation in the poverty rate. Higher positive correlation was observed in eastern Nepal (Karl Pearson's correlation coefficient=0.66). The regression analysis showed that the household size determined 43% of the variation in the poverty rate in east. The relation was poor in far-west. It could be because higher incidence of poverty was there irrespective of household size. Overall, the facts revealed that the bigger households were relatively poorer. With the increasing level of awareness and interventions for family planning, it is anticipated that the household size will decrease leading to the decreased poverty rate. In addition, the government needs to devise a mechanism to create employment opportunities for the household labour force to reduce poverty.

Keywords: household size, poverty rate, nepal, regional development

Procedia PDF Downloads 362

Authors: Himayatullah Khan, Alena Fedorova

Abstract:

The present paper analyses the income-consumption relationships in Pakistan using annual time series data from 1980-81 to 2010-1. The paper uses the Augmented Dickey-Fuller test to check the unit root and stationarity in these two time series. The paper finds that the two time series are nonstationary but stationary at their first difference levels. The Augmented Engle-Granger test and the Cointegrating Regression Durbin-Watson test imply that the two time series of consumption and income are cointegrated and that long-run marginal propensity to consume is 0.88 which is given by the estimated (static) equilibrium relation. The paper also used the error correction mechanism to find out to model dynamic relationship. The purpose of the ECM is to indicate the speed of adjustment from the short-run equilibrium to the long-run equilibrium state. The results show that MPC is equal to 0.93 and is highly significant. The coefficient of Engle-Granger residuals is negative but insignificant. Statistically, the equilibrium error term is zero, which suggests that consumption adjusts to changes in GDP in the same period. The short-run changes in GDP have a positive impact on short-run changes in consumption. The paper concludes that we may interpret 0.93 as the short-run MPC. The pair-wise Granger Causality test shows that both GDP and consumption Granger cause each other.

Keywords: cointegrating regression, Augmented Dickey Fuller test, Augmented Engle-Granger test, Granger causality, error correction mechanism

Procedia PDF Downloads 416

Authors: Dwi Kartika Rukmi, Miftafu Darussalam

Abstract:

Background: The disclosure of women’s HIV status toward their sexual partners is an important issue that should be regarded as one of the efforts to prevent and control the spread of HIV. Research on the disclosure of seropositive HIV status as well as women-related factors in Indonesia, especially Yogyakarta is only a few. Methods: This is a correlational descriptive research along with its cross-sectional approach on 329 women with HIV/AIDS at the Victory Plus NGO from June to July 2016. This research used a purposive sampling method and a questionnaire as the data collection technique. The bivariate analysis test was undertaken by using a chi-square and multivariate test along with a logistic regression. Result: The multivariate analysis and logistic regression show five independent variables related to the disclosure of seropositive HIV status of women with HIV/AIDS toward their sexual partners, namely ethnicity (aOR = 36,859; 95% CI; (6,544-207,616)) religion (aOR =0,255; 95%CI; (0,075-0,868)), discussion with partners prior to the HIV test (aOR =0,069; 95%CI; (0,065-0,438)) , types of sexual partners (aOR = 0.191; 95% CI; (0.082-0,445)) and knowledge on the partners’ HIV status (aOR = 0.036; 95% CI; (0.008-0.160)). The highest level of reason for seropositive HIV women not to be open about their partners’ status is the fear of being rejected by their partners and the environmental stigma of HIV AIDS disease. Conclusion: The disclosure of seropositive HIV status in women with HIV/AIDS in the Victory Plus NGO of Yogyakarta was 79.4% or classified as a high category with some related factors such as ethnicity, religion, discussion with partners prior to the HIV test, types of partners and knowledge on the partners’ HIV status.

