Search results for: real estate price prediction

Authors: Frikha Rim, Abdelmoula Bouayed Nouha, Rebai Tarek

Abstract:

Pregnancy is a hypercoagulable state which causing a defective maternal haemostatic response and leading to thrombosis of the uteroplacental vasculature, that might cause pregnancy complications as recurrent pregnancy loss (RPL). Since heritable Thrombophilic defects are associated with increased thrombosis, their prevalence was evaluated in patients with special emphasis on combinations of the above pathologies. Especially, Factor V Leiden (FVL) G1691A, methylene tetra hydro folate reductase (MTHFR) C677T, and factor II (FII) G20210A mutations are three important causes of thrombophilia, which might be related to recurrent pregnancy loss (RPL). In this study we evaluated the presence of these three mutations [factor V Leiden (FVL), prothrombin G20210A (PTG) and methylenetetrahydrofolate reductase (MTHFR) C677T] amongst 35 Tunisian women with more than 2 miscarriages, referred to our genetic counseling. DNA was extracted from peripheral blood samples and PCR-RFLP was performed for the molecular diagnosis of each mutation. Factor V Leiden and Prothrombin mutation were detected respectively in 5.7% and 2.9% of women with particular history of early fetal loss and thrombotic events. Despites the luck of strength of this study, we insist that testing for the most inherited thrombophilia (FVL and FII mutation) should be performed in women with RPL in the context of thrombotic events. Multi-centre collaboration is necessary to clarify the real impact of thrombotic molecular defects on the pregnancy outcome, to ascertain the effect of thrombophilia on recurrent pregnancy loss and then to evaluate the appropriate therapeutic approach.

Keywords: thrombophilia, recurrent pregnancy loss, factor V Leiden, prothrombin G20210A, methylene tetra hydro folate reductase

Procedia PDF Downloads 458

Authors: Zama Mahmood

Abstract:

The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

Procedia PDF Downloads 335

Authors: Kalpana Rajouriya, Ajay Taneja

Abstract:

Particulates are ubiquitous in the air environment and cause serious threats to human beings, such as lung cancer, COPD, and Asthma. Particulates mainly arise from industrial effluent, vehicular emission, and other anthropogenic activities. In the glass industrial city Firozabad, real-time monitoring of size segregated Particulate Matter (PM) and black carbon was done by Aerosol Black Carbon Detector (ABCD) and GRIMM portable aerosol Spectrometer at two different sites in which one site is urban and another is rural. The average mass concentration of size segregated PM during the study period (March & April 2022) was recorded as PM10 (223.73 g/m⁻³), PM5.0 (44.955 g/m⁻³), PM2.5 (59.275 g/m⁻³), PM1.0 (33.02 g/m⁻³), PM0.5 (2.05 g/m⁻³), and PM0.25 (2.99 g/m⁻³). The highest concentration of BC was found in Urban due to the emissions from diesel engines and wood burning, while NO2 was highest at the rural sites. The average concentrations of PM10 (6.08 and 2.73 times) PM2.5 exceeded the NAAQS and WHO guidelines. Particulate Matter deposition and health risk assessment was done by MPPD and USEPA model to know about the particulate matter toxicity in industrial residents. Health risk assessment results showed that Children are most likely to be affected by exposure of PM10 and PM2.5 and may have various non-carcinogenic and carcinogenic diseases. Deposition results inferred that the sensitive exposed population, especially 9 years old children, have high PM deposition as well as visualization and may be at risk of developing health-related problems from exposure to size-segregated PM. They will be discussed during presentation.

Keywords: particulate matter, black carbon, NO2, deposition of PM, health risk

Procedia PDF Downloads 66

Authors: Zhihui Liu, Dongmei Hao, Qian Qiu, Yang An, Lin Yang, Song Zhang, Yimin Yang, Xuwen Li, Dingchang Zheng

Abstract:

Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor.

