Search results for: Ming Show Wong
3568 Local Interpretable Model-agnostic Explanations (LIME) Approach to Email Spam Detection
Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew
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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.
Procedia PDF Downloads 393567 Hybrid Heat Pump for Micro Heat Network
Authors: J. M. Counsell, Y. Khalid, M. J. Stewart
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Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat. For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system. This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.Keywords: gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated and sustainable electric
Procedia PDF Downloads 4093566 Effectiveness of Catalysis in Ozonation for the Removal of Herbizide 2,4 Dichlorophenoxyacetic Acid from Contaminated Water
Authors: S. Shanthi
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Catalyzed oxidation processes show extraordinary guarantee for application in numerous wastewater treatment ranges. Advanced oxidation processes are emerging innovation that might be utilized for particular objectives in wastewater treatment. This research work provides a solution for removal a refractory organic compound 2,4-dichlorophenoxyaceticacid a common water pollutant. All studies were done in batch mode in a constantly stirred reactor. Alternative ozonation processes catalysed by transition metals or granular activated carbon have been investigated for degradation of organics. Catalytic ozonation under study are homogeneous catalytic ozonation, which is based on ozone activation by transition metal ions present in aqueous solution, and secondly as heterogeneous catalytic ozonation in the presence of Granular Activated Carbon (GAC). The present studies reveal that heterogeneous catalytic ozonation using GAC favour the ozonation of 2,4-dichlorophenoxyaceticacid by increasing the rate of ozonation and a much higher degradation of substrates were obtained in a given time. Be that it may, Fe2+and Fe3+ ions decreased the rate of degradation of 2,4-dichlorophenoxyaceticacid indicating that it acts as a negative catalyst. In case of heterogeneous catalytic ozonation using GAC catalyst it was found that during the initial 5 minutes of contact solution concentration decreased significantly as the pollutants were adsorbed initially. Thereafter the substrate started getting oxidized and ozonation became a dominates the treatment process. The exhausted GAC was found to be regenerated in situ. The percentage reduction of the substrate was maximum achieved in minimum possible time when GAC catalyst is employed.Keywords: ozonation, homogeneous catalysis, heterogeneous catalysis, granular activated carbon
Procedia PDF Downloads 2403565 Probability-Based Damage Detection of Structures Using Model Updating with Enhanced Ideal Gas Molecular Movement Algorithm
Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee
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Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification
Procedia PDF Downloads 2713564 Debating the Role of Patriarchy in the Incidence of Gender-Based Violence in Jordan: Systematic Review of the Literature
Authors: Nour Daoud
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Patriarchy continues to thrive in Jordan where male-controlled values are still entrenched in a society that is suffering from upsetting percentages of Gender-based Violence (GBV). This paper is a systematic review of the literature with an attempt to evaluate and interpret all available research evidence relevant to determining the extent to which patriarchy contributes to the occurrence, re-occurrence, and continuation of GBV in Jordan. Twenty-one (21) full-text articles were selected for the in-depth review due to meeting the established criteria for inclusion. 81 percent of articles included primary data while 19 percent included secondary data. Analysis of data was based on a specific extraction form that was developed using the ‘Excel’ to respond to the main goal of the paper. Interpretation of data was in light of the theorization of different feminism schools on the relationship between patriarchy and gender-based violence. Findings show that 33 percent of the selected articles affirm that the patriarchal standpoint best explains the role of patriarchy in the incidence of gender-based violence in Jordan under its three main themes (Honor-based Violence, Intimate Partner Violence and Street Harassment). Apart from the limited number of articles that were found debating this argument and the low percentage of articles that acknowledged the role of patriarchy in the incidence of gender-based violence in Jordan, this paper breaks the ice to implement future empirical studies on this subject. Also, it is an invitation for all Jordanian women to unite their efforts in order to eradicate all forms of victimization against them.Keywords: honor-based violence, intimate partner violence, middle-east, street harassment
Procedia PDF Downloads 2163563 Geochemistry and Petrogenesis of Anorogenic Acid Plutonic Rocks of Khanak and Devsar of Southwestern Haryana
Authors: Naresh Kumar, Radhika Sharma, A. K. Singh
