Search results for: probability weighted moment estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4244

Search results for: probability weighted moment estimation

2894 The Effect of Conservative Tillage on Physical Properties of Soil and Yield of Rainfed Wheat

Authors: Abolfazl Hedayatipoor, Mohammad Younesi Alamooti

Abstract:

In order to study the effect of conservative tillage on a number of physical properties of soil and the yield of rainfed wheat, an experiment in the form of a randomized complete block design (RCBD) with three replications was conducted in a field in Aliabad County, Iran. The study treatments included: T1) Conventional method, T2) Combined moldboard plow method, T3) Chisel-packer method, and T4) Direct planting method. During early October, the study soil was prepared based on these treatments in a field which was used for rainfed wheat farming in the previous year. The apparent specific gravity of soil, weighted mean diameter (WMD) of soil aggregates, soil mechanical resistance, and soil permeability were measured. Data were analyzed in MSTAT-C. Results showed that the tillage practice had no significant effect on grain yield (p < 0.05). Soil permeability was 10.9, 16.3, 15.7 and 17.9 mm/h for T1, T2, T3 and T4, respectively.

Keywords: rainfed agriculture, conservative tillage, energy consumption, wheat

Procedia PDF Downloads 190
2893 Functionalized SPIO Conjugated with Doxorubicin for Tumor Diagnosis and Chemotherapy Enhanced by Applying Magnetic Fields

Authors: Po-Chin Liang, Yung-Chu Chen, Chi-Feng Chiang, Yun-Ping Lin, Wen-Yuan Hsieh, Win-Li Lin

Abstract:

The aim of this study was to develop super paramagnetic iron oxide (SPIO) nano-particles comprised of a magnetic Fe3O4 core and a shell of aqueous stable self-doped polyethylene glycol (PEG) with a high loading of doxorubicin (SPIO-PEG-D) for tumor theranostics. The in-vivo MRI study showed that there was a stronger T2-weighted signal enhancement for the group under a magnetic field, and hence it indicated that this group had a better accumulation of SPIO-PEG than the group without a magnetic field. In the anticancer evaluation of SPIO-PEG-D, the group with a magnetic field displayed a significantly smaller tumor size than the group without. The overall results show that SPIO-PEG-D nanoparticles have the potential for the application of MRI/monitoring chemotherapy and the therapy can be locally enhanced by applying an external magnetic field.

Keywords: super paramagnetic iron oxide nano particles, doxorubicin, chemotherapy, MRI, magnetic fields

Procedia PDF Downloads 583
2892 Mathematics Teachers’ Background Characteristics as a Correlate of Secondary School Students’ Achievement in Mathematics in Gombe State, Nigeria

Authors: Ali Adamu

Abstract:

Teachers’ background characteristics as a correlate of students’ achievement in Mathematics were studied in Gombe State. Pearson Product Moment Correlation Coefficient was used for the analysis. Five Hundred and Twelve (512) students and 20 teachers from 12 schools in Gombe State of Nigeria were used for the study. Students’ Achievement Tests and Mathematics Teachers’ backgrounds were instruments for the study. The findings indicated that teachers’ qualifications, experience of the teacher, and teachers’ personalities had a positive correlation with students’ achievement. Recommendations are made, which include allowing the teachers to go for training as well as the government should ensure recruiting teachers that have experience in the teaching job.

Keywords: achievement-test, teachers’ personality, teaching mathematics, teacher-background

Procedia PDF Downloads 75
2891 Ensemble-Based SVM Classification Approach for miRNA Prediction

Authors: Sondos M. Hammad, Sherin M. ElGokhy, Mahmoud M. Fahmy, Elsayed A. Sallam

Abstract:

In this paper, an ensemble-based Support Vector Machine (SVM) classification approach is proposed. It is used for miRNA prediction. Three problems, commonly associated with previous approaches, are alleviated. These problems arise due to impose assumptions on the secondary structural of premiRNA, imbalance between the numbers of the laboratory checked miRNAs and the pseudo-hairpins, and finally using a training data set that does not consider all the varieties of samples in different species. We aggregate the predicted outputs of three well-known SVM classifiers; namely, Triplet-SVM, Virgo and Mirident, weighted by their variant features without any structural assumptions. An additional SVM layer is used in aggregating the final output. The proposed approach is trained and then tested with balanced data sets. The results of the proposed approach outperform the three base classifiers. Improved values for the metrics of 88.88% f-score, 92.73% accuracy, 90.64% precision, 96.64% specificity, 87.2% sensitivity, and the area under the ROC curve is 0.91 are achieved.