Keywords: electrohysterogram, feature, preterm labor, term labor

Procedia PDF Downloads 571

Authors: Euphrasia Susy Suhendra, Lies Handrijaningsih

Abstract:

The banking sector as an intermediary party or intermediaries occupies a very important position in bridging the needs of working capital investment in the real sector with funds owner. This will certainly make money more effectively to improve the economic value added. As an intermediary, Islamic banks raise funds from the public and then distribute in the form of financing. In practice, the distribution of funding that is run by Islamic Banking is not as easy as, in theory, because, in fact, there are many financing problems; some are caused by lacking the assessment and supervision of banks to customers. This study aims to analyze the influence of the Third Party Funds, Return on Assets (ROA), Non Performing Financing (NPF), and Financing Deposit Ratio (FDR) to Total Financing provided to the Community by Islamic Banks in Indonesia. The data used is monthly data released by Bank of Indonesia in Islamic Banking Statistics in the time period of January 2009 - December 2013. This study uses cointegration test to see the long-term relationship, and use error correction models to examine the relationship of short-term. The results of this study indicate that the Third Party Fund has a short-term effect on total funding, Return on Assets has a long term effect on the total financing, Non Performing Financing has long-term effects of total financing, and Financing deposit ratio has the effect of short-term and long-term of the total financing provided by Islamic Banks in Indonesia.

Keywords: Islamic banking, third party fund, return on asset, non-performing financing, financing deposit ratio

Procedia PDF Downloads 466

Authors: Sara Ataei, Molouk Hadjibabaie, Shirinsadat Badri, Amirhossein Moslehi, Iman Karimzadeh, Ardeshir Ghavamzadeh

Abstract:

Purpose: To assess the pattern and probable risk factors for moderate and major drug–drug interactions in a referral hematology-oncology ward in Iran. Methods: All patients admitted to hematology–oncology ward of Dr. Shariati Hospital during a 6-month period and received at least two anti-cancer or non-anti-cancer medications simultaneously were included. All being scheduled anti-cancer and non-anti-cancer medications both prescribed and administered during ward stay were considered for drug–drug interaction screening by Lexi-Interact On- Desktop software. Results: One hundred and eighty-five drug–drug interactions with moderate or major severity were detected from 83 patients. Most of drug–drug interactions (69.73 %) were classified as pharmacokinetics. Fluconazole (25.95 %) was the most commonly offending medication in drug–drug interactions. Interaction of sulfamethoxazole-trimethoprim with fluconazole was the most common drug–drug interaction (27.27 %). Vincristine with imatinib was the only identified interaction between two anti-cancer agents. The number of administered medications during ward stay was considered as an independent risk factor for developing a drug–drug interaction. Conclusions: Potential moderate or major drug–drug interactions occur frequently in patients with hematological malignancies or related diseases. Performing larger standard studies are required to assess the real clinical and economical effects of drug–drug interactions on patients with hematological and non-hematological malignancies.

Keywords: drug–drug interactions, hematology–oncology ward, hematological malignancies

Procedia PDF Downloads 454

Authors: Iddrisu Ibrahim, Joseph Atia Ayariga, Junhuan Xu, Daniel Abugri, Boakai Robertson, Olufemi S. Ajayi

Abstract:

The emergence of multidrug resistance poses a huge risk to public health globally. Yet these recalcitrant pathogens continue to rise in incidence rate, with resistance rates significantly outpacing the speed of antibiotic development. This, therefore, presents an aura of related health issues such as untreatable nosocomial infections arising from organ transplants and surgeries, as well as community-acquired infections that are related to people with compromised immunity, e.g., diabetic and HIV patients, etc. There is a global effort to fight multidrug-resistant pathogens spearheaded by the World Health Organization, thus calling for research into novel antimicrobial agents to fight multiple drug resistance. Previously, our laboratory demonstrated that Cannabidiol (CBD) was an effective antimicrobial against Salmonella typhimurium (S. typhimurium). However, we observed resistance development over time. To understand the mechanisms S. typhimurium uses to develop resistance to Cannabidiol (CBD), we studied the abundance of bacteria lipopolysaccharide (LPS) and membrane sterols of both susceptible and resistant S. typhimurium. Using real-time quantitative polymerase chain reaction (RT-qPCR), we also analyzed the expression of selected genes known for aiding resistance development in S. typhimurium. We discovered that there was a significantly higher expression of blaTEM, fimA, fimZ, and integrons in the CBD-resistant bacteria, and these were also accompanied by a shift in abundance in cell surface molecules such as lipopolysaccharide (LPS) and sterols.