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Acid plutonic rocks from the Khanak and Devsar areas of southwestern Haryana were investigated to understand their geochemical and petrogenetic characteristics and tectonic environments. Three dominant rock types (grey, grayish green and pink granites) are the principal geochemical features of Khanak and Devsar areas which reflect the dependencies of their composition on varied geological environment during the anorogenic magmatism. These rocks are enriched in SiO₂, Na₂O+K₂O, Fe/Mg, Rb, Zr, Y, Th, U, REE (Rare Earth Elements) enriched and depleted in MgO, CaO, Sr, P, Ti, Ni, Cr, V and Eu and exhibit a clear affinity to the within-plate granites that were emplaced in an extensional tectonic environment. Chondrite-normalized REE patterns show enriched LREE (Light Rare Earth Elements), moderate to strong negative Eu anomalies and flat heavy REE and grey and grayish green is different from pink granite which is enriched by Rb, Ga, Nb, Th, U, Y and HREE (Heavy Rare Earth Elements) concentrations. The composition of parental magma of both areas corresponds to mafic source contaminated with crustal materials. Petrogenetic modelling suggest that the acid plutonic rocks might have been generated from a basaltic source by partial melting (15-25%) leaving a residue with 35% plagioclase, 25% alkali feldspar, 25% quartz, 7% orthopyroxene, 5% biotite and 3% hornblende. Granites from both areas might be formed from different sources with different degree of melting for grey, grayish green and pink granites.Keywords: A-type granite, anorogenic, Malani igneous suite, Khanak and Devsar
Procedia PDF Downloads 1663562 Yawning Computing Using Bayesian Networks
Authors: Serge Tshibangu, Turgay Celik, Zenzo Ncube
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Road crashes kill nearly over a million people every year, and leave millions more injured or permanently disabled. Various annual reports reveal that the percentage of fatal crashes due to fatigue/driver falling asleep comes directly after the percentage of fatal crashes due to intoxicated drivers. This percentage is higher than the combined percentage of fatal crashes due to illegal/Un-Safe U-turn and illegal/Un-Safe reversing. Although a relatively small percentage of police reports on road accidents highlights drowsiness and fatigue, the importance of these factors is greater than we might think, hidden by the undercounting of their events. Some scenarios show that these factors are significant in accidents with killed and injured people. Thus the need for an automatic drivers fatigue detection system in order to considerably reduce the number of accidents owing to fatigue.This research approaches the drivers fatigue detection problem in an innovative way by combining cues collected from both temporal analysis of drivers’ faces and environment. Monotony in driving environment is inter-related with visual symptoms of fatigue on drivers’ faces to achieve fatigue detection. Optical and infrared (IR) sensors are used to analyse the monotony in driving environment and to detect the visual symptoms of fatigue on human face. Internal cues from drivers faces and external cues from environment are combined together using machine learning algorithms to automatically detect fatigue.Keywords: intelligent transportation systems, bayesian networks, yawning computing, machine learning algorithms
Procedia PDF Downloads 4493561 Effect of Genuine Missing Data Imputation on Prediction of Urinary Incontinence
Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno
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Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index
Procedia PDF Downloads 1603560 Numerical Study on the Flow around a Steadily Rotating Spring: Understanding the Propulsion of a Bacterial Flagellum
Authors: Won Yeol Choi, Sangmo Kang
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The propulsion of a bacterial flagellum in a viscous fluid has attracted many interests in the field of biological hydrodynamics, but remains yet fully understood and thus still a challenging problem. In this study, therefore, we have numerically investigated the flow around a steadily rotating micro-sized spring to further understand such bacterial flagellum propulsion. Note that a bacterium gains thrust (propulsive force) by rotating the flagellum connected to the body through a bio motor to move forward. For the investigation, we convert the spring model from the micro scale to the macro scale using a similitude law (scale law) and perform simulations on the converted macro-scale model using a commercial software package, CFX v13 (ANSYS). To scrutinize the propulsion characteristics of the flagellum through the simulations, we make parameter studies by changing some flow parameters, such as the pitch, helical radius and rotational speed of the spring and the Reynolds number (or fluid viscosity), expected to affect the thrust force experienced by the rotating spring. Results show that the propulsion characteristics depend strongly on the parameters mentioned above. It is observed that the forward thrust increases in a linear fashion with either of the rotational speed or the fluid viscosity. In addition, the thrust is directly proportional to square of the helical radius and but the thrust force is increased and then decreased based on the peak value to the pitch. Finally, we also present the appropriate flow and pressure fields visualized to support the observations.Keywords: fluid viscosity, hydrodynamics, similitude, propulsive force
Procedia PDF Downloads 3413559 A Modified Nonlinear Conjugate Gradient Algorithm for Large Scale Unconstrained Optimization Problems
Authors: Tsegay Giday Woldu, Haibin Zhang, Xin Zhang, Yemane Hailu Fissuh
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It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms.Keywords: conjugate gradient method, global convergence, large scale optimization, sufficient descent property
Procedia PDF Downloads 1903558 The Factors Affecting on Promoting Productivity from Nurses' View
Authors: Mahnaz Sanjari, Sedigheh Salemi, Mohammad Mirzabeigi
