Search results for: detection of identifying

Authors: Emmanuel Iyamuremye

Abstract:

Extreme rainfall events have caused significant damage to agriculture, ecology, and infrastructure, disruption of human activities, injury, and loss of life. They also have significant social, economic, and environmental consequences because they considerably damage urban as well as rural areas. Early detection of extreme maximum rainfall helps to implement strategies and measures, before they occur, hence mitigating the consequences. Extreme value theory has been used widely in modeling extreme rainfall and in various disciplines, such as financial markets, the insurance industry, failure cases. Climatic extremes have been analyzed by using either generalized extreme value (GEV) or generalized Pareto (GP) distributions, which provides evidence of the importance of modeling extreme rainfall from different regions of the world. In this paper, we focused on Peak Over Thresholds approach, where the Poisson-generalized Pareto distribution is considered as the proper distribution for the study of the exceedances. This research also considers the use of the generalized Pareto (GP) distribution with a Poisson model for arrivals to describe peaks over a threshold. The research used statistical techniques to fit models that used to predict extreme rainfall in Kigali. The results indicate that the proposed Poisson-GP distribution provides a better fit to maximum monthly rainfall data. Further, the Poisson-GP models are able to estimate various return levels. The research also found a slow increase in return levels for maximum monthly rainfall for higher return periods, and further, the intervals are increasingly wider as the return period is increasing.

Keywords: exceedances, extreme value theory, generalized Pareto distribution, Poisson generalized Pareto distribution

Procedia PDF Downloads 134

Authors: Tamunotonye Mayowa Braide, Isaac Oluwatayo

Abstract:

This study investigates multidimensional poverty, and its correlates among rural households in Sekhukhune and Capricorn District municipalities (SDM & CDM) in Limpopo Province, South Africa. Primary data were collected from 407 rural households selected through purposive and simple random sampling techniques. Analytical techniques employed include descriptive statistics, principal component analysis (PCA), and the Alkire Foster (A-F) methodology. The results of the descriptive statistics showed there are more females (66%) than males (34%) in rural areas of Limpopo Province, with about 45% of them having secondary school education as the highest educational level attained and only about 3% do not have formal education. In the analysis of deprivation, eight dimensions of deprivation, constructed from 21 variables, were identified using the PCA. These dimensions include type and condition of dwelling water and sanitation, educational attainment and income, type of fuel for cooking and heating, access to clothing and cell phone, assets and fuel for light, health condition, crowding, and child health. In identifying the poor with poverty cut-off (0.13) of all indicators, about 75.9% of the rural households are deprived in 25% of the total dimensions, with the adjusted headcount ratio (M0) being 0.19. Multidimensional poverty estimates showed higher estimates of poor rural households with 71%, compared to 29%, which fall below the income poverty line. The study conducted poverty decomposition, using sub-groups within the area by examining regions and household characteristics. In SDM, there are more multidimensionally poor households than in CDM. The water and sanitation dimension is the largest contributor to the multidimensional poverty index (MPI) in rural areas of Limpopo Province. The findings can, therefore, assist in better design of welfare policy and target poverty alleviation programs and as well help in efficient resource allocation at the provincial and local municipality levels.

Keywords: Alkire-Foster methodology, Limpopo province, multidimensional poverty, principal component analysis, South Africa

Procedia PDF Downloads 163

Authors: A. Fordham, A. Hudson

Abstract:

Background: Studies have suggested 16-25% of normotensive trauma patients with no clinical signs of shock have abnormal lactate and BD readings evidencing shock; a phenomenon known as occult hypoperfusion (OH). In light of the scarce quantity of evidence currently documenting OH, this study aimed to identify the prevalence of OH in the pre-hospital setting and explore ways to improve its identification and management. Methods: A quantitative retrospective data analysis was carried out on 75 sets of patient records for trauma patients treated by Kent Surrey Sussex Air Ambulance Trust between November 2013 and October 2014. The KSS HEMS notes and subsequent ED notes were collected. Trends between patients’ SBP on the scene, whether or not they received PRBCs on the scene as well as lactate and BD readings in the ED were assessed. Patients’ KSS HEMS notes written by the HEMS crew were also reviewed and recorded. Results: -Suspected OH was identified in 7% of the patients who did not receive PRBCs in the pre-hospital phase. -SBP heavily influences the physicians’ decision of whether or not to transfuse PRBCs in the pre-hospital phase. Preliminary conclusions: OH is an under-studied and underestimated phenomenon. We suggest a prospective trial is carried out to evaluate whether detecting trauma patients’ tissue perfusion status in the pre-hospital phase using portable devices capable of measuring serum BD and/or lactate could aid more accurate detection and management of all haemorrhaging trauma patients, including patients with OH.