Keywords: women, HIV, disclosure, sexual partner

Procedia PDF Downloads 261

Authors: Kalandi Charan Pradhan

Abstract:

In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

Procedia PDF Downloads 225

Authors: Mastawal Melese, Yismaw Assefa

Abstract:

This study aims to identify household-level determinants of solid waste disposal (SWD) practices in Bure Town, north-western Ethiopia. Using a cross-sectional design and a mixed-methods approach, data were collected from 238 randomly selected households through structured interviews, focus group discussions, and field observations. Descriptive analysis revealed that 14.7% of households used composting as a primary SWD method, 37.4% practiced open dumping, 25.6% used burning, and 22.3% resorted to burial. Multinomial logistic regression showed that factors such as monthly income, age, family size, length of residence, sex, home ownership, solid waste sorting procedures, and education significantly influenced the choice of disposal method. Households with lower education, income, home ownership, and shorter residence times were more likely to use improper disposal methods. Females were found to be more likely to engage in better waste disposal practices than males. These findings underscore the need for context-specific interventions in newly developing towns to enhance household-level SWM systems by addressing key socio-economic factors.

Keywords: multinomial logistic regression, solid waste management, solid waste disposal, urban household

Procedia PDF Downloads 24

Authors: Nixon Kuruvila, H. V. Ravindra

Abstract:

Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi’s Technique and Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are Dimensional Accuracy (DA) and Material Removal Rate (MRR). Experiments were designed as per Taguchi’s L16 Orthogonal Array (OA) where in Pulse-on duration, Pulse-off duration, Current, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Oil Hardened Non Shrinking Steel (OHNS) having the thickness of 40 mm. The results of the study reveals that among the machining parameters it is preferable to go in for lower pulse-off duration for achieving over all good performance. Regarding MRR, OHNS is to be eroded with medium pulse-off duration and higher flush rate. Finally, the validation exercise performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.

Keywords: dimensional accuracy (DA), regression analysis (RA), Taguchi method (TM), volumetric material removal rate (VMRR)

Procedia PDF Downloads 411

Authors: Chen Shuwen, Nunthapin Chantachaimongkol

Abstract:

Since the world has moved into a transitional period, known as globalization; the business environment is now more complicated than ever before. Corporate information has become a matter of great importance for stakeholders, in order to understand the current situation. As a result of this, the concept of corporate governance has been broadly introduced to manage and control the affairs of corporations while businesses are required to disclose both financial and non-financial information to public via various communication channels such as the annual report, the financial report, the company’s website, etc. However, currently there are several other issues related to asymmetric information such as moral hazard or adverse selection that still occur intensively in workplaces. To prevent such problems in the business, it is required to have an understanding of what factors strengthen their transparency, accountability, fairness, and responsibility. Under aforementioned arguments, this paper aims to propose a conceptual framework that enables an investigation on how corporate governance mechanism influences disclosure efficiency of listed companies in the Association of Southeast Asia Nations (ASEAN) and the factors that should be considered for further development of good behaviors, particularly in regards to voluntary disclosure practices. To achieve its purpose, extensive reviews of literature are applied as a research methodology. It is divided into three main steps. Firstly, the theories involved with both corporate governance and disclosure practices such as agency theory, contract theory, signaling theory, moral hazard theory, and information asymmetry theory are examined to provide theoretical backgrounds. Secondly, the relevant literatures based on multi- perspectives of corporate governance, its attributions and their roles on business processes, the influences of corporate governance mechanisms on business performance, and the factors determining corporate governance characteristics as well as capability are reviewed to outline the parameters that should be included in the proposed model. Thirdly, the well-known regulatory document OECD principles and previous empirical studies on the corporate disclosure procedures are evaluated to identify the similarities and differentiations with the disclosure patterns in the ASEAN. Following the processes and consequences of the literature review, abundant factors and variables are found. Further to the methodology, additional critical factors that also have an impact on the disclosure behaviors are addressed in two groups. In the first group, the factors which are linked to the national characteristics - the quality of national code, legal origin, culture, the level of economic development, and so forth. Whereas in the second group, the discoveries which refer to the firm’s characteristics - ownership concentration, ownership’s rights, controlling group, and so on. However, because of research limitations, only some literature are chosen and summarized to form part of the conceptual framework that explores the relationship between corporate governance and the disclosure practices of listed companies in ASEAN.