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Nowadays, the world is facing a crisis of workforce and one of the most striking examples is the shortage of nurses. Nursing workforce productivity is related by various factors such as absenteeism, professional effectiveness and quality care. This cross-sectional study was conducted in 700 nurses who work in government hospitals from 35 hospitals of 9 provinces in Iran. The study was approved by the Nursing Council and was carried out with the authorization of the Research Ethics Committee. The questionnaire included 33 questions and 4 sub categories such as human resource, education and management. The reliability was evaluated by Cronbach's alpha (α=0/85). Statistical analyzes were performed, using SPSS version 16. The result showed that nurses emphasized on "respect to nurse-to-bed ratio" and less importance item was "using less experienced nurse". In addition, another important factor in clinical productivity is "Proper physical structure and amenities","good communication with colleagues" and "having good facilities". Also, "human resources at all levels of standard", "promoting on merit" and "well defined relationship in health system" are another important factors in productivity from nurse` view. The main managerial factor is "justice between employees" and the main educational component of productivity is “updating nursing knowledge”. The results show that more than half of the participants emphasized on the management and educational factors. Productivity as one of the main part of the health care quality leads to appropriate use of human and organizational resources, reduce cost services, and organizational development.Keywords: productivity, nursing services, workforce, cost services
Procedia PDF Downloads 3373557 Corrosion Response of Friction Stir Processed Mg-Zn-Zr-RE Alloy
Authors: Vasanth C. Shunmugasamy, Bilal Mansoor
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Magnesium alloys are increasingly being considered for structural systems across different industrial sectors, including precision components of biomedical devices, owing to their high specific strength, stiffness and biodegradability. However, Mg alloys exhibit a high corrosion rate that restricts their application as a biomaterial. For safe use as biomaterial, it is essential to control their corrosion rates. Mg alloy corrosion is influenced by several factors, such as grain size, precipitates and texture. In Mg alloys, microgalvanic coupling between the α-Mg matrix and secondary precipitates can exist, which results in an increased corrosion rate. The present research addresses this challenge by engineering the microstructure of a biodegradable Mg–Zn–RE–Zr alloy by friction stir processing (FSP), a severe plastic deformation process. The FSP-processed Mg alloys showed improved corrosion resistance and mechanical properties. FSPed Mg alloy showed refined grains, a strong basal texture and broken and uniformly distributed secondary precipitates in the stir zone. Mg, alloy base material, exposed to In vitro corrosion medium showed micro galvanic coupling between precipitate and matrix, resulting in the unstable passive layer. However, FS processed alloy showed uniform corrosion owing to stable surface film formation. The stable surface film is attributed to refined grains, preferred texture and distribution of precipitates. The research results show promising potential for Mg alloy to be developed as a biomaterial.Keywords: biomaterials, severe plastic deformation, magnesium alloys, corrosion
Procedia PDF Downloads 243556 Handling Patient's Supply during Inpatient Stay: Using Lean Six Sigma Techniques to Implement a Comprehensive Medication Handling Program
Authors: Erika Duggan
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A Major Hospital had identified that there was no standard process for handling a patient’s medication that they brought with them to the hospital. It was also identified that each floor was handling the patient’s medication differently and storing it in multiple locations. Based on this disconnect many patients were leaving the hospital without their medication. The project team was tasked with creating a cohesive process to send a patient’s unneeded medication home on admission, storing any of the patient’s medication that could not be sent home, storing any of the patient’s medication for inpatient administration, and sending all of the patient’s medication home on discharge. The project team consisted of pharmacists, RNs, LPNs, members from nursing informatics and a project engineer and followed a DMAIC framework. Working together observations were performed to identify what was working and not working on the different floors which resulted in process maps. Using the multidisciplinary team, brainstorming, including affinity diagramming and other lean six sigma techniques, the best process for receiving, storing, and returning the medication was created. It was highlighted that being able to track the medication throughout the patient’s stay would be beneficial and would help make sure the medication left with the patient on discharge. Using an automated medications dispensing system would help store, and track patient’s medications. Also, the use of a specific order that would show up on the discharge instructions would assist the front line staff in retrieving the medication from a set location and sending it home with the patient. This new process will effectively streamline the admission and discharge process for patients who brought their medication with them as well as effectively tracking the medication during the patient’s stay. As well as increasing patient safety as it relates to medication administration.Keywords: lean six sigma, medication dispensing, process improvement, process mapping
Procedia PDF Downloads 2493555 Multicriteria for Optimal Land Use after Mining
Authors: Carla Idely Palencia-Aguilar