Keywords: occult hypoperfusion, PRBC transfusion, point of care testing, pre-hospital emergency medicine, trauma

Procedia PDF Downloads 358

Authors: Miguel García-Ferrús, Ana González, María A. Ferrús

Abstract:

The most demanded organic foods worldwide are those that are consumed fresh, such as fruits and vegetables. However, there is a knowledge gap about some aspects of organic food microbiological quality and safety. Organic fruits and vegetables are more exposed to pathogenic microorganisms due to surface contact with natural fertilizers such as animal manure, wastes and vermicompost used during farming. It has been suggested that some emergent pathogens, such as Helicobacter pylori or Arcobacter spp., could reach humans through the consumption of raw or minimally processed vegetables. Therefore, the objective of this work was to study the contamination of organic fresh green leafy vegetables by Arcobacter spp. and Helicobacter pylori. For this purpose, a total of 24 vegetable samples, 13 lettuce and 11 spinach were acquired from 10 different ecological supermarkets and greengroceries and analyzed by culture and PCR. Arcobacter spp. was detected in 5 samples (20%) by PCR, 4 spinach and one lettuce. One spinach sample was found to be also positive by culture. For H. pylori, the H. pylori VacA gene-specific band was detected in 12 vegetable samples (50%), 10 lettuces and 2 spinach. Isolation in the selective medium did not yield any positive result, possibly because of low contamination levels together with the presence of the organism in its viable but non-culturable form. Results showed significant levels of H. pylori and Arcobacter contamination in organic vegetables that are generally consumed raw, which seems to confirm that these foods can act as transmission vehicles to humans.

Keywords: Arcobacter sp., Helicobacter pylori, Organic Vegetables, Polymerase Chain Reaction (PCR)

Procedia PDF Downloads 163

Authors: Durata Haciu, Elif Sena Tekin, Gokce Ozturk, Patricia Ramey Balcı

Abstract:

Coastal zones are under increasing threat due to anthropogenic activities that introduce considerable pollutants such as heavy metals into marine ecosystems. As part of a larger experimental study examining species responses to contaminated marine sediments, surface sediments (top 5cm) were analysed for major trace elements at three locations in Istanbul Straight. Samples were randomly collected by divers (May 2018) using hand-corers from Istinye (n=4), Garipce (n=10) and Poyrazköy (n=6), at water depths of 4-8m. Twelve metals were examined: As, arsenic; Pb, lead; Cd, cadmium; Cr, chromium; Cu, Copper; Fe, Iron; Ni, Nickel; Zn, Zinc; V, vanadium; Mn, Manganese; Ba, Barium; and Ag, silver by wavelength-dispersive X-ray fluorescence spectrometry (WDXRF) and Inductively Coupled Plasma/Mass Spectroscopy (ICP/MS). Preliminary results indicate that the average concentrations of metals (mg kg⁻¹) varied considerably among locations. In general, concentrations were relatively lower at Garipce compared to either Istinye or Poyrazköy. For most metals mean concentrations were highest at Poyrazköy and Ag and Cd were below detection limits (exception= Ag in a few samples). While Cd and As were undetected in all stations, the concentrations of Fe and Ni fall in the criteria of moderately polluted range and the rest of the metals in the range of low polluted range as compared to Effects Range Low (ERL) and Effects Range median (ERM) values determined by US Environmental Protection Agency (EPA).

Keywords: effect-range classification, ICP/MS, marine sediments, XRF

Procedia PDF Downloads 130

Authors: Lucia Vodanovic, Bryan Pirolli

Abstract:

The London College of Communication is one of the only universities in the world to offer a lifestyle journalism master’s degree. A hybrid originally constructed largely out of a generic journalism program crossed with numerous cultural studies approaches, the degree has developed into a leading lifestyle journalism education attracting students worldwide. This research project seeks to present a framework for structuring the degree as well as to understand how students in this emerging field of study value the program. While some researchers have addressed questions about journalism and higher education, none have looked specifically at the increasingly important genre of lifestyle journalism, which Folker Hanusch defines as including notions of consumerism and critique among other identifying traits. Lifestyle journalism, itself poorly researched by scholars, can relate to topics including travel, fitness, and entertainment, and as such, arguably a lifestyle journalism degree should prepare students to engage with these topics. This research uses the existing Masters of Arts and Lifestyle Journalism at the London College of Communications as a case study to examine the school’s approach. Furthering Hanusch’s original definition, this master’s program attempts to characterizes lifestyle journalism by a specific voice or approach, as reflected in the diversity of student’s final projects. This framework echoes the ethos and ideas of the university, which focuses on creativity, design, and experimentation. By analyzing the current degree as well as student feedback, this research aims to assist future educators in pursuing the often neglected field of lifestyle journalism. Through a discovery of the unique mix of practical coursework, theoretical lessons, and broad scope of student work presented in this degree program, researchers strive to develop a framework for lifestyle journalism education, referring to Mark Deuze’s ten questions for journalism education development. While Hanusch began the discussion to legitimize the study of lifestyle journalism, this project strives to go one step further and open up a discussion about teaching of lifestyle journalism at the university level.