Keywords: antimicrobials, resistance, cannabidiol, gram-negative bacteria, integrons, blaTEM, Fim, LPS, ergosterols

Procedia PDF Downloads 101

Authors: Hyun-Kyung Lee, Jehyung Oh, Young Eun Jeong, Hyun-Shik Lee

Abstract:

Perfluoroalkyl compounds (PFCs) are environmental toxicants that persistently accumulate in the human blood. Their widespread detection and accumulation in the environment raise concerns about whether these chemicals might be developmental toxicants and teratogens in the ecosystem. We evaluated and compared the toxicity of PFCs of containing various numbers of carbon atoms (C8-11 carbons) on vertebrate embryogenesis. We assessed the developmental toxicity and teratogenicity of various PFCs. The toxic effects on Xenopus embryos were evaluated using different methods. We measured teratogenic indices (TIs) and investigated the mechanisms underlying developmental toxicity and teratogenicity by measuring the expression of organ-specific biomarkers such as xPTB (liver), Nkx2.5 (heart), and Cyl18 (intestine). All PFCs that we tested were found to be developmental toxicants and teratogens. Their toxic effects were strengthened with increasing length of the fluorinated carbon chain. Furthermore, we produced evidence showing that perfluorodecanoic acid (PFDA) and perfluoroundecanoic acid (PFuDA) are more potent developmental toxicants and teratogens in an animal model compared to the other PFCs we evaluated [perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA)]. In particular, severe defects resulting from PFDA and PFuDA exposure were observed in the liver and heart, respectively, using the whole mount in situ hybridization, real-time PCR, pathologic analysis of the heart, and dissection of the liver. Our studies suggest that most PFCs are developmental toxicants and teratogens, however, compounds that have higher numbers of carbons (i.e., PFDA and PFuDA) exert more potent effects.

Keywords: PFC, xenopus, fetax, development

Procedia PDF Downloads 352

Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

Abstract:

Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

Procedia PDF Downloads 256

Authors: Rahul Madathiparambil Visalakshan, Alex Cavallaro, John Hayball, Krasimir Vasilev

Abstract:

The role of biomaterial surface nanotopograhy on fibrinogen adsorption and unfolding, and the subsequent immune response were studied. Inconsistent topography and varying chemical functionalities along with a lack of reproducibility pose a challenge in determining the specific effects of nanotopography or chemistry on proteins and cells. It is important to have a well-defined nanotopography with a homogeneous chemistry to study the real effect of nanotopography on biological systems. Therefore, we developed a technique that can produce well-defined and highly reproducible topography to identify the role of specific roughness, size, height and density with the presence of homogeneous chemical functionality. Using plasma polymerisation of oxazoline monomers and immobilized gold nanoparticles we created surfaces with an equal number density of nanoparticles of different sizes. This surface was used to study the role of surface nanotopography and the interplay of surface chemistry on proteins and immune cells. The effect of nanotopography on fibrinogen adsorption was investigated using Quartz Cristal Microbalance with Dissipation and micro BCA. The mass of fibrinogen adsorbed on the surface increased with increasing size of nano-topography. Protein structural changes up on adsorption to the nano rough surface was studied using circular dichroism spectroscopy. Fibrinogen unfolding varied depending on the specific nanotopography of the surfaces. It was revealed that the in vitro immune response to the nanotopography surfaces changed due to this protein unfolding.

Keywords: biomaterial inflammation, protein and cell responses, protein unfolding, surface nanotopography

Procedia PDF Downloads 176

Authors: I. V. Pinto, M. R. Sooriyarachchi

Abstract:

It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, penalized quasi-likelihood, power, quasi-likelihood, type-I error

Procedia PDF Downloads 142

Authors: Xiyang Li, Qi Yu, Lun Zhang

Abstract:

In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

Procedia PDF Downloads 85

Authors: Mindaye Teshome, Evaldo Muñoz Braz, Carlos M. M. Eleto Torres, Patricia Mattos

Abstract:

Sustainable forest management planning requires up-to-date information on the structure, standing volume, biomass, and growth rate of trees from a given forest. This kind of information is lacking in many forests in Ethiopia. The objective of this study was to quantify the population structure, diameter growth rate, and standing volume of wood from Juniperus procera trees in the Chilimo forest. A total of 163 sample plots were set up in the forest to collect the relevant vegetation data. Growth ring measurements were conducted on stem disc samples collected from 12 J. procera trees. Diameter and height measurements were recorded from a total of 1399 individual trees with dbh ≥ 2 cm. The growth rate, maximum current and mean annual increments, minimum logging diameter, and cutting cycle were estimated, and alternative cutting cycles were established. Using these data, the harvestable volume of wood was projected by alternating four minimum logging diameters and five cutting cycles following the stand table projection method. The results show that J. procera trees have an average density of 183 stems ha⁻¹, a total basal area of 12.1 m² ha⁻¹, and a standing volume of 98.9 m³ ha⁻¹. The mean annual diameter growth ranges between 0.50 and 0.65 cm year⁻¹ with an overall mean of 0.59 cm year⁻¹. The population of J. procera tree followed a reverse J-shape diameter distribution pattern. The maximum current annual increment in volume (CAI) occurred at around 49 years when trees reached 30 cm in diameter. Trees showed the maximum mean annual increment in volume (MAI) around 91 years, with a diameter size of 50 cm. The simulation analysis revealed that 40 cm MLD and a 15-year cutting cycle are the best minimum logging diameter and cutting cycle. This combination showed the largest harvestable volume of wood potential, volume increments, and a 35% recovery of the initially harvested volume. It is concluded that the forest is well stocked and has a large amount of harvestable volume of wood from J. procera trees. This will enable the country to partly meet the national wood demand through domestic wood production. The use of the current population structure and diameter growth data from tree ring analysis enables the exact prediction of the harvestable volume of wood. The developed model supplied an idea about the productivity of the J. procera tree population and enables policymakers to develop specific management criteria for wood harvesting.

Keywords: logging, growth model, cutting cycle, minimum logging diameter

Procedia PDF Downloads 89

Authors: Omar Mayyas

Abstract:

Clinical decision-making (CDM) is essential to community health nursing (CHN) education. For this reason, nursing educators are responsible for developing these skills among nursing students because nursing students are exposed to highly critical conditions after graduation. However, due to limited exposure to real-world situations, many nursing students need help developing clinical decision-making skills in this area. Therefore, the impact of Virtual Simulation (VS) on community health nursing students' clinical decision-making in nursing education has to be investigated. This study aims to examine the difference in CDM ability among CHN students who received traditional education compared to those who received VS classes, to identify the factors that may influence CDM ability differences between CHN students who received a traditional education and VS classes, and to provide recommendations for educational programs that can enhance the CDM ability of CHN students and improve the quality of care provided in community settings. A mixed-method study will conduct. A randomized controlled trial will compare the CDM ability of CHN students who received 1hr traditional class with another group who received 1hr VS scenario about diabetic patient nursing care. Sixty-four students in each group will randomly select to be exposed to the intervention from undergraduate nursing students who completed the CHN course at York University. The participants will receive the same Clinical Decision Making in Nursing Scale (CDMNS) questionnaire. The study intervention will follow the Medical Research Council (MRC) approach. SPSS and content analysis will use for data analysis.

Keywords: clinical decision-making, virtual simulation, community health nursing students, community health nursing education

Procedia PDF Downloads 67

Authors: Noran Adel Emara, Elham Ghazi Mohammad

Abstract:

Qatar University is engaged in a systemic education reform that includes integrating the latest and most effective technologies for teaching and learning. ICube is high-immersive virtual reality technology is used to teach educational scenarios that are difficult to teach in real situations. The trends toward delivering science education via virtual reality applications have accelerated in recent years. However, research on students perceptions of integrating virtual reality especially ICube technology is somehow limited. Students often have difficulties focusing attention on learning science topics that require imagination and easily lose attention and interest during the lesson. The aim of this study was to examine students’ perception of integrating ICube technology in the solar system lesson. Moreover, to explore how ICube could engage students in learning scientific concept of the solar system. The research framework included the following quantitative research design with data collection and analysis from questionnaire results. The solar system lesson was conducted by teacher candidates (Diploma students) who taught in the ICube virtual lab in Qatar University. A group of 30 students from eighth grade were randomly selected to participate in the study. Results showed that the students were extremely engaged in learning the solar system and responded positively to integrating ICube in teaching. Moreover, the students showed interest in learning more lessons through ICube as it provided them with valuable learning experience about complex situations.