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Mining in Colombia represents around 2% of the GDP (USD 8 billion in 2018), with main productions represented by coal, nickel, gold, silver, emeralds, iron, limestone, gypsum, among others. Sand and Gravel had been decreasing its participation of the GDP with a reduction of 33.2 million m3 in 2015, to 27.4 in 2016, 22.7 in 2017 and 15.8 in 2018, with a consumption of approximately 3 tons/inhabitant. However, with the new government policies it is expected to increase in the following years. Mining causes temporary environmental impacts, once restoration and rehabilitation takes place, social, environmental and economic benefits are higher than the initial state. A way to demonstrate how the mining interventions had contributed to improve the characteristics of the region after sand and gravel mining, the NDVI (Normalized Difference Vegetation Index) from MODIS and ASTER were employed. The histograms show not only increments of vegetation in the area (8 times higher), but also topographies similar to the ones before the intervention, according to the application for sustainable development selected: either agriculture, forestry, cattle raising, artificial wetlands or do nothing. The decision was based upon a Multicriteria analysis for optimal land use, with three main variables: geostatistics, evapotranspiration and groundwater characteristics. The use of remote sensing, meteorological stations, piezometers, sunphotometers, geoelectric analysis among others; provide the information required for the multicriteria decision. For cattle raising and agricultural applications (where various crops were implemented), conservation of products were tested by means of nanotechnology. The results showed a duration of 2 years with no chemicals added for preservation and concentration of vitamins of the tested products.Keywords: ASTER, Geostatistics, MODIS, Multicriteria
Procedia PDF Downloads 1193554 Development of Methods for Plastic Injection Mold Weight Reduction
Authors: Bita Mohajernia, R. J. Urbanic
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Mold making techniques have focused on meeting the customers’ functional and process requirements; however, today, molds are increasing in size and sophistication, and are difficult to manufacture, transport, and set up due to their size and mass. Presently, mold weight saving techniques focus on pockets to reduce the mass of the mold, but the overall size is still large, which introduces costs related to the stock material purchase, processing time for process planning, machining and validation, and excess waste materials. Reducing the overall size of the mold is desirable for many reasons, but the functional requirements, tool life, and durability cannot be compromised in the process. It is proposed to use Finite Element Analysis simulation tools to model the forces, and pressures to determine where the material can be removed. The potential results of this project will reduce manufacturing costs. In this study, a light weight structure is defined by an optimal distribution of material to carry external loads. The optimization objective of this research is to determine methods to provide the optimum layout for the mold structure. The topology optimization method is utilized to improve structural stiffness while decreasing the weight using the OptiStruct software. The optimized CAD model is compared with the primary geometry of the mold from the NX software. Results of optimization show an 8% weight reduction while the actual performance of the optimized structure, validated by physical testing, is similar to the original structure.Keywords: finite element analysis, plastic injection molding, topology optimization, weight reduction
Procedia PDF Downloads 2813553 Covalently Conjugated Gold–Porphyrin Nanostructures
Authors: L. Spitaleri, C. M. A. Gangemi, R. Purrello, G. Nicotra, G. Trusso Sfrazzetto, G. Casella, M. Casarin, A. Gulino
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Hybrid molecular–nanoparticle materials, obtained with a bottom-up approach, are suitable for the fabrication of functional nanostructures showing structural control and well-defined properties, i.e., optical, electronic or catalytic properties, in the perspective of applications in different fields of nanotechnology. Gold nanoparticles (Au NPs) exhibit important chemical, electronic and optical properties due to their size, shape and electronic structures. In fact, Au NPs containing no more than 30-40 atoms are only luminescent because they can be considered as large molecules with discrete energy levels, while nano-sized Au NPs only show the surface plasmon resonance. Hence, it appears that gold nanoparticles can alternatively be luminescent or plasmonic, and this represents a severe constraint for their use as an optical material. The aim of this work was the fabrication of nanoscale assembly of Au NPs covalently anchored to each other by means of novel bi-functional porphyrin molecules that work as bridges between different gold nanoparticles. This functional architecture shows a strong surface plasmon due to the Au nanoparticles and a strong luminescence signal coming from porphyrin molecules, thus, behaving like an artificial organized plasmonic and fluorescent network. The self-assembly geometry of this porphyrin on the Au NPs was studied by investigation of the conformational properties of the porphyrin derivative at the DFT level. The morphology, electronic structure and optical properties of the conjugated Au NPs – porphyrin system were investigated by TEM, XPS, UV–vis and Luminescence. The present nanostructures can be used for plasmon-enhanced fluorescence, photocatalysis, nonlinear optics, etc., under atmospheric conditions since our system is not reactive to air nor water and does not need to be stored in a vacuum or inert gas.Keywords: gold nanoparticle, porphyrin, surface plasmon resonance, luminescence, nanostructures
Procedia PDF Downloads 1443552 Comparison of Serum Levels of Secreted Frizzler Protein 5 in Patients with Type 2 Diabetes Mellitus Treated and Not Treated with Metformin
Authors: Irma Gabriela Lopez-Moreno, Elva Perez-Luque, Herlinda Aguilar-Zavala