Keywords: education, journalism, lifestyle, university

Procedia PDF Downloads 304

Authors: Abrha Ybeyn Gebremedhn, Yitea Seneshaw Getahun, Alebachew Shumye Moges, Fikrey Tesfay

Abstract:

Rainfed agriculture in Ethiopia has failed to produce enough food, to achieve the increasing demand for food. Pinpointing the appropriate site for rainwater harvesting (RWH) have a substantial contribution to increasing the available water and enhancing agricultural productivity. The current study related to the identification of the potential RWH sites was conducted at the Chacha watershed central highlands of Ethiopia which is endowed with rugged topography. The Geographic Information System with Analytical Hierarchy Process was used to generate the different maps for identifying appropriate sites for RWH. In this study, 11 factors that determine the RWH locations including slope, soil texture, runoff depth, land cover type, annual average rainfall, drainage density, lineament intensity, hydrologic soil group, antecedent moisture content, and distance to the roads were considered. The overall analyzed result shows that 10.50%, 71.10%, 17.90%, and 0.50% of the areas were found under highly, moderately, marginally suitable, and unsuitable areas for RWH, respectively. The RWH site selection was found highly dependent on a slope, soil texture, and runoff depth; moderately dependent on drainage density, annual average rainfall, and land use land cover; but less dependent on the other factors. The highly suitable areas for rainwater harvesting expansion are lands having a flat topography with a soil textural class of high-water holding capacity that can produce high runoff depth. The application of this study could be a baseline for planners and decision-makers and support any strategy adoption for appropriate RWH site selection.

Keywords: runoff depth, antecedent moisture condition, AHP, weighted overlay, water resource

Procedia PDF Downloads 50

Authors: Waleed A. El-Said, Dina M. Fouad, Mohamed H. Aly, Mohamed A. El-Gahami

Abstract:

Green synthesis of nanomaterials has received increasing attention as an eco-friendly technology in materials science. Here, we have used two types of extractions from green tea leaf (i.e. total extraction and tannin extraction) as reducing agents for a rapid, simple and one step synthesis method of mesoporous silica nanoparticles (MSNPs)/iron oxide (Fe3O4) nanocomposite based on deposition of Fe3O4 onto MSNPs. MSNPs/Fe3O4 nanocomposite were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X-ray, vibrating sample magnetometer, N2 adsorption, and high-resolution transmission electron microscopy. The average mesoporous silica particle diameter was found to be around 30 nm with high surface area (818 m2/gm). MSNPs/Fe3O4 nanocomposite was used for removing lindane pesticide (an environmental hazard material) from aqueous solutions. Fourier transform infrared, UV-vis, High-performance liquid chromatography and gas chromatography techniques were used to confirm the high ability of MSNPs/Fe3O4 nanocomposite for sensing and capture of lindane molecules with high sorption capacity (more than 89%) that could develop a new eco-friendly strategy for detection and removing of pesticide and as a promising material for water treatment application.

Keywords: green synthesis, mesoporous silica, magnetic iron oxide NPs, adsorption Lindane

Procedia PDF Downloads 435

Authors: Orlando Ketebu

Abstract:

Ogbono seed is the seed obtained from African bush mango (Irvingia gabonenesis) and bitter bush mango (Irvingia wombolu). Irvingia gabonenesis is known for its sweet edible pulp while Irvingia wombolu has a bitter pulp. Their seed powder is used in cooking soup known as ogbono soup in Nigeria and in West Africa. The powder thickens when cooked and researches have shown that it has medicinal uses such as lowering cholesterol; aiding weight loss and helps in improving diabetes control. The nutritional composition of the seeds indicated that Irvingia gabonenesis contains 8.60% protein, 13.8% carbohydrate, 2.0% moisture, 1.5% crude fiber, 16.4% ash, and Irvingia wombolu contains 7.38% protein, 25.75% carbohydrate, 11.7% moisture, 0.84% crude fiber, 2.50% ash. Solvent extraction of these seeds has shown that the seed of the two species are oil seeds with approximately 70 % and 52 % for Irvingia gabonenesis and Irvingia wombolu respectively. One major setback using ogbono seed powder in cooking soup is identifying the specie of ogbono seed powder that thickens most within the same cooking condition and how temperature affects the thickness of ogbono seed powder which determines its viscosity and in turn affects the quality of the soup and its nutrients. This research work monitored how the viscosity of ogbono species after being sun dried for one week changes with temperature. The result showed that heating 20 grams of powdered Irvingia gabonenesis and Irvingia wombolu at 30 OC, 45 OC, 55 OC, 65 OC, 75 OC, 85 OC and 95OC respectively in 200 ml beaker mixed with 100 ml of water, the viscosity of both species decreases with increase temperature with Irvingia wombolu having higher average viscosity in Pascal seconds (Pa.s) of 1.059, 1.042, 0.961, 0.778, 0.684, 0.675, and 0.495 at 30 OC, 45 OC, 55 OC, 65 OC, 75 OC, 85 OC and 95 OC respectively compared to Irvingia gabonenesis with result 0.982, 0.920, 0.720, 0.646, 0.597 and 0.446 at 30 OC, 45 OC, 55 OC, 65 OC, 75 OC, 85 OC and 95 OC respectively. Also from the experiment carried out it was found out that the viscosity of both species decreases with ageing of the seeds and the quantity of ogbono seed powder used and amount of water added also affected the viscosity of both species. In conclusion, it was observed that under the same cooking conditions (temperature range, quantity of water added, time and quantity of ogbono seed powder used), Irvingia wombolu had higher viscosity which is a measure of its thickness and quality of nutrients compared to Irvingia gabonenesis and the viscosity of both species decreases with increasing temperature.