Keywords: corporate governance, disclosure practice, ASEAN, listed company

Procedia PDF Downloads 194

Authors: Farah Lazzali, Yamina Ait Meziane

Abstract:

Recent earthquakes in Algeria have demonstrated the need for seismic risk reduction. In fact, the latest major earthquake that affected the Algiers-Boumerdes region in 2003 caused excessive levels of loss of life and property. Economic, social and environmental damage were also experienced. During the three days following the event, a relatively weak coordination of public authority was noted. Many localities did not receive any relief due to lack of information from concerned authorities and delay in connecting damaged roads. Following this event, Algerian government and civil society has recognized the urgent need for an appropriate and immediate seismic risk mitigation strategy. This paper describes procedures for emergency response following past earthquakes in Algeria and provides a brief review of risk mitigation activities since 1980. The paper also aims to provide measures to reduce earthquake risk through general strategy and practical implementation of the mitigation actions.

Keywords: earthquake, hazard, prevention, strategy, risk reduction

Procedia PDF Downloads 531

Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

Abstract:

Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

Procedia PDF Downloads 149

Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

Abstract:

Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

Procedia PDF Downloads 335

Authors: Rabiaal Adawiyah Shazali, Corina Joseph

Abstract:

The disclosure of Intellectual Capital (IC) information is getting more vital in today’s era of a knowledge-based economy. Companies are advised by accounting bodies to enhance IC disclosure which complements the conventional financial disclosures. There are no accounting standards for Intellectual Capital Disclosure (ICD), therefore the disclosure is entirely voluntary. Hence, this study aims to investigate the extent of ICD and to examine the relationship between corporate governance and ICD in Malaysia. This study employed content analysis of 100 annual reports by the top 100 public listed companies in Malaysia during 2012. The uniqueness of this study lies on its underpinning theory used where it applies the institutional isomorphism theory to support the effect of the attributes of corporate governance towards ICD. In order to achieve the stated objective, multiple regression analysis were employed to conduct this study. From the descriptive statistics, it was concluded that public listed companies in Malaysia have increased their awareness towards the importance of ICD. Furthermore, results from the multiple regression analysis confirmed that corporate governance affects the company’s ICD where the frequency of audit committee meetings and the board size has positively influenced the level of ICD in companies. Findings from this study would provide an incentive for companies in Malaysia to enhance the disclosure of IC. In addition, this study would assist Bursa Malaysia and other regulatory bodies to come up with a proper guideline for the disclosure of IC.

Keywords: annual report, content analysis, corporate governance, intellectual capital disclosure

Procedia PDF Downloads 216

Authors: Kalpana Adhikari, Mandip Subedi, Keshab Sharma, Indra P. Acharya

Abstract:

The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 struck the central region of Nepal on April 25, 2015 with the epicenter about 77 km northwest of Kathmandu Valley . Peak ground acceleration observed during the earthquake was 0.18g. This motion induced several geotechnical effects such as landslides, foundation failures liquefaction, lateral spreading and settlement, and local amplification. An aftershock of moment magnitude (Mw) 7.3 hit northeast of Kathmandu on May 12 after 17 days of main shock caused additional damages. Kathmandu is the largest city in Nepal, have a population over four million. As the Kathmandu Valley deposits are composed mainly of sand, silt and clay layers with a shallow ground water table, liquefaction is highly anticipated. Extensive liquefaction was also observed in Kathmandu Valley during the 1934 Nepal-Bihar earthquake. Field investigations were carried out in Kathmandu Valley immediately after Mw 7.8, April 25 main shock and Mw 7.3, May 12 aftershock. Geotechnical investigation of both liquefied and non-liquefied sites were conducted after the earthquake. This paper presents observations of liquefaction and liquefaction induced damage, and the liquefaction potential assessment based on Standard Penetration Tests (SPT) for liquefied and non-liquefied sites. SPT based semi-empirical approach has been used for evaluating liquefaction potential of the soil and Liquefaction Potential Index (LPI) has been used to determine liquefaction probability. Recorded ground motions from the event are presented. Geological aspect of Kathmandu Valley and local site effect on the occurrence of liquefaction is described briefly. Observed liquefaction case studies are described briefly. Typically, these are sand boils formed by freshly ejected sand forced out of over-pressurized sub-strata. At most site, sand was ejected to agricultural fields forming deposits that varied from millimetres to a few centimeters thick. Liquefaction-induced damage to structures in these areas was not significant except buildings on some places tilted slightly. Boiled soils at liquefied sites were collected and the particle size distributions of ejected soils were analyzed. SPT blow counts and the soil profiles at ten liquefied and non-liquefied sites were obtained. The factors of safety against liquefaction with depth and liquefaction potential index of the ten sites were estimated and compared with observed liquefaction after 2015 Gorkha earthquake. The liquefaction potential indices obtained from the analysis were found to be consistent with the field observation. The field observations along with results from liquefaction assessment were compared with the existing liquefaction hazard map. It was found that the existing hazard maps are unrepresentative and underestimate the liquefaction susceptibility in Kathmandu Valley. The lessons learned from the liquefaction during this earthquake are also summarized in this paper. Some recommendations are also made to the seismic liquefaction mitigation in the Kathmandu Valley.

Keywords: factor of safety, geotechnical investigation, liquefaction, Nepal earthquake

Procedia PDF Downloads 325

Authors: Hasan Serdar Öge, Esra Çiftçi, Kazım Karaboğa

Abstract:

The main purpose of the research is to address the role of psychological harassment behaviors (mobbing) to which employees are exposed and personality characteristics over work alienation. Research population was composed of the employees of Provincial Special Administration. A survey with four sections was created to measure variables and reach out the basic goals of the research. Correlation and step-wise regression analyses were performed to investigate the separate and overall effects of sub-dimensions of psychological harassment behaviors and personality characteristic on work alienation of employees. Correlation analysis revealed significant but weak relationships between work alienation and psychological harassment and personality characteristics. Step-wise regression analysis revealed also significant relationships between work alienation variable and assault to personality, direct negative behaviors (sub dimensions of mobbing) and openness (sub-dimension of personality characteristics). Each variable was introduced into the model step by step to investigate the effects of significant variables in explaining the variations in work alienation. While the explanation ratio of the first model was 13%, the last model including three variables had an explanation ratio of 24%.

Keywords: alienation, five-factor personality characteristics, mobbing, psychological harassment, work alienation

Procedia PDF Downloads 407

Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

Abstract:

In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

Procedia PDF Downloads 45

Authors: Pangkaj Kumar Mahanta, Md. Rafizul Islam

Abstract:

The rapid growth of the population causes a substantial amount of increase in household waste all over the world. Waste management is becoming one of the most challenging phenomena in the present day. The most environmentally friendly final disposal process of waste is sanitary landfilling, which is practiced in most developing countries. However, in Southeast Asia, most of the final disposal point is an open dump site. Due to the ignominy of proper management of waste and monitoring, the surrounding environment gets polluted more by the open dump site in comparison with a sanitary landfill. Khulna is 3rd largest metropolitan city in Bangladesh, having a population of around 1.5 million and producing approximately 450 tons per day of Municipal Solid Waste. The Municipal solid waste of Khulna city is disposed of in Rajbandh open dump site. The surrounding air is being polluted by the gas produced in the open dump site. Also, the open dump site produces leachate, which contains various heavy metals like Cadmium (Cd), Chromium (Cr), Lead (Pb), Manganese (Mn), Mercury (Hg), Strontium (Sr), etc. Leachate pollutes the soil as well as the groundwater of the open dump site and also the surrounding area through seepage. Moreover, during the rainy season, the surface water is polluted by leachate runoff. Also, the plastic waste flowing out from the open dump site through various drivers pollutes the nearby environment. The health risk assessment associated with heavy metals was carried out by computing the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) via different exposure pathways following the USEPA guidelines. For ecological risk, potential contamination index (Cp), Contamination factor (CF), contamination load index (PLI), numerical integrated contamination factor (NICF), enrichment factor (EF), ecological risk index (ER), and potential ecological risk index (PERI) were computed. The health risk and ecological risk assessment results reveal that some heavy metals possess strong health and ecological risk. In addition, the child faces higher harmful health risks from several heavy metals than the adult for all the exposure pathways and media. The conversion of an open dump site into a sanitary landfill and a proper management system can reduce the problems associated with an open dump site. In the sanitary landfill, the produced gas will be managed properly to save the surrounding atmosphere from being polluted. The seepage of leachate can be minimized by installing a compacted clay layer (CCL) as a baseline and leachate collection in a sanitary landfill to save the underlying soil layer and surrounding water bodies from leachate. Another important component of a sanitary landfill is the conversion of plastic waste to energy will minimize the plastic pollution in the landfill area and also the surrounding soil and water bodies. Also, in the sanitary landfill, the bio-waste can be used to make compost to reduce the volume of bio-waste and proper utilization of the landfill area.

Keywords: ecological risk, health risk, open dump site, sanitary landfill

Procedia PDF Downloads 195

Authors: Waleed Basuliman

Abstract:

Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

Procedia PDF Downloads 488

Authors: Khalid Kaddoura, Ahmed Assad, Tarek Zayed

Abstract:

Sewer pipelines are prone to deterioration over-time. In fact, their deterioration does not follow a fixed downward pattern. This is in fact due to the defects that propagate through their service life. Sewer pipeline defects are categorized into distinct groups. However, the main two groups are the structural and operational defects. By definition, the structural defects influence the structural integrity of the sewer pipelines such as deformation, cracks, fractures, holes, etc. However, the operational defects are the ones that affect the flow of the sewer medium in the pipelines such as: roots, debris, attached deposits, infiltration, etc. Yet, the process for each defect to emerge follows a cause and effect relationship. Deformation, which is the change of the sewer pipeline geometry, is one type of an influencing defect that could be found in many sewer pipelines due to many surrounding factors. This defect could lead to collapse if the percentage exceeds 15%. Therefore, it is essential to predict the deformation percentage before confronting such a situation. Accordingly, this study will predict the percentage of the deformation defect in sewer pipelines adopting the multiple regression analysis. Several factors will be considered in establishing the model, which are expected to influence the defamation defect severity. Besides, this study will construct a time-based curve to understand how the defect would evolve overtime. Thus, this study is expected to be an asset for decision-makers as it will provide informative conclusions about the deformation defect severity. As a result, inspections will be minimized and so the budgets.

Keywords: deformation, prediction, regression analysis, sewer pipelines

Procedia PDF Downloads 189

Authors: Martial Amou

Abstract:

This study was carried out to assess the situation of households’ livelihood under a changing climate pattern in the Zio district of Togo, West Africa. The study examined three important aspects: (i) assessment of households’ livelihood situation under a changing climate pattern, (ii) farmers’ perception and understanding of local climate change, (iii) determinants of adaptation strategies undertaken in cropping pattern to climate change. To this end, secondary sources of data, and survey data collected from 235 farmers in four villages in the study area were used. Adapted conceptual framework from Sustainable Livelihood Framework of DFID, two steps Binary Logistic Regression Model and descriptive statistics were used in this study as methodological approaches. Based on Sustainable Livelihood Approach (SLA), various factors revolving around the livelihoods of the rural community were grouped into social, natural, physical, human, and financial capital. Thus, the study came up that households’ livelihood situation represented by the overall livelihood index in the study area (34%) is below the standard average households’ livelihood security index (50%). The natural capital was found as the poorest asset (13%) and this will severely affect the sustainability of livelihood in the long run. The result from descriptive statistics and the first step regression (selection model) indicated that most of the farmers in the study area have clear understanding of climate change even though they do not have any idea about greenhouse gases as the main cause behind the issue. From the second step regression (output model) result, education, farming experience, access to credit, access to extension services, cropland size, membership of a social group, distance to the nearest input market, were found to be the significant determinants of adaptation measures undertaken in cropping pattern by farmers in the study area. Based on the result of this study, recommendations are made to farmers, policy makers, institutions, and development service providers in order to better target interventions which build, promote or facilitate the adoption of adaptation measures with potential to build resilience to climate change and then improve rural livelihood.