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Introduction: Type 2 Diabetes Mellitus (T2DM) is characterized by combination of insulin resistance and deterioration of insulin secretion. Sfrp5 is a protein that antagonizes Wnt5a proteins by preventing it from reaching its receptor and activating the Wnt/β-catenin signaling pathway, this pathway is one of the most important regulators of adipogenesis. Although metformin decreases glucose levels its mechanisms of action are not fully known but it has been implicated in the inhibition of the Wnt/β-catenin signaling pathway. Objective: The objective was evaluating the effects of metformin on serum levels of Sfrp5 in patients with T2DM treated and not treated with metformin. Methods: Two groups of patients were selected: one group of T2DM patients treated with metformin (n = 35) and another group of subjects with recent diagnosis of T2DM untreated (n = 35) with a mean age of 48 ± 9 years. In these subjects anthropometric measures were taken as weight, height, waist and hip circumference, were calculated the percentage of body fat, visceral fat and muscle mass. In addition, were measured glucose levels, lipid profile, adiponectin and Sfrp5. Results: Sfrp5 were higher in metformin-treated patients compared to the untreated group (19.9 vs 13.6 ng/mL p < 0.001), a negative correlation was found between Sfrp5 levels and total cholesterol levels (r= -0.25, p = 0.03) and percentage of visceral fat (r = -0.26, p = 0.03) and a positive correlation with HDL cholesterol levels (r = 0.31, p = 0.01) and adiponectin (r=0.65, p = < 0.001). Conclusions: The findings show that metformin consumption increased levels of Sfrp5, which may lead to a decrease in the activation of the WNT/β-catenin pathway impacting on adipogenesis.Keywords: adiponectin, diabetes, metformin, Sfrp5
Procedia PDF Downloads 1663551 Analysis of the Effective Components on the Performance of the Public Sector in Iran
Authors: Mahsa Habibzadeh
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The function is defined as the process of systematic and systematic measurement of the components of how each task is performed and determining their potential for improvement in accordance with the specific standards of each component. Hence, evaluation is the basis for the improvement of organizations' functional excellence and the move towards performance excellence depends on performance improvement planning. Because of the past two decades, the public sector system has undergone dramatic changes. The purpose of such developments is often to overcome the barriers of the bureaucratic system, which impedes the efficient use of limited resources. Implementing widespread changes in the public sector of developed and even developing countries has led the process of developments to be addressed by many researchers. In this regard, the present paper has been carried out with the approach of analyzing the components that affect the performance of the public sector in Iran. To achieve this goal, indicators that affect the performance of the public sector and the factors affecting the improvement of its accountability have been identified. The research method in this research is descriptive and analytical. A statistical population of 120 people consists of managers and employees of the public sector in Iran. The questionnaires were distributed among them and analyzed using SPSS and LISREL software. The obtained results indicate that the results of the research findings show that between responsibilities there is a significant relationship between participation of managers and employees, legality, justice and transparency of specialty and competency, participation in public sector functions. Also, the significant coefficient for the liability variable is 3.31 for justice 2.89 for transparency 1.40 for legality of 2.27 for specialty and competence 2.13 and 5.17 for participation 5.17. Implementing indicators that affect the performance of the public sector can lead to satisfaction of the audience.Keywords: performance, accountability system, public sector, components
Procedia PDF Downloads 2203550 A Study on the Importance and Contributions of Transforming from OEM to ODM in Malaysian Furniture Industry
Authors: Nurul Ain Haron, Saiful Hazmi Bachek, Hafez Zainudin
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This study is aimed to establish the importance and contribution of Original Design Manufacturing (ODM) in Malaysian Furniture Industry and to close the gap between the players in the industry. The study confirms that today’s furniture industry favor Original Equipment Manufacturing (OEM) basis. Thus, resulting in the local industry lacking the expertise of designing furniture to a state of no contest. This study method used consists of literature reviews, observation, questionnaire and sessions of interviews. The result shows that the public has from minimum to almost no knowledge of the term Original Design Manufacturing (ODM) concept and the impact towards our current future industry. The manufacturers however, prefers Original Equipment Manufacturing (OEM) concept due to its easy and fast investment returns with the need of product designing process, while the interviews carried out with the authorized council had some convincing urges of doing their part promoting the awareness through trainings and seminars. Findings show that, in the rush of archiving ODM status needs extensive cooperation from many parties that are authorized council, furniture manufacturers, designers and also the public perceptions of labeling local made goods as the black goat. The current mind set of OEM manufacturers need to be change for industry’s future. As Malaysia’s living status constantly increases, so will the demands of a better salary. If these current issues are not resolved, OEM international buyers will definitely have to shift to some other lower cost manufacturer like China or Taiwan. When vendors stopped to order, today’s OEM manufacturers will no longer exist in the future.Keywords: design manufacturing, furniture design, original design manufacturing, original equipment manufacturing