Keywords: ogbono seed powder, temperature, viscosity , soup

Procedia PDF Downloads 188

Authors: Biniam Tedros Kahsay, Yohannes Yebabe Tesfay

Abstract:

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

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

Procedia PDF Downloads 56

Authors: Golayeh Yousefi, Mehdi Homaee, Ali Akbar Norouzi

Abstract:

Ongoing monitoring of soil contamination by heavy metals is critical for ecosystem stability and environmental protection, and food security. The conventional methods of determining these soil contaminants are time-consuming and costly. Spectroscopy in the visible near-infrared (VNIR) - short wave infrared (SWIR) region is a rapid, non-destructive, noninvasive, and cost-effective method for assessment of soil heavy metals concentration by studying the spectral properties of soil constituents. The aim of this study is to derive spectral bands and important ranges that are sensitive to heavy metals and can be used to estimate the concentration of these soil contaminants. In other words, the change in the spectral properties of spectrally active constituents of soil can lead to the accurate identification and estimation of the concentration of these compounds in soil. For this purpose, 325 soil samples were collected, and their spectral reflectance curves were evaluated at a range of 350-2500 nm. After spectral preprocessing operations, the partial least-squares regression (PLSR) model was fitted on spectral data to predict the concentration of Cu and Ni. Based on the results, the spectral range of Cu- sensitive spectra were 480, 580-610, 1370, 1425, 1850, 1920, 2145, and 2200 nm, and Ni-sensitive ranges were 543, 655, 761, 1003, 1271, 1415, 1903, 2199 nm. Finally, the results of this study indicated that the spectral data contains a lot of information that can be applied to identify the soil properties, such as the concentration of heavy metals, with more detail.

Keywords: heavy metals, spectroscopy, spectral bands, PLS regression

Procedia PDF Downloads 82

Authors: Bin Feng, Zhulin Zong

Abstract:

Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

Procedia PDF Downloads 90

Authors: Yao Xing, Hong Ling Liu, Wei Dong Yu

Abstract:

With the increase of global population, it is of importance for the safe water supply, while, the water-monitoring method with the capability of rapidness, low-cost, green and robustness remains unsolved. In this paper, gold nanoclusters-wool keratin is added into copper ions measured by fluorescent method in order to probe copper ions in aqueous solution. The fluorescent results show that gold nanoclusters-wool keratin exhibits high stability of pHs, while it is sensitive to temperature and time. Based on Gauss fitting method, the results exhibit that the slope of gold nanoclusters-wool keratin with pH resolution under acidic condition is higher compared to it under alkaline solutions. Besides, gold nanoclusters-wool keratin added into copper ions shows a fluorescence turn-off response transferring from red to blue under UV light, leading to the dramatically decreased fluorescent intensity of gold nanoclusters-wool keratin solution located at 690 nm. Moreover, the limited concentration of copper ions tested by gold nanoclusters-wool keratin system is around 1 µmol/L, which meets the need of detection standards. The fitting slope of Stern-Volmer plot at low concentration of copper ions is larger than it at high concentrations, which indicates that aggregated gold nanoclusters are from small amounts to large numbers with the increasing concentration of copper ions. It is expected to provide novel method and materials for copper ions testing with low cost, high efficiency, and easy operability.

Keywords: gold nanoclusters, copper ions, wool keratin, fluorescence

Procedia PDF Downloads 250

Authors: Temesgen Geremew

Abstract:

ZnS/glass and CdS/glass single layers and ZnS/CdS and CdS/ZnS heterojunction thin films were deposited by the chemical bath deposition method using zinc acetate and cadmium acetate as the metal ion sources and thioacetamide as a nonmetallic ion source in acidic medium. Na2EDTA was used as a complexing agent to control the free cation concentration. +e single layer and heterojunction thin films were characterized with X-ray diffraction (XRD), a scanning electron microscope (SEM), energy dispersive X-ray (EDX), and a UV-VIS spectrometer. +e XRD patterns of the CdS/glass thin film deposited on the soda lime glass substrate crystalized in the cubic structure with a single peak along the (111) plane. +e ZnS/CdS heterojunction and ZnS/glass single layer thin films were crystalized in the hexagonal ZnS structure. +e CdS/ZnS heterojunction thin film is nearly amorphous.The optical analysis results confirmed single band gap values of 2.75 eV and 2.5 eV for ZnS/CdS and CdS/ZnS heterojunction thin films, respectively. +e CdS/glass and CdS/ZnS thin films have more imaginary dielectric components than the real part. The optical conductivity of the single layer and heterojunction films is in the order of 1015 1/s. +e optical study also confirmed refractive index values between 2 and 2.7 for ZnS/glass, ZnS/CdS, and CdS/ZnS thin films for incident photon energies between 1.2 eV and 3.8 eV. +e surface morphology studies revealed compacted spherical grains covering the substrate surfaces with few cracks on ZnS/glass, ZnS/CdS, and CdS/glass and voids on CdS/ZnS thin films. +e EDX result confirmed nearly 1 :1 metallic to nonmetallic ion ratio in the single-layered thin films and the dominance of Zn ion over Cd ion in both ZnS/CdS and CdS/ZnS heterojunction thin films.