Keywords: climate change, rural livelihood, cropping pattern, adaptation, Zio District

Procedia PDF Downloads 326

Authors: Daming Xu, Yuanyuan Wang

Abstract:

Abstract: Under the trend of rapid expansion of urbanization, the motorized urban characteristics become more and more obvious, and the walkability of urban space is seriously affected. The construction of walkability of space, as the main mode of travel for the elderly in their daily lives, has become more and more important in the current social context of serious aging. Settlement is the most basic living unit of residents, and daily shopping, medical care, and other daily trips are closely related to the daily life of the elderly. Therefore, it is of great practical significance to explore the impact of built environment on elderly people's daily walking trips at the settlement level for the construction of pedestrian-friendly settlements for the elderly. The study takes three typical settlements in Harbin Daoli District in three different periods as examples and obtains data on elderly people's walking trips and built environment characteristics through field research, questionnaire distribution, and internet data acquisition. Finally, correlation analysis and multinomial logistic regression model were applied to analyze the influence mechanism of built environment on elderly people's walkability based on the control of personal attribute variables in order to provide reference and guidance for the construction of walkability for elderly people in built environment in the future.

Keywords: built environment, elderly, walkability, multinomial logistic regression model

Procedia PDF Downloads 77

Authors: Ke Qiu, Minzi Mao, Jianjun Ren, Yu Zhao

Abstract:

Although much has been done to investigate the influence of obstructive sleep apnea (OSA) on cognitive function, little attention has been paid to the role which gender differences play in this association. In the present study, we aim to explore the gender-specific association between OSA and cognitive impairment. Participants from UK biobank who have completed at least one of the five baseline cognitive tests (visuospatial memory, prospective memory, fluid intelligence, short numeric memory and reaction time) were included and were further categorized into three groups: (1) OSA, (2) self-reported snoring but without OSA, and (3) healthy controls (without OSA or snoring). Multivariable regression analysis was performed to examine the associations among snoring, OSA and performance of each of the five cognitive domains. A total of 267,889 participants (47% male, mean age: 57 years old) were included in our study. In the multivariable regression analysis, female participants in the OSA group had a higher risk of having poor prospective memory (OR: 1.24, 95% CI: 1.02～1.50, p = 0.03). Meanwhile, among female participants, OSA were inversely associated with the performances of fluid intelligence (β: -0.29, 95% CI: -0.46～-0.13, p < 0.001) and short-numeric memory (β: -0.14, 95% CI: -0.35～0.08, p = 0.02). In contrast, among male participants, no significant association was observed between OSA and impairment of the five cognitive domains. Overall, OSA was significantly associated with cognitive impairment in female participants rather than in male participants, indicating that more special attention and timely interventions should be given to female OSA patients to prevent further cognitive impairment.