Procedia PDF Downloads 4353549 Drivers of Deforestation in the Colombian Amazon: An Empirical Causal Loop Diagram of Food Security and Land-Use Change
Authors: Jesica López, Deniz Koca, Asaf Tzachor
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In 2016 the historic peace accord between the Colombian government and the Revolutionary Armed Forces of Colombia (FARC) had no strong mechanism for managing changes to land use and the environment. Since the end of a 60-year conflict in Colombia, large areas of forest in the Amazon region have been rapidly converted to agricultural uses, most recently by cattle ranching. This suggests that the peace agreement presents a threat to the conservation of the country's rainforest. We analyze the effects of cattle ranching as a driver and accelerator of deforestation from a systemic perspective, focusing on two key leverage points the legal and illegal activities involved in the cattle ranching practices. We map and understand the inherent dynamic complexity of deforestation, including factors such as land policy instruments, national strategy to tackle deforestation, land use nexus with Amazonian food systems, and loss of biodiversity. Our results show that deforestation inside Colombian Protected Areas (PAs) in the Amazon region and the surrounding buffer areas has accelerated with the onset of peace. By using a systems analysis approach, we contextualized the competition of land between cattle ranching and the need to protect tropical forests and their biodiversity loss. We elaborate on future recommendations for land use management decisions making suggest the inclusion of an Amazonian food system, interconnecting and visualizing the synergies between sustainable development goals, climate action (SDG 13) and life on land (SDG 15).Keywords: tropical rainforest, deforestation, sustainable land use, food security, Colombian Amazon
Procedia PDF Downloads 843548 Comparative Study of Tensile Properties of Cast and Hot Forged Alumina Nanoparticle Reinforced Composites
Authors: S. Ghanaraja, Subrata Ray, S. K. Nath
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Particle reinforced Metal Matrix Composite (MMC) succeeds in synergizing the metallic matrix with ceramic particle reinforcements to result in improved strength, particularly at elevated temperatures, but adversely it affects the ductility of the matrix because of agglomeration and porosity. The present study investigates the outcome of tensile properties in a cast and hot forged composite reinforced simultaneously with coarse and fine particles. Nano-sized alumina particles have been generated by milling mixture of aluminum and manganese dioxide powders. Milled particles after drying are added to molten metal and the resulting slurry is cast. The microstructure of the composites shows good distribution of both the size categories of particles without significant clustering. The presence of nanoparticles along with coarser particles in a composite improves both strength and ductility considerably. Delay in debonding of coarser particles to higher stress is due to reduced mismatch in extension caused by increased strain hardening in presence of the nanoparticles. However, higher addition of powder mix beyond a limit results in deterioration of mechanical properties, possibly due to clustering of nanoparticles. The porosity in cast composite generally increases with the increasing addition of powder mix as observed during process and on forging it has got reduced. The base alloy and nanocomposites show improvement in flow stress which could be attributed to lowering of porosity and grain refinement as a consequence of forging.Keywords: aluminium, alumina, nano-particle reinforced composites, porosity
Procedia PDF Downloads 2393547 Conjugated Linoleic Acid (CLA) Health Benefits and Sources
Authors: Hilal Ahmad Punoo
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Conjugated linoleic acid (CLA) is a mixture of positional and geometric isomers of octadecadienoic acid with two conjugated double bonds. Of more than a dozen isomers of CLA found naturally in dairy and meat products from ruminants, c-9, t-11 and t-10, c-12 are the two isomers with known physiological importance, including anticarcinogenic, antidiabetic, antilipogenic, and antiatherosclerotic effects. Conjugated linoleic acids (CLA) may influence the onset and severity of several chronic diseases, including various cancers, atherosclerosis, obesity, bone density loss, and diabetes. These findings are of special interest to the agriculture community, because dietary sources of CLA are almost exclusively beef and dairy products. Thus, a better understanding of the specific isomers and mechanisms responsible for these positive effects of CLA on human health would be both prudent and economically beneficial. To date, research related to the advantages of CLA consumption on human health has been conducted using experimental laboratory animals and cell culture systems. These data consistently show that relatively low levels of CLA can influence risk of cancer. Further, very recent investigations suggest that the predominate CLA isoform (cis-9, trans-11 CLA or rumenic acid) found in beef and milk fat possesses anticarcinogenic effects but does not alter body composition; the trans-10, cis-12 CLA has been shown to inhibit lipogenesis. Clearly, further work, especially using human subjects, will be required to characterize the potential benefits of CLA consumption on human health. Moreover, we suggest that foods naturally containing high amounts of CLA (e.g., beef and dairy products) be considered as meeting the definition of functional foods.Keywords: conjugated linoleic acid, potential health benefits, fats, animals, humans
Procedia PDF Downloads 3013546 Solving the Economic Load Dispatch Problem Using Differential Evolution
Authors: Alaa Sheta