Keywords: SERS, sensor, Hg2+, water detection, polythiophene

Procedia PDF Downloads 64

Authors: Sandra Tapin-Lingua, Katia Ruel, Jean-Paul Joseleau, Daouia Messaoudi, Olivier Fahy, Michel Petit-Conil

Abstract:

The preservative efficacy of organic biocides is strongly related to their capacity of penetration and retention within wood tissues. The specific detection of the pyrethroid insecticide is currently obtained after extraction followed by chemical analysis by chromatography techniques. However visualizing the insecticide molecule within the wood structure requires specific probes together with microscopy techniques. Therefore, the aim of the present work was to apply a new methodology based on antibody-antigen recognition and electronic microscopy to visualize directly pyrethroids in the wood material. A polyclonal antibody directed against cypermethrin was developed and implement it on Pinus sylvestris wood samples coated with technical cypermethrin. The antibody was tested on impregnated wood and the specific recognition of the insecticide was visualized in transmission electron microscopy (TEM). The immunogold-TEM assay evidenced the capacity of the synthetic biocide to penetrate in the wood. The depth of penetration was measured on sections taken at increasing distances from the coated surface of the wood. Such results correlated with chemical analyzes carried out by GC-ECD after extraction. In addition, the immuno-TEM investigation allowed visualizing, for the first time at the ultrastructure scale of resolution, that cypermethrin was able to diffuse within the secondary wood cell walls.

Keywords: cypermethrin, insecticide, wood penetration, wood retention, immuno-transmission electron microscopy, polyclonal antibody

Procedia PDF Downloads 411

Authors: Ava Zarif Sanayei, Mustafa Farjad-Fard, Mohammad-Reza Mohammadian-Behbahani, Leyli Ebrahimi, Sedigheh Sina

Abstract:

The fabrication and testing of a low-cost air-filled ion chamber for X-ray dosimetry is studied. The chamber is made of a metal cylinder, a central wire, a BC517 Darlington transistor, a 9V DC battery, and a voltmeter in order to have a cost-effective means to measure the dose. The output current of the dosimeter is amplified by the transistor and then fed to the large internal resistance of the voltmeter, producing a readable voltage signal. The dose-response linearity of the ion chamber is evaluated for different exposure scenarios by the X-ray tube. kVp values 70, 90, and 120, and mAs up to 20 are considered. In all experiments, a solid-state dosimeter (Solidose 400, Elimpex Medizintechnik) is used as a reference device for chamber calibration. Each case of exposure is repeated three times, the voltmeter and Solidose readings are recorded, and the mean and standard deviation values are calculated. Then, the calibration curve, derived by plotting voltmeter readings against Solidose readings, provided a linear fit result for all tube kVps of 70, 90, and 120. A 99, 98, and 100% linear relationship, respectively, for kVp values 70, 90, and 120 are demonstrated. The study shows the feasibility of achieving acceptable dose measurements with a simplified setup. Further enhancements to the proposed setup include solutions for limiting the leakage current, optimizing chamber dimensions, utilizing electronic microcontrollers for dedicated data readout, and minimizing the impact of stray electromagnetic fields on the system.

Keywords: dosimetry, ion chamber, radiation detection, X-ray

Procedia PDF Downloads 76

Authors: Frederick Anlimah, Vinod Gopaldasani, Catherine MacPhail, Brian Davies

Abstract:

Aim: This study aims to identify the barriers and challenges hindering the implementation of effective controls and the adoption of safe work practices to protect workers from respirable crystalline silica (RCS) exposure. Problem or Situation: Tunnelling is one of many occupations that expose workers to the harmful effects of respirable crystalline silica. Despite various control measures, such as engineering controls and personal protective equipment, exposures remain inadequately controlled, leading to incurable silicosis and other severe illnesses, such as lung cancer. Methods: The research involved surveying tunnel construction workers, conducting interviews, and facilitating focus group discussions. Additionally, site observations and content analysis of work procedures and instructions were performed. Results: Preliminary data analysis reveals notable findings. While there is a commendable level of knowledge and commitment among management and workers concerning RCS exposure in tunnelling, there is a striking lack of prioritization regarding dust control. Moreover, the risks associated with dust exposure are not sufficiently acknowledged. Additionally, the data suggests that engineers and supervisors responsible for implementing dust controls often possess limited knowledge regarding the factors influencing the effectiveness of these measures. These findings emphasise the need for a paradigm shift, including higher prioritisation of dust control, adoption of holistic dust reduction strategies, and enhanced knowledge about effective control measures. Conclusion: This research shed light on tunnel construction workers' barriers and challenges in protecting themselves from RCS exposure. This knowledge will be essential in developing interventions and strategies to enhance dust exposure and prevent the adverse health effects of respirable crystalline silica exposure in tunnelling and similar industries.