Keywords: obstructive sleep apnea (OSA), cognitive impairment, gender-specific association, UK biobank

Procedia PDF Downloads 152

Authors: A. D. Usman, W. F. Wan Ahmad, H. H. Danjuma

Abstract:

Exposure due to GSM frequencies is subject of daily debate. Though regulatory bodies provide guidelines for exposure, people still exercise fear on the possible health hazard that may result due to long term usage. In this study, exposure due to electromagnetic field emitted by GSM base stations in industrial areas was investigated. The aimed was to determine whether industrial area exposure is higher as compared to residential as well as compliance with ICNIRP guidelines. Influence of reflection and absorption with respect to inverse square law was also investigated. Measurements from GSM base stations were performed at various distances in far field region. The highest measured peak power densities as well as the calculated values at GSM 1.8 GHz were 6.05 and 90 mW/m2 respectively. This corresponds to 0.07 and 1% of ICNIRP guidelines. The highest peak power densities as well as the calculated values at GSM 0.9 GHz were 11.92 and 49.7 mW/m2 respectively. These values were 0.3 and 1.1% of ICNIRP guidelines.

Keywords: Global System for Mobile Communications (GSM), Electromagnetic Field (EMF), far field, power density, Radiofrequency (RF)

Procedia PDF Downloads 482

Authors: Danny Fraser, James Zhang

Abstract:

Aim of the study: Our study aims to identify any statistically significant evidence as it relates to PROMs for mastectomy and implant-based reconstruction to guide future surgical management. Method: The demographic, pre and post-operative treatment and implant characteristics were collected of all patients at Basildon hospital who underwent breast reconstruction from 2017-2023. We used the Breast-Q psychosocial well-being, physical well-being, and satisfaction with breasts scales. An Independent t-test was conducted for each group, and linear regression of age and implant size. Results: 69 patients were contacted, and 39 PROMs returned. The mean age of patients was 57.6. 40% had smoked before, and 40.8% had BMI>30. 29 had pre-pectoral placement, and 40 had subpectoral placement. 17 had smooth implants, and 52 textured. Sub pectoral placement was associated with higher (75.7 vs. 61.9 p=0.046) psychosocial scores than pre pectoral, and textured implants were associated with a lower physical score than the smooth surface (34.7 VS 50.2 P=0.046). On linear regression, age was positively associated (p=0.007) with psychosocial score. Conclusion: We present a large cohort of patients who underwent breast reconstruction. Understanding the PROMs of these procedures can guide clinicians, patients and policy makers to be more informed of the course of rehabilitation of these operations. Significance: We have found that from a patient perspective subpectoral implant placement was associated with a statistically significant improvement in psychosocial scores.

Keywords: breast surgery, mastectomy, breast implants, oncology

Procedia PDF Downloads 61

Authors: Vineet Agrawal, Deepanjali S., Medha R., Subitha L.

Abstract:

Background. Hospital malnutrition is a highly prevalent issue and is known to increase the morbidity, mortality, length of hospital stay, and cost of care. In India, studies on hospital malnutrition have been restricted to ICU, post-surgical, and cancer patients. We designed this study to assess the impact of hospital malnutrition on 30-day post-discharge and in-hospital mortality in patients admitted in the general medicine department, irrespective of diagnosis. Methodology. All patients aged above 18 years admitted in the medicine wards, excluding medico-legal cases, were enrolled in the study. Nutritional assessment was done within 72 h of admission, using Subjective Global Assessment (SGA), which classifies patients into three categories: Severely malnourished, Mildly/moderately malnourished, and Normal/well-nourished. Anthropometric measurements like Body Mass Index (BMI), Triceps skin-fold thickness (TSF), and Mid-upper arm circumference (MUAC) were also performed. Patients were followed-up during hospital stay and 30 days after discharge through telephonic interview, and their final diagnosis, comorbidities, and cause of death were noted. Multivariate logistic regression and cox regression model were used to determine if the nutritional status at admission independently impacted mortality at one month. Results. The prevalence of malnourishment by SGA in our study was 67.3% among 395 hospitalized patients, of which 155 patients (39.2%) were moderately malnourished, and 111 (28.1%) were severely malnourished. Of 395 patients, 61 patients (15.4%) expired, of which 30 died in the hospital, and 31 died within 1 month of discharge from hospital. On univariate analysis, malnourished patients had significantly higher morality (24.3% in 111 Cat C patients) than well-nourished patients (10.1% in 129 Cat A patients), with OR 9.17, p-value 0.007. On multivariate logistic regression, age and higher Charlson Comorbidity Index (CCI) were independently associated with mortality. Higher CCI indicates higher burden of comorbidities on admission, and the CCI in the expired patient group (mean=4.38) was significantly higher than that of the alive cohort (mean=2.85). Though malnutrition significantly contributed to higher mortality on univariate analysis, it was not an independent predictor of outcome on multivariate logistic regression. Length of hospitalisation was also longer in the malnourished group (mean= 9.4 d) compared to the well-nourished group (mean= 8.03 d) with a trend towards significance (p=0.061). None of the anthropometric measurements like BMI, MUAC, or TSF showed any association with mortality or length of hospitalisation. Inference. The results of our study highlight the issue of hospital malnutrition in medicine wards and reiterate that malnutrition contributes significantly to patient outcomes. We found that SGA performs better than anthropometric measurements in assessing under-nutrition. We are of the opinion that the heterogeneity of the study population by diagnosis was probably the primary reason why malnutrition by SGA was not found to be an independent risk factor for mortality. Strategies to identify high-risk patients at admission and treat malnutrition in the hospital and post-discharge are needed.