Keywords: ICube, integrating technology, science education, virtual reality

Procedia PDF Downloads 302

Authors: Lahcen Daoudi, Fatima Zahra Omdi, Abldelali Gourfi

Abstract:

In Morocco, as in most Mediterranean countries, water scarcity is a common situation because of low and unevenly distributed rainfall. The expansions of irrigated lands, as well as the growth of urban and industrial areas and tourist resorts, contribute to an increase of water demand. Therefore in the 1960s Morocco embarked on an ambitious program to increase the number of dams to boost water retention capacity. However, the decrease in the capacity of these reservoirs caused by sedimentation is a major problem; it is estimated at 75 million m3/year. Dams and reservoirs became unusable for their intended purposes due to sedimentation in large rivers that result from soil erosion. Soil erosion presents an important driving force in the process affecting the landscape. It has become one of the most serious environmental problems that raised much interest throughout the world. Monitoring soil erosion risk is an important part of soil conservation practices. The estimation of soil loss risk is the first step for a successful control of water erosion. The aim of this study is to estimate the soil loss risk and its spatial distribution in the different fields of Morocco and to prioritize areas for soil conservation interventions. The approach followed is the Revised Universal Soil Loss Equation (RUSLE) using remote sensing and GIS, which is the most popular empirically based model used globally for erosion prediction and control. This model has been tested in many agricultural watersheds in the world, particularly for large-scale basins due to the simplicity of the model formulation and easy availability of the dataset. The spatial distribution of the annual soil loss was elaborated by the combination of several factors: rainfall erosivity, soil erodability, topography, and land cover. The average annual soil loss estimated in several basins watershed of Morocco varies from 0 to 50t/ha/year. Watersheds characterized by high-erosion-vulnerability are located in the North (Rif Mountains) and more particularly in the Central part of Morocco (High Atlas Mountains). This variation of vulnerability is highly correlated to slope variation which indicates that the topography factor is the main agent of soil erosion within these basin catchments. These results could be helpful for the planning of natural resources management and for implementing sustainable long-term management strategies which are necessary for soil conservation and for increasing over the projected economic life of the dam implemented.

Keywords: soil loss, RUSLE, GIS-remote sensing, watershed, Morocco

Procedia PDF Downloads 461

Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

Abstract:

Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

Procedia PDF Downloads 189

Authors: Sara Mohammad Atef Sabaika

Abstract:

Background: The development of factor VIII (FVIII) inhibitor and hemophilic arthropathy in patients with hemophilia A (PWHA) are a great challenge for hemophilia care. Both genetic and environmental factors led to complications in PWHA. The development of inhibitory antibodies is usually induced by the immune response. Tumor necrosis factor α (TNF-α), one of the cytokines, might contribute to its polymorphism. Aim: Study the association between tumor necrosis alpha level and genotypes in pediatric patients with hemophilia A and its relation to inhibitor development and joint status. Methods: A cross-sectional study was conducted among a sufficient number of PWHA attending the Pediatric Hematology and Oncology Unit, Pediatric department in Menoufia University hospital. The clinical parameters, FVIII, FVIII inhibitor, and serum TNF-α level were assessed. The genotyping of −380G > A TNF-α gene polymorphism was performed using real time polymerase chain reaction. Results: Among the 50 PWHA, 28 (56%) were identified as severe PWHA. The FVIII inhibitor was identified in 6/28 (21.5%) of severe PWHA. There was a significant correlation between serum TNF-α level and the development of inhibitor (p = 0:043). There was significant correlation between polymorphisms of −380G > A TNF-α gene and hemophilic arthropathy development (p = 0:645). Conclusion: The prevalence of FVIII inhibitor in severe PWHA in Menoufia was 21.5%. The frequency of replacement therapy is a risk factor for inhibitor development. Serum TNF-α level and its gene polymorphism might be used to predict inhibitor development and joint status in pediatric patients with hemophilia A.

Keywords: hemophilic arthropathy, TNF alpha., patients witb hemophilia A PWHA, inhibitor

Procedia PDF Downloads 94

Authors: Dhanashree Aole, V. Hariharan, Swati Surushe

Abstract:

Corrosion can cause serious and expensive damage to the automobile components. Various proven techniques for controlling and preventing corrosion depend on the specific material to be protected. Electrochemical Impedance Spectroscopy (EIS) and salt spray tests are commonly used to assess the corrosion degradation mechanism of coatings on metallic surfaces. While, the only test which monitors the corrosion rate in real time is known as Linear Polarisation Resistance (LPR). In this study, electrochemical tests (EIS & LPR) and spray test are reviewed to assess the corrosion resistance and durability of different coatings. The main objective of this study is to correlate the test results obtained using linear polarization resistance (LPR) and Electrochemical Impedance Spectroscopy (EIS) with the results obtained using standard salt spray test. Another objective of this work is to evaluate the performance of various coating systems- CED, Epoxy, Powder coating, Autophoretic, and Zn-trivalent coating for vehicle underbody application. The corrosion resistance coating are assessed. From this study, a promising correlation between different corrosion testing techniques is noted. The most profound observation is that electrochemical tests gives quick estimation of corrosion resistance and can detect the degradation of coatings well before visible signs of damage appear. Furthermore, the corrosion resistances and salt spray life of the coatings investigated were found to be according to the order as follows- CED> powder coating > Autophoretic > epoxy coating > Zn- Trivalent plating.

Keywords: Linear Polarization Resistance (LPR), Electrochemical Impedance Spectroscopy (EIS), salt spray test, sacrificial and barrier coatings

Procedia PDF Downloads 526

Authors: Shengnan Chen, Shuhua Wang

Abstract:

Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

Procedia PDF Downloads 283

Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

Abstract:

In general, state-of-the-art Data Acquisition Systems (DAQ) in high energy physics experiments must satisfy high requirements in terms of reliability, efficiency and data rate capability. This paper presents the development and deployment of a debugging tool named DAQ Debugger for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. Utilizing a hardware event builder, the iFDAQ is designed to be able to readout data at the average maximum rate of 1.5 GB/s of the experiment. In complex softwares, such as the iFDAQ, having thousands of lines of code, the debugging process is absolutely essential to reveal all software issues. Unfortunately, conventional debugging of the iFDAQ is not possible during the real data taking. The DAQ Debugger is a tool for identifying a problem, isolating the source of the problem, and then either correcting the problem or determining a way to work around it. It provides the layer for an easy integration to any process and has no impact on the process performance. Based on handling of system signals, the DAQ Debugger represents an alternative to conventional debuggers provided by most integrated development environments. Whenever problem occurs, it generates reports containing all necessary information important for a deeper investigation and analysis. The DAQ Debugger was fully incorporated to all processes in the iFDAQ during the run 2016. It helped to reveal remaining software issues and improved significantly the stability of the system in comparison with the previous run. In the paper, we present the DAQ Debugger from several insights and discuss it in a detailed way.

Keywords: DAQ Debugger, data acquisition system, FPGA, system signals, Qt framework

Procedia PDF Downloads 284

Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

Abstract:

Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

Procedia PDF Downloads 138

Authors: Ahmed Barakat, Nourhan Ahmed Saad, Mahmoud Hammad

Abstract:

Tracking and monitoring agricultural products, cold chain activities, and transportation in real-time can effectively ensure both the quality and safety of agricultural products, as well as reduce overall logistics costs. Effective supply chain practices are one of the main requirements for enhancing agricultural business in Egypt. Cold chain is among the best practices for the storage and transportation of perishable goods and has potential within the agricultural sector in Egypt. This practice has the scope of reducing the wastage of food and increasing the profitability with a reduction in costs. Even though it has several implementation challenges for the farmers, traders, and people involved in the entire supply chain, it has highlighted better benefits for all and for the export of goods for the economic progression for Egypt. The aim of this paper is to explore cold supply chain practices for the agriculture sector in Egypt, to enhance the export performance of fresh goods. In this context, this study attempts to explore those aspects of the performance of cold supply chain practices that can enhance the functioning of the agriculture sector in Egypt from the perspective of export companies (traders) and farmers. Based on the empirical results obtained by data collection from the farmers and traders, the study argues that there is a significant association between cold supply chain practices and enhancement of the agriculture value chain. The paper thus highlights the contribution of the study with final conclusions and limitations with scope for future research.

Keywords: agriculture sector, cold chain management, export companies, non-traded goods, supply chain management

Procedia PDF Downloads 162

Authors: Ada Garus

Abstract:

This paper presents the outcomes of the sustainability assessment of food delivery with a last-mile delivery service introduced in a real-world case study. The methodology used in the sustainability assessment integrates multi-criteria decision-making analysis, sustainability pillars, and scenario analysis to best reflect the conflicting needs of stakeholders involved in the last mile delivery system. The case study provides an application of the framework to the food delivery system of the Joint Research Centre of the European Commission where three alternative solutions were analyzed I) the existent state in which individuals frequent the local cantine or pick up their food, using their preferred mode of transport II) the hypothetical scenario in which individuals can only order their food using the delivery droid system III) a scenario in which the food delivery droid based system is introduced as a supplement to the current system. The environmental indices are calculated using a simulation study in which decision regarding the food delivery is predicted using a multinomial logit model. The vehicle dynamics model is used to predict the fuel consumption of the regular combustion engines vehicles used by the cantine goers and the electricity consumption of the droid. The sustainability assessment allows for the evaluation of the economic, environmental, and social aspects of food delivery, making it an apt input for policymakers. Moreover, the assessment is one of the first studies to investigate automated delivery droids, which could become a frequent addition to the urban landscape in the near future.