Keywords: MiRNAs, SVM classification, ensemble algorithm, assumption problem, imbalance data

Procedia PDF Downloads 324
2890 Using Seismic and GPS Data for Hazard Estimation in Some Active Regions in Egypt

Authors: Abdel-Monem Sayed Mohamed

Abstract:

Egypt rapidly growing development is accompanied by increasing levels of standard living particular in its urban areas. However, there is a limited experience in quantifying the sources of risk management in Egypt and in designing efficient strategies to keep away serious impacts of earthquakes. From the historical point of view and recent instrumental records, there are some seismo-active regions in Egypt, where some significant earthquakes had occurred in different places. The special tectonic features in Egypt: Aswan, Greater Cairo, Red Sea and Sinai Peninsula regions are the territories of a high seismic risk, which have to be monitored by up-to date technologies. The investigations of the seismic events and interpretations led to evaluate the seismic hazard for disaster prevention and for the safety of the dense populated regions and the vital national projects as the High Dam. In addition to the monitoring of the recent crustal movements, the most powerful technique of satellite geodesy GPS are used where geodetic networks are covering such seismo-active regions. The results from the data sets are compared and combined in order to determine the main characteristics of the deformation and hazard estimation for specified regions. The final compiled output from the seismological and geodetic analysis threw lights upon the geodynamical regime of these seismo-active regions and put Aswan and Greater Cairo under the lowest class according to horizontal crustal strains classifications. This work will serve a basis for the development of so-called catastrophic models and can be further used for catastrophic risk management. Also, this work is trying to evaluate risk of large catastrophic losses within the important regions including the High Dam, strategic buildings and archeological sites. Studies on possible scenarios of earthquakes and losses are a critical issue for decision making in insurance as a part of mitigation measures.

Keywords: b-value, Gumbel distribution, seismic and GPS data, strain parameters

Procedia PDF Downloads 436
2889 Integrating Technology in Teaching and Learning Mathematics

Authors: Larry Wang

Abstract:

The aim of this paper is to demonstrate how an online homework system is integrated in teaching and learning mathematics and how it improves the student success rates in some gateway mathematics courses. WeBWork provided by the Mathematical Association of America is adopted as the online homework system. During the period of 2010-2015, the system was implemented in classes of precalculus, calculus, probability and statistics, discrete mathematics, linear algebra, and differential equations. As a result, the passing rates of the sections with WeBWork are well above other sections without WeBWork (about 7-10% higher). The paper also shows how the WeBWork system was used.

Keywords: gateway mathematics, online grading, pass rate, WeBWorK

Procedia PDF Downloads 275
2888 An Accelerated Stochastic Gradient Method with Momentum

Authors: Liang Liu, Xiaopeng Luo

Abstract:

In this paper, we propose an accelerated stochastic gradient method with momentum. The momentum term is the weighted average of generated gradients, and the weights decay inverse proportionally with the iteration times. Stochastic gradient descent with momentum (SGDM) uses weights that decay exponentially with the iteration times to generate the momentum term. Using exponential decay weights, variants of SGDM with inexplicable and complicated formats have been proposed to achieve better performance. However, the momentum update rules of our method are as simple as that of SGDM. We provide theoretical convergence analyses, which show both the exponential decay weights and our inverse proportional decay weights can limit the variance of the parameter moving directly to a region. Experimental results show that our method works well with many practical problems and outperforms SGDM.

Keywords: exponential decay rate weight, gradient descent, inverse proportional decay rate weight, momentum

Procedia PDF Downloads 144
2887 Classification of Digital Chest Radiographs Using Image Processing Techniques to Aid in Diagnosis of Pulmonary Tuberculosis

Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

Abstract:

Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

Procedia PDF Downloads 103
2886 Learning from Long COVID: How Healthcare Needs to Change for Contested Illnesses

Authors: David Tennison

Abstract:

In the wake of the Covid-19 pandemic, a new chronic illness emerged onto the global stage: Long Covid. Long Covid presents with several symptoms commonly seen in other poorly-understood illnesses, such as fibromyalgia (FM) and myalgic encephalomyelitis/ chronic fatigue syndrome (ME/CFS). However, while Long Covid has swiftly become a recognised illness, FM and ME/CFS are still seen as contested, which impacts patient care and healthcare experiences. This study aims to examine what the differences are between Long Covid and FM; and if the Long Covid case can provide guidance for how to address the healthcare challenge of contested illnesses. To address this question, this study performed comprehensive research into the history of FM; our current biomedical understanding of it; and available healthcare interventions (within the context of the UK NHS). Analysis was undertaken of the stigma and stereotypes around FM, and a comparison made between FM and the emerging Long Covid literature, along with the healthcare response to Long Covid. This study finds that healthcare for chronic contested illnesses in the UK is vastly insufficient - in terms of pharmaceutical and holistic interventions, and the provision of secondary care options. Interestingly, for Long Covid, many of the treatment suggestions are pulled directly from those used for contested illnesses. The key difference is in terms of funding and momentum – Long Covid has generated exponentially more interest and research in a short time than there has been in the last few decades of contested illness research. This stands to help people with FM and ME/CFS – for example, research has recently been funded into “brain fog”, a previously elusive and misunderstood symptom. FM is culturally regarded as a “women’s disease” and FM stigma stems from notions of “hysteria”. A key finding is that the idea of FM affecting women disproportionally is not reflected in modern population studies. Emerging data on Long Covid also suggests a slight leaning towards more female patients, however it is less feminised, potentially due to it emerging in the global historical moment of the pandemic. Another key difference is that FM is rated as an extremely low-prestige illness by healthcare professionals, while it was in large part due to the advocacy of affected healthcare professionals that Long Covid was so quickly recognised by science and medicine. In conclusion, Long Covid (and the risk of future pandemics and post-viral illnesses) highlight a crucial need for implementing new, and reinforcing existing, care networks for chronic illnesses. The difference in how contested illnesses like FM, and new ones like Long Covid are treated have a lot to do with the historical moment in which they emerge – but cultural stereotypes, from within and without medicine, need updating. Particularly as they contribute to disease stigma that causes genuine harm to patients. However, widespread understanding and acceptance of Long Covid could help fight contested illness stigma, and the attention, funding and research into Long Covid may actually help raise the profile of contested illnesses and uncover answers about their symptomatology.

Keywords: long COVID, fibromyalgia, myalgic encephalomyelitis, chronic fatigue syndrome, NHS, healthcare, contested illnesses, chronic illnesses, COVID-19 pandemic

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2885 Optimum Design of Helical Gear System on Basis of Maximum Power Transmission Capability

Authors: Yasaman Esfandiari

Abstract:

Mechanical engineering has always dealt with amplification of the input power in power trains. One of the ways to achieve this goal is to use gears to change the amplitude and direction of the torque and the speed. However, the gears should be optimally designed to best achieve these objectives. In this study, helical gear systems are optimized to achieve maximum power. Material selection, space restriction, available facilities for manufacturing, the probability of tooth breakage, and tooth wear are taken into account and governing equations are derived. Finally, a Matlab code was generated to solve the optimization problem and the results are verified.

Keywords: design, gears, Matlab, optimization

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2884 Clinical Feature Analysis and Prediction on Recurrence in Cervical Cancer

Authors: Ravinder Bahl, Jamini Sharma

Abstract:

The paper demonstrates analysis of the cervical cancer based on a probabilistic model. It involves technique for classification and prediction by recognizing typical and diagnostically most important test features relating to cervical cancer. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases. The combination of the conventional statistical and machine learning tools is applied for the analysis. Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Keywords: cervical cancer, recurrence, no recurrence, probabilistic, classification, prediction, machine learning

Procedia PDF Downloads 345
2883 Discovering Event Outliers for Drug as Commercial Products

Authors: Arunas Burinskas, Aurelija Burinskiene

Abstract:

On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

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2882 Storage Assignment Strategies to Reduce Manual Picking Errors with an Emphasis on an Ageing Workforce

Authors: Heiko Diefenbach, Christoph H. Glock

Abstract:

Order picking, i.e., the order-based retrieval of items in a warehouse, is an important time- and cost-intensive process for many logistic systems. Despite the ongoing trend of automation, most order picking systems are still manual picker-to-parts systems, where human pickers walk through the warehouse to collect ordered items. Human work in warehouses is not free from errors, and order pickers may at times pick the wrong or the incorrect number of items. Errors can cause additional costs and significant correction efforts. Moreover, age might increase a person’s likelihood to make mistakes. Hence, the negative impact of picking errors might increase for an aging workforce currently witnessed in many regions globally. A significant amount of research has focused on making order picking systems more efficient. Among other factors, storage assignment, i.e., the assignment of items to storage locations (e.g., shelves) within the warehouse, has been subject to optimization. Usually, the objective is to assign items to storage locations such that order picking times are minimized. Surprisingly, there is a lack of research concerned with picking errors and respective prevention approaches. This paper hypothesize that the storage assignment of items can affect the probability of pick errors. For example, storing similar-looking items apart from one other might reduce confusion. Moreover, storing items that are hard to count or require a lot of counting at easy-to-access and easy-to-comprehend self heights might reduce the probability to pick the wrong number of items. Based on this hypothesis, the paper discusses how to incorporate error-prevention measures into mathematical models for storage assignment optimization. Various approaches with respective benefits and shortcomings are presented and mathematically modeled. To investigate the newly developed models further, they are compared to conventional storage assignment strategies in a computational study. The study specifically investigates how the importance of error prevention increases with pickers being more prone to errors due to age, for example. The results suggest that considering error-prevention measures for storage assignment can reduce error probabilities with only minor decreases in picking efficiency. The results might be especially relevant for an aging workforce.