Keywords: respirable crystalline silica, dust control, worker practices, exposure prevention, silicosis

Procedia PDF Downloads 69

Authors: David Nkurunziza, Rahman Tafahomi

Abstract:

The population growth rate of the city of Kigali is increasing annually. In 1960 the population was six thousand, in 1990 it became two hundred thousand and is supposed to be 4 to 5 million incoming twenty years. With the increase in the residents living in the city of Kigali, there is also a need for an increase in social and economic infrastructures connected by the road networks to serve the residents effectively. A road network is a route that connects people to their needs and has to facilitate people to reach the social and economic facilities easily. This research analyzed the social and economic aspects of three selected roads networks passing through all three districts of the city of Kigali, whose center is the city center roundabout, thorough evaluation of the proximity of the social and economic facilities to the road network. These road networks are the city center to nyabugogo to karuruma, city center to kanogo to Rwanda to kicukiro center to Nyanza taxi park, and city center to Yamaha to kinamba to gakinjiro to kagugu health center road network. This research used a methodology of identifying and quantifying the social and economic facilities within a limited distance of 300 meters along each side of the road networks. Social facilities evaluated are the health facilities, education facilities, institution facilities, and worship facilities, while the economic facilities accessed are the commercial zones, industries, banks, and hotels. These facilities were evaluated and graded based on their distance from the road and their value. The total scores of each road network per kilometer were calculated and finally, the road networks were ranked based on their percentage score per one kilometer—this research was based on field surveys and interviews to collect data with forms and questionnaires. The analysis of the data collected declared that the road network from the city center to Yamaha to kinamba to gakinjiro to the kagugu health center is the best performer, the second is the road network from the city center to nyabugogo to karuruma, while the third is the road network from the city center to kanogo to rwandex to kicukiro center to nyaza taxi park.

Keywords: social economical aspect, road network functionality, urban road network, economic and social facilities

Procedia PDF Downloads 160

Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

Abstract:

Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

Procedia PDF Downloads 246

Authors: L. Malic, X. Zhang, D. Brassard, L. Clime, J. Daoud, C. Luebbert, V. Barrere, A. Boutin, S. Bidawid, N. Corneau, J. Farber, T. Veres

Abstract:

The incidence of infections caused by foodborne pathogens such as Listeria monocytogenes (L. monocytogenes) poses a great potential threat to public health and safety. These issues are further exacerbated by legal repercussions due to “zero tolerance” food safety standards adopted in developed countries. Unfortunately, a large number of related disease outbreaks are caused by pathogens present in extremely low counts currently undetectable by available techniques. The development of highly sensitive and rapid detection of foodborne pathogens is therefore crucial, and requires robust and efficient pre-analytical sample preparation. Immunomagnetic separation is a popular approach to sample preparation. Microfluidic chips combined with external magnets have emerged as viable high throughput methods. However, external magnets alone are not suitable for the capture of nanoparticles, as very strong magnetic fields are required. Devices that incorporate externally applied magnetic field and microstructures of a soft magnetic material have thus been used for local field amplification. Unfortunately, very complex and costly fabrication processes used for integration of soft magnetic materials in the reported proof-of-concept devices would prohibit their use as disposable tools for food and water safety or diagnostic applications. We present a sample preparation magnetic microfluidic device implemented in low-cost thermoplastic polymers using fabrication techniques suitable for mass-production. The developed magnetic capture chip (M-chip) was employed for rapid capture and release of L. monocytogenes conjugated to immunomagnetic nanoparticles (IMNs) in buffer and beef filtrate. The M-chip relies on a dense array of Nickel-coated high-aspect ratio pillars for capture with controlled magnetic field distribution and a microfluidic channel network for sample delivery, waste, wash and recovery. The developed Nickel-coating process and passivation allows generation of switchable local perturbations within the uniform magnetic field generated with a pair of permanent magnets placed at the opposite edges of the chip. This leads to strong and reversible trapping force, wherein high local magnetic field gradients allow efficient capture of IMNs conjugated to L. monocytogenes flowing through the microfluidic chamber. The experimental optimization of the M-chip was performed using commercially available magnetic microparticles and fabricated silica-coated iron-oxide nanoparticles. The fabricated nanoparticles were optimized to achieve the desired magnetic moment and surface functionalization was tailored to allow efficient capture antibody immobilization. The integration, validation and further optimization of the capture and release protocol is demonstrated using both, dead and live L. monocytogenes through fluorescence microscopy and plate- culture method. The capture efficiency of the chip was found to vary as function of listeria to nanoparticle concentration ratio. The maximum capture efficiency of 30% was obtained and the 24-hour plate-culture method allowed the detection of initial sample concentration of only 16 cfu/ml. The device was also very efficient in concentrating the sample from a 10 ml initial volume. Specifically, 280% concentration efficiency was achieved in 17 minutes only, demonstrating the suitability of the system for food safety applications. In addition, flexible design and low-cost fabrication process will allow rapid sample preparation for applications beyond food and water safety, including point-of-care diagnosis.