Keywords: innovations in transportation technologies, behavioural change and mobility, urban freight logistics, innovative transportation systems

Procedia PDF Downloads 193

Authors: Ali A. Ukasha, Majdi F. Elbireki, Mohammad F. Abdullah

Abstract:

Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression and salt and peppers attacks, bitplanes decomposition, Arnold transform, color image, wavelet transform, lossless image encryption

Procedia PDF Downloads 518

Authors: Sagar Ghos, Andrew E. Elaryan, Syed Ashik Ali, Musharraf Zaman, Mohammed Ashiqur Rahman

Abstract:

Achieving desired density during construction is an important indicator of pavement quality. Insufficient compaction often compromises pavement performance and service life. Intelligent compaction (IC) is an emerging technology for monitoring compaction quality during the construction of asphalt pavements. This paper aims to provide an overview of findings from four case studies in Oklahoma involving the compaction quality of asphalt pavements, namely SE 44th St project (Project 1) and EOC Turnpike project (Project 2), Highway 92 project (Project 3), and 108th Avenue project (Project 4). For this purpose, an IC technology, the intelligent compaction analyzer (ICA), developed at the University of Oklahoma, was used to evaluate compaction quality. Collected data include GPS locations, roller vibrations, roller speed, the direction of movement, and temperature of the asphalt mat. The collected data were analyzed using a widely used software, VETA. The average densities for Projects 1, 2, 3 and 4, were found as 89.8%, 91.50%, 90.7% and 87.5%, respectively. The maximum densities were found as 94.6%, 95.8%, 95.9%, and 89.7% for Projects 1, 2, 3, and 4, respectively. It was observed that the ICA estimated densities correlated well with the field core densities. The ICA results indicated that at least 90% of the asphalt mats were subjected to at least two roller passes. However, the number of passes required to achieve the desired density (94% to 97%) differed from project to project depending on the underlying layer. The results of these case studies show both opportunities and challenges in using IC for monitoring compaction quality during construction in real-time.

Keywords: asphalt pavement construction, density, intelligent compaction, intelligent compaction analyzer, intelligent compaction measure value

Procedia PDF Downloads 158

Authors: Tim Steinhaus, Christian Beidl

Abstract:

Urban air quality and climate protection are two major challenges for future mobility systems. Despite the steady reduction of pollutant emissions from vehicles over past decades, local immission load within cities partially still reaches heights, which are considered hazardous to human health. Although traffic-related emissions account for a major part of the overall urban pollution, modeling the exact interaction remains challenging. In this paper, a novel approach for the determination of the emission-immission interaction on the basis of neural network modeling for traffic induced NO2-immission load within a near-traffic hot-spot scenario is presented. In a detailed sensitivity analysis, the significance of relevant influencing variables on the prevailing NO2 concentration is initially analyzed. Based on this, the generation process of the model is described, in which not only environmental influences but also the vehicle fleet composition including its associated segment- and certification-specific real driving emission factors are derived and used as input quantities. The validity of this approach, which has been presented in the past, is re-examined in this paper using updated data on vehicle emissions and recent immission measurement data. Within the framework of a final scenario analysis, the future development of the immission load is forecast for different developments in the vehicle fleet composition. It is shown that immission levels of less than half of today’s yearly average limit values are technically feasible in hot-spot situations.