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Economic Load Dispatch (ELD) is one of the vital optimization problems in power system planning. Solving the ELD problems mean finding the best mixture of power unit outputs of all members of the power system network such that the total fuel cost is minimized while sustaining operation requirements limits satisfied across the entire dispatch phases. Many optimization techniques were proposed to solve this problem. A famous one is the Quadratic Programming (QP). QP is a very simple and fast method but it still suffer many problem as gradient methods that might trapped at local minimum solutions and cannot handle complex nonlinear functions. Numbers of metaheuristic algorithms were used to solve this problem such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). In this paper, another meta-heuristic search algorithm named Differential Evolution (DE) is used to solve the ELD problem in power systems planning. The practicality of the proposed DE based algorithm is verified for three and six power generator system test cases. The gained results are compared to existing results based on QP, GAs and PSO. The developed results show that differential evolution is superior in obtaining a combination of power loads that fulfill the problem constraints and minimize the total fuel cost. DE found to be fast in converging to the optimal power generation loads and capable of handling the non-linearity of ELD problem. The proposed DE solution is able to minimize the cost of generated power, minimize the total power loss in the transmission and maximize the reliability of the power provided to the customers.Keywords: economic load dispatch, power systems, optimization, differential evolution
Procedia PDF Downloads 2753545 Land Suitability Prediction Modelling for Agricultural Crops Using Machine Learning Approach: A Case Study of Khuzestan Province, Iran
Authors: Saba Gachpaz, Hamid Reza Heidari
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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.Keywords: land suitability, machine learning, random forest, sustainable agriculture
Procedia PDF Downloads 723544 Effect of Knowledge of Bubble Point Pressure on Estimating PVT Properties from Correlations
Authors: Ahmed El-Banbi, Ahmed El-Maraghi
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PVT properties are needed as input data in all reservoir, production, and surface facilities engineering calculations. In the absence of PVT reports on valid reservoir fluid samples, engineers rely on PVT correlations to generate the required PVT data. The accuracy of PVT correlations varies, and no correlation group has been found to provide accurate results for all oil types. The effect of inaccurate PVT data can be significant in engineering calculations and is well documented in the literature. Bubble point pressure can sometimes be obtained from external sources. In this paper, we show how to utilize the known bubble point pressure to improve the accuracy of calculated PVT properties from correlations. We conducted a systematic study using around 250 reservoir oil samples to quantify the effect of pre-knowledge of bubble point pressure. The samples spanned a wide range of oils, from very volatile oils to black oils and all the way to low-GOR oils. A method for shifting both undersaturated and saturated sections of the PVT properties curves to the correct bubble point is explained. Seven PVT correlation families were used in this study. All PVT properties (e.g., solution gas-oil ratio, formation volume factor, density, viscosity, and compressibility) were calculated using the correct bubble point pressure and the correlation estimated bubble point pressure. Comparisons between the calculated PVT properties and actual laboratory-measured values were made. It was found that pre-knowledge of bubble point pressure and using the shifting technique presented in the paper improved the correlation-estimated values by 10% to more than 30%. The most improvement was seen in the solution gas-oil ratio and formation volume factor.Keywords: PVT data, PVT properties, PVT correlations, bubble point pressure
Procedia PDF Downloads 533543 Optimal Design of Storm Water Networks Using Simulation-Optimization Technique
Authors: Dibakar Chakrabarty, Mebada Suiting
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Rapid urbanization coupled with changes in land use pattern results in increasing peak discharge and shortening of catchment time of concentration. The consequence is floods, which often inundate roads and inhabited areas of cities and towns. Management of storm water resulting from rainfall has, therefore, become an important issue for the municipal bodies. Proper management of storm water obviously includes adequate design of storm water drainage networks. The design of storm water network is a costly exercise. Least cost design of storm water networks assumes significance, particularly when the fund available is limited. Optimal design of a storm water system is a difficult task as it involves the design of various components, like, open or closed conduits, storage units, pumps etc. In this paper, a methodology for least cost design of storm water drainage systems is proposed. The methodology proposed in this study consists of coupling a storm water simulator with an optimization method. The simulator used in this study is EPA’s storm water management model (SWMM), which is linked with Genetic Algorithm (GA) optimization method. The model proposed here is a mixed integer nonlinear optimization formulation, which takes care of minimizing the sectional areas of the open conduits of storm water networks, while satisfactorily conveying the runoff resulting from rainfall to the network outlet. Performance evaluations of the developed model show that the proposed method can be used for cost effective design of open conduit based storm water networks.Keywords: genetic algorithm (GA), optimal design, simulation-optimization, storm water network, SWMM
Procedia PDF Downloads 2373542 Antioxidant Effects of C-Phycocyanin on Oxidized Astrocyte in Brain Injury Using 2D and 3D Neural Nanofiber Tissue Model