Keywords: array of pillars, bacteria isolation, immunomagnetic sample preparation, polymer microfluidic device

Procedia PDF Downloads 279

Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

This study employs a method based on image analyses and structure information to detect accumulated ice on known structures. The icing of marine vessels and offshore structures causes significant reductions in their efficiency and creates unsafe working conditions. Image processing methods are used to measure ice loads automatically. Most image processing methods are developed based on captured image analyses. In this method, ice loads on structures are calculated by defining structure coordinates and processing captured images. A pyramidal structure is designed with nine cylindrical bars as the known structure of experimental setup. Unsymmetrical ice accumulated on the structure in a cold room represents the actual case of experiments. Camera intrinsic and extrinsic parameters are used to define structure coordinates in the image coordinate system according to the camera location and angle. The thresholding method is applied to capture images and detect iced structures in a binary image. The ice thickness of each element is calculated by combining the information from the binary image and the structure coordinate. Averaging ice diameters from different camera views obtains ice thicknesses of structure elements. Comparison between ice load measurements using this method and the actual ice loads shows positive correlations with an acceptable range of error. The method can be applied to complex structures defining structure and camera coordinates.

Keywords: camera calibration, ice detection, ice load measurements, image processing

Procedia PDF Downloads 367

Authors: Afsaneh Mohammadnejad, Marianne Nygaard, Jan Baumbach, Shuxia Li, Weilong Li, Jesper Lund, Jacob v. B. Hjelmborg, Lene Christensen, Qihua Tan

Abstract:

Cognitive impairment in the elderly is a key issue affecting the quality of life. Despite a strong genetic background in cognition, only a limited number of single nucleotide polymorphisms (SNPs) have been found. These explain a small proportion of the genetic component of cognitive function, thus leaving a large proportion unaccounted for. We hypothesize that one reason for this missing heritability is the misspecified modeling in data analysis concerning phenotype distribution as well as the relationship between SNP dosage and the phenotype of interest. In an attempt to overcome these issues, we introduced a model-free method based on the generalized correlation coefficient (GCC) in a genome-wide association study (GWAS) of cognitive function in twin samples and compared its performance with two popular linear regression models. The GCC-based GWAS identified two genome-wide significant (P-value < 5e-8) SNPs; rs2904650 near ZDHHC2 on chromosome 8 and rs111256489 near CD6 on chromosome 11. The kinship model also detected two genome-wide significant SNPs, rs112169253 on chromosome 4 and rs17417920 on chromosome 7, whereas no genome-wide significant SNPs were found by the linear mixed model (LME). Compared to the linear models, more meaningful biological pathways like GABA receptor activation, ion channel transport, neuroactive ligand-receptor interaction, and the renin-angiotensin system were found to be enriched by SNPs from GCC. The GCC model outperformed the linear regression models by identifying more genome-wide significant genetic variants and more meaningful biological pathways related to cognitive function. Moreover, GCC-based GWAS was robust in handling genetically related twin samples, which is an important feature in handling genetic confounding in association studies.

Keywords: cognition, generalized correlation coefficient, GWAS, twins

Procedia PDF Downloads 121

Authors: Wilfred Elliam

Abstract:

Background: Pain is a prevalent and debilitating symptom among breast cancer patients, impacting their quality of life and overall well-being. The experience of pain in this population is multifaceted, influenced by a combination of disease-related factors, treatment side effects, and individual characteristics. Despite advancements in cancer treatment and pain management, many breast cancer patients continue to suffer from chronic pain, which can persist long after the completion of treatment. Understanding the progression of pain in breast cancer patients over time and identifying its correlates is crucial for effective pain management and supportive care strategies. The purpose of this research is to understand the patterns and progression of pain experienced by breast cancer survivors over time. Methods: Data were collected from breast cancer patients at Hartford Hospital at four time points: baseline, 3, 6 and 12 weeks. Key variables measured include pain, body mass index (BMI), fatigue, musculoskeletal pain, sleep disturbance, and demographic variables (age, employment status, cancer stage, and ethnicity). Binomial generalized linear mixed models were used to examine changes in pain and symptoms over time. Results: A total of 100 breast cancer patients aged  18 years old were included in the analysis. We found that the effect of time on pain (p = 0.024), musculoskeletal pain (p= <0.001), fatigue (p= <0.001), and sleep disturbance (p-value = 0.013) were statistically significant with pain progression in breast cancer patients. Patients using aromatase inhibitors have worse fatigue (<0.05) and musculoskeletal pain (<0.001) compared to patients with Tamoxifen. Patients who are obese (<0.001) and overweight (<0.001) are more likely to report pain compared to patients with normal weight. Conclusion: This study revealed the complex interplay between various factors such as time, pain, sleep disturbance in breast cancer patient. Specifically, pain, musculoskeletal pain, sleep disturbance, fatigue exhibited significant changes across the measured time points, indicating a dynamic pain progression in these patients. The findings provide a foundation for future research and targeted interventions aimed at improving pain in breast cancer patient outcomes.