Keywords: air quality, emission, emission-immission-interaction, immission, NO2, zero impact

Procedia PDF Downloads 126

Authors: Rafael Santos Fischer, Aloísio Leoni Schmid, Amanda Dalla-Bonna

Abstract:

The life cycle analysis and the energy life cycle analysis are useful design support tools when sustainability becomes imperative. The final phase of buildings life cycle is probably the least known, on which less knowledge is available. In the Brazilian building industry, the lifespan of a building design rarely is treated as a definite design parameter. There is rather a common sense attitude to take any building demands as permanent, and to take for granted that buildings solutions are durable and solid. Housing, being a permanent issue in any society, presents a real challenge to the choice of a design lifespan. In Brazilian history, there was a contrast of the native solutions of collective, non-durable houses built by several nomadic tribes, and the stone and masonry buildings introduced by the sedentary Portuguese conquerors. Durable buildings are commonly associated with welfare. However, social dynamics makes traditional families of both parents and children be just one of several possible arrangements. In addition, a more liberal attitude towards family leads to an increase in the number of people living in alternative arrangements. Japan is an example of country where houses have been made intentionally ephemeral since the half of 20th century. The present article presents the development of a flexible housing design solution on the basis of the Design Science Research approach. A comparison in terms of energy life cycle shows how flexibility and dematerialization may point at a feasible future for housing policies in Brazil.

Keywords: adaptability, adaptable building, embodied energy, life cyclce analysis, social housing

Procedia PDF Downloads 589

Authors: Esra Güney, Tuba Uçar

Abstract:

Aim: This study has been conducted for the purpose of determining the effects of fetal movement counting on antenatal maternal attachment. Material and Method: This research was conducted on the basis of the real test model with the pre-test /post-test control groups. The study population consists of pregnant women registered in the six different Family Health Centers located in the central Malatya districts of Yeşilyurt and Battalgazi. When power analysis is done, the sample size was calculated for each group of at least 55 pregnant women (55 tests, 55 controls). The data were collected by using Personal Information Form and MAAS (Maternal Antenatal Attachment Scale) between July 2015-June 2016. Fetal movement counting training was given to pregnant women by researchers in the experimental group after the pre-test data collection. No intervention was applied to the control group. Post-test data for both groups were collected after four weeks. Data were evaluated with percentage, chi-square arithmetic average, chi-square test and as for the dependent and independent group’s t test. Result: In the MAAS, the pre-test average of total scores in the experimental group is 70.78±6.78, control group is also 71.58±7.54 and so there was no significant difference in mean scores between the two groups (p>0.05). MAAS post-test average of total scores in the experimental group is 78.41±6.65, control group is also is 72.25±7.16 and so the mean scores between groups were found to have statistically significant difference (p<0.05). Conclusion: It was determined that fetal movement counting increases the maternal antenatal attachments.

Keywords: antenatal maternal attachment, fetal movement counting, pregnancy, midwifery

Procedia PDF Downloads 272

Authors: Seyedeh Rozhano Azimi Hashemi

Abstract:

There is no doubt that ‘Art’ is a social phenomena and cinema is the most social kind of art. Hence, it’s clear that we can analyze the relation’s of cinema and art from different aspects. In this paper sociological cinema will be investigated which, is a subdivision of sociological art. This term will be discussed by two main approaches. One of these approaches is focused on the effects of cinema on the society, which is known as “Effects Theory” and the second one, which is dealing with the reflection of social issues in cinema is called ” Reflection Theory”. "Reflect theory" approach, unlike "Effects theory" is considering movies as documents, in which social life is reflected, and by analyzing them, the changes and tendencies of a society are understood. Criticizing these approaches to cinema and society doesn’t mean that they are not real. Conversely, it proves the fact that for better understanding of cinema and society’s relation, more complicated models are required, which should consider two aspects. First, they should be bilinear and they should provide a dynamic and active relation between cinema and society, as for the current concept social life and cinema have bi-linear effects on each other, and that’s how they fit in a dialectic and dynamic process. Second, it should pay attention to the role of inductor elements such as small social institutions, marketing, advertisements, cultural pattern, art’s genres and popular cinema in society. In the current study, image of middle class in cinema of Iran and changing the role of women in cinema and society which were two bold issue that cinema and society faced since 1979 revolution till 80s are analyzed. Films as an artwork on one hand, are reflections of social changes and with their effects on the society on the other hand, are trying to speed up the trends of these changes. Cinema by the illustration of changes in ideologies and approaches in exaggerated ways and through it’s normalizing functions, is preparing the audiences and public opinions for the acceptance of these changes. Consequently, audience takes effect from this process, which is a bi-linear and interactive process.

Keywords: Iranian Cinema, Cinema and Society, Middle Class, Woman’s Role

Procedia PDF Downloads 340