Authors: Seung Ju Yeon, Seul Ki Min, Jun Sang Park, Yeo Seon Kwon, Hoo Cheol Lee, Hyun Jung Shim, Il-Doo Kim, Ja Kyeong Lee, Hwa Sung Shin
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In brain injury, depleting oxidative stress is the most effective way to reduce the brain infarct size. C-phycocyanin (C-Pc) is a well-known antioxidant protein that has neuroprotective effects obtained from green microalgae. Astrocyte is glial cell that supports the nerve cell such as neuron, which account for a large portion of the brain. In brain injury, such as ischemia and reperfusion, astrocyte has an important rule that overcomes the oxidative stress and protect from brain reactive oxygen species (ROS) injury. However little is known about how C-Pc regulates the anti-oxidants effects of astrocyte. In this study, when the C-Pc was treated in oxidized astrocyte, we confirmed that inflammatory factors Interleukin-6 and Interleukin-3 were increased and antioxidants enzyme, Superoxide dismutase (SOD) and catalase was upregulated, and neurotrophic factors, brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) was alleviated. Also, it was confirmed to reduce infarct size of the brain in ischemia and reperfusion because C-Pc has anti-oxidant effects in middle cerebral artery occlusion (MCAO) animal model. These results show that C-Pc can help astrocytes lead neuroprotective activities in the oxidative stressed environment of the brain. In summary, the C-PC protects astrocytes from oxidative stress and has anti-oxidative, anti-inflammatory, neurotrophic effects under ischemic situations.Keywords: c-phycocyanin, astrocyte, reactive oxygen species, ischemia and reperfusion, neuroprotective effect
Procedia PDF Downloads 3093541 Analyzing the Impact of Spatio-Temporal Climate Variations on the Rice Crop Calendar in Pakistan
Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad
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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.Keywords: Landsat NDVI, panel models, temperature, rainfall
Procedia PDF Downloads 1953540 Convertible Lease, Risky Debt and Financial Structure with Growth Option
Authors: Ons Triki, Fathi Abid
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The basic objective of this paper is twofold. It resides in designing a model for a contingent convertible lease contract that can ensure the financial stability of a company and recover the losses of the parties to the lease in the event of default. It also aims to compare the convertible lease contract on inefficiencies resulting from the debt-overhang problem and asset substitution with other financing policies. From this perspective, this paper highlights the interaction between investments and financing policies in a dynamic model with existing assets and a growth option where the investment cost is financed by a contingent convertible lease and equity. We explore the impact of the contingent convertible lease on the capital structure. We also check the reliability and effectiveness of the use of the convertible lease contract as a means of financing. Findings show that the rental convertible contract with a sufficiently high conversion ratio has less severe inefficiencies arising from risk-shifting and debt overhang than those entailed by risky debt and pure-equity financing. The problem of underinvestment pointed out by Mauer and Ott (2000) and the problem of overinvestment mentioned by Hackbarth and Mauer (2012) may be reduced under contingent convertible lease financing. Our findings predict that the firm value under contingent convertible lease financing increases globally with asset volatility instead of decreasing with business risk. The study reveals that convertible leasing contracts can stand for a reliable solution to ensure the lessee and quickly recover the counterparties of the lease upon default.Keywords: contingent convertible lease, growth option, debt overhang, risk-shifting, capital structure
Procedia PDF Downloads 623539 The Effects of Continuous and Interval Aerobic Exercises with Moderate Intensity on Serum Levels of Glial Cell Line-Derived Neurotrophic Factor and Aerobic Capacity in Obese Children
Authors: Ali Golestani, Vahid Naseri, Hossein Taheri
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Recently, some of studies examined the effect of exercise on neurotrophic factors influencing the growth, protection, plasticity and function in central and peripheral nerve cells. The aim of this study was to investigate the effects of continuous and interval aerobic exercises with moderate intensity on serum levels of glial cell line-derived neurotrophic factor (GDNF) and aerobic capacity in obese children. 21 obese students with an average age of 13.6 ± 0.5 height 171 ± 5 and BMI 32 ± 1.2 were divided randomly to control, continuous aerobic and interval aerobic groups. Training protocol included continuous or interval aerobic exercises with moderate intensity 50-65%MHR, three times per week for 10 weeks. 48 hours before and after executing of protocol, blood samples were taken from the participants and their GDNF serum levels were measured by ELISA. Aerobic power was estimated using Shuttle-run test. T-test results indicated a small increase in their GDNF serum levels, which was not statistically significant (p =0.11). In addition, the results of ANOVA did not show any significant difference between continuous and interval aerobic training on the serum levels of their GDNF but their aerobic capacity significantly increased (p =0.012). Although continuous and interval aerobic exercise improves aerobic power in obese children, they had no significant effect on their serum levels of GDNF.Keywords: aerobic power, continuous aerobic training, glial cell line-derived neurotrophic factor (GDNF), interval aerobic training, obese children
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