Keywords: breast cancer, chronic pain, pain management, quality of life

Procedia PDF Downloads 29

Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

Abstract:

Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

Procedia PDF Downloads 249

Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

Abstract:

There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

Procedia PDF Downloads 330

Authors: Folong Tchoffo Marlyse Fabiola, Anaba Onana Achille Basile

Abstract:

Located in the western region of Cameroon, in the BAMBOUTOS department, the city of Mbouda belongs to the Pan-African basement. The water resources exploited in this region consist of surface water and groundwater from weathered and fractured aquifers within the same basement. To study the factors determining the productivity of aquifers in the Mbouda area, we adopted a methodology based on collecting data from boreholes drilled in the region, identifying different types of rocks, analyzing structures, and conducting geophysical surveys in the field. The results obtained allowed us to distinguish two main types of rocks: metamorphic rocks composed of amphibolites and migmatitic gneisses and igneous rocks, namely granodiorites and granites. Several types of structures were also observed, including planar structures (foliation and schistosity), folded structures (folds), and brittle structures (fractures and lineaments). A structural synthesis combines all these elements into three major phases of deformation. Phase D1 is characterized by foliation and schistosity, phase D2 is marked by shear planes and phase D3 is characterized by open and sealed fractures. The analysis of structures (fractures in outcrops, Landsat lineaments, subsurface structures) shows a predominance of ENE-WSW and WNW-ESE directions. Through electrical surveys and borehole data, we were able to identify the sequence of different geological formations. Four geo-electric layers were identified, each with a different electrical conductivity: conductive, semi-resistive, or resistive. The last conductive layer is considered a potentially aquiferous zone. The flow rates of the boreholes ranged from 2.6 to 12 m3/h, classified as moderate to high according to the CIEH classification. The boreholes were mainly located in basalts, which are mineralogically rich in ferromagnesian minerals. This mineral composition contributes to their high productivity as they are more likely to be weathered. The boreholes were positioned along linear structures or at their intersections.

Keywords: Mbouda, Pan-African basement, productivity, west-Cameroon

Procedia PDF Downloads 61

Authors: Raluca Ana Maria Viziteu, Anna Prudnikova

Abstract:

Industrial control systems (ICS) have received much attention in recent years due to the convergence of information technology (IT) and operational technology (OT) that has increased the interdependence of safety and security issues to be considered. These issues require ICS-tailored solutions. That led to the need to creation of a methodology for supporting ICS device manufacturers and system integrators in carrying out threat modeling of embedded ICS devices in a way that guarantees the quality of the identified threats and minimizes subjectivity in the threat identification process. To research, the possibility of creating such a methodology, a set of existing standards, regulations, papers, and publications related to threat modeling in the ICS sector and other sectors was reviewed to identify various existing methodologies and methods used in threat modeling. Furthermore, the most popular ones were tested in an exploratory phase on a specific PLC device. The outcome of this exploratory phase has been used as a basis for defining specific characteristics of ICS embedded devices and their deployment scenarios, identifying the factors that introduce subjectivity in the threat modeling process of such devices, and defining metrics for evaluating the minimum quality requirements of identified threats associated to the deployment of the devices in existing infrastructures. Furthermore, the threat modeling methodology was created based on the previous steps' results. The usability of the methodology was evaluated through a set of standardized threat modeling requirements and a standardized comparison method for threat modeling methodologies. The outcomes of these verification methods confirm that the methodology is effective. The full paper includes the outcome of research on different threat modeling methodologies that can be used in OT, their comparison, and the results of implementing each of them in practice on a PLC device. This research is further used to build a threat modeling methodology tailored to OT environments; a detailed description is included. Moreover, the paper includes results of the evaluation of created methodology based on a set of parameters specifically created to rate threat modeling methodologies.

Keywords: device manufacturers, embedded devices, industrial control systems, threat modeling

Procedia PDF Downloads 78

Authors: M. R. Mogarekar, Shraddha V. More, Pankaj Kumar

Abstract:

Gastroenteritis, the third leading killer of children in India today is responsible for 13% of all deaths in children <5 years of age and kills an estimated 300,000 children in India each year. We decided to investigate parameters which can help in early disease detection and prompt treatment. Serum paraoxonase is calcium dependent esterase which is widely distributed among tissues such as liver, kidney, and intestine and is located in the chromosomal region 7q21.3 22.1. Studies show the presence of excessive reactive oxygen metabolites and antioxidant imbalance in the gastrointestinal tract leading to oxidative stress in gastroenteritis. To our knowledge, this is the first ever study done. The objective of present study is to investigate the role of paraoxonase 1 (PON 1) status i.e arylesterase and lactonase activities and Q192R polymorphism and conjugated dienes, in gastroenteritis of paediatric population. The study and control group consists of 40 paediatric patients with and without gastroenteritis. Paraoxonase arylesterase and lactonase activities were assessed and phenotyping was determined. Conjugated dienes were also assessed. PON 1 arylesterase activities in cases (61.494±13.220) and controls (70.942±15.385) and lactonase activities in cases (15.702±1.036) and controls (17.434±1.176) were significantly decreased (p<0.05). There is no significant difference of phenotypic distribution in cases and controls. Conjugated dienes were found significantly increased in patients (0.086±0.024) than the control group (0.064±0.019) (p<0.05). Paraoxonase 1 activities (arylesterase and lactonase) and conjugated dienes may be useful in risk assessment and management in gastroenteritis in paediatric population.

Keywords: paraoxonase 1 polymorphism, arylesterase, lactonase, conjugated dienes, p-nitrophenylacetate, DHC

Procedia PDF Downloads 306

Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

Abstract:

Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

Procedia PDF Downloads 429

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

Abstract:

Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

Procedia PDF Downloads 438