Keywords: hospitalization outcome, length of hospital stay, mortality, malnutrition, subjective global assessment (SGA)

Procedia PDF Downloads 150

Authors: Justin Orimisan Ijigbade

Abstract:

The study was conducted to assess the effect of climate variability on honeybee’s production in Ondo State, Nigeria. Multistage sampling technique was employed to collect the data from 60 beekeepers across six Local Government Areas in Ondo State. Data collected were subjected to descriptive statistics and multiple regression model analyses. The results showed that 93.33% of the respondents were male with 80% above 40 years of age. Majority of the respondents (96.67%) had formal education and 90% produced honey for commercial purpose. The result revealed that 90% of the respondents admitted that low temperature as a result of long hours/period of rainfall affected the foraging efficiency of the worker bees, 73.33% claimed that long period of low humidity resulted in low level of nectar flow, while 70% submitted that high temperature resulted in improper composition of workers, dunes and queen in the hive colony. The result of multiple regression showed that beekeepers’ experience, educational level, access to climate information, temperature and rainfall were the main factors affecting honey bees production in the study area. Therefore, beekeepers should be given more education on climate variability and its adaptive strategies towards ensuring better honeybees production in the study area.

Keywords: climate variability, honeybees production, humidity, rainfall and temperature

Procedia PDF Downloads 273

Authors: Zhidong Zhang, Amanda Resendez

Abstract:

This study is to examine how teachers’ perspective on education technology use in their class influence their students’ achievement. The authors hypothesized that teachers’ perspective can directly or indirectly influence students’ learning, performance, and achievements. In this study, a questionnaire entitled, Teacher’s Perspective on Educational Technology, was delivered to 63 teachers and 1268 students’ mathematics and reading achievement records were collected. The questionnaire consists of four parts: a) demographic variables, b) attitudes on technology integration, c) outside factor affecting technology integration, and d) technology use in the classroom. Kruskal-Wallis and hierarchical regression analysis techniques were used to examine: 1) the relationship between the demographic variables and teachers’ perspectives on educational technology, and 2) how the demographic variables were causally related to students’ mathematics and reading achievements. The study found that teacher demographics were significantly related to the teachers’ perspective on educational technology with p < 0.05 and p < 0.01 separately. These teacher demographical variables included the school district, age, gender, the grade currently teach, teaching experience, and proficiency using new technology. Further, these variables significantly predicted students’ mathematics and reading achievements with p < 0.05 and p < 0.01 separately. The variations of R² are between 0.176 and 0.467. That means 46.7% of the variance of a given analysis can be explained by the model.

Keywords: teacher's perception of technology use, mathematics achievement, reading achievement, Kruskal-Wallis test, hierarchical regression analysis

Procedia PDF Downloads 133