Keywords: an aging workforce, error prevention, order picking, storage assignment

Procedia PDF Downloads 185
2881 Modeling of Foundation-Soil Interaction Problem by Using Reduced Soil Shear Modulus

Authors: Yesim Tumsek, Erkan Celebi

Abstract:

In order to simulate the infinite soil medium for soil-foundation interaction problem, the essential geotechnical parameter on which the foundation stiffness depends, is the value of soil shear modulus. This parameter directly affects the site and structural response of the considered model under earthquake ground motions. Strain-dependent shear modulus under cycling loads makes difficult to estimate the accurate value in computation of foundation stiffness for the successful dynamic soil-structure interaction analysis. The aim of this study is to discuss in detail how to use the appropriate value of soil shear modulus in the computational analyses and to evaluate the effect of the variation in shear modulus with strain on the impedance functions used in the sub-structure method for idealizing the soil-foundation interaction problem. Herein, the impedance functions compose of springs and dashpots to represent the frequency-dependent stiffness and damping characteristics at the soil-foundation interface. Earthquake-induced vibration energy is dissipated into soil by both radiation and hysteretic damping. Therefore, flexible-base system damping, as well as the variability in shear strengths, should be considered in the calculation of impedance functions for achievement a more realistic dynamic soil-foundation interaction model. In this study, it has been written a Matlab code for addressing these purposes. The case-study example chosen for the analysis is considered as a 4-story reinforced concrete building structure located in Istanbul consisting of shear walls and moment resisting frames with a total height of 12m from the basement level. The foundation system composes of two different sized strip footings on clayey soil with different plasticity (Herein, PI=13 and 16). In the first stage of this study, the shear modulus reduction factor was not considered in the MATLAB algorithm. The static stiffness, dynamic stiffness modifiers and embedment correction factors of two rigid rectangular foundations measuring 2m wide by 17m long below the moment frames and 7m wide by 17m long below the shear walls are obtained for translation and rocking vibrational modes. Afterwards, the dynamic impedance functions of those have been calculated for reduced shear modulus through the developed Matlab code. The embedment effect of the foundation is also considered in these analyses. It can easy to see from the analysis results that the strain induced in soil will depend on the extent of the earthquake demand. It is clearly observed that when the strain range increases, the dynamic stiffness of the foundation medium decreases dramatically. The overall response of the structure can be affected considerably because of the degradation in soil stiffness even for a moderate earthquake. Therefore, it is very important to arrive at the corrected dynamic shear modulus for earthquake analysis including soil-structure interaction.

Keywords: clay soil, impedance functions, soil-foundation interaction, sub-structure approach, reduced shear modulus

Procedia PDF Downloads 253
2880 A Generalized Model for Performance Analysis of Airborne Radar in Clutter Scenario

Authors: Vinod Kumar Jaysaval, Prateek Agarwal

Abstract:

Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.

Keywords: airborne radar, blind zone, clutter, probability of detection

Procedia PDF Downloads 450
2879 Flow Dynamics of Nanofluids in a Horizontal Cylindrical Annulus Using Nonhomogeneous Dynamic Model

Authors: M. J. Uddin, M. M. Rahman

Abstract:

Transient natural convective flow dynamics of nanofluids in a horizontal homocentric annulus using nonhomogeneous dynamic model has been experimented numerically. The simulation is carried out for four different shapes of the inner wall, which is either cylindrical, elliptical, square or triangular. The outer surface of the annulus is maintained at constant low temperature while the inner wall is maintained at a uniform temperature; higher than the outer one. The enclosure is permeated by a uniform magnetic field having variable orientation. The Brownian motion and thermophoretic deposition phenomena of the nanoparticles are taken into account in model construction. The governing nonlinear momentum, energy, and concentration equations are solved numerically using Galerkin weighted residual finite element method. To find the best performer, the local Nusselt number is demonstrated for different shapes of the inner wall. The heat transfer enhancement for different nanofluids for four different shapes of the inner wall is exhibited.

Keywords: nanofluids, annulus, nonhomogeneous dynamic model, heat transfer

Procedia PDF Downloads 150
2878 Probabilistic Modeling Laser Transmitter

Authors: H. S. Kang

Abstract:

Coupled electrical and optical model for conversion of electrical energy into coherent optical energy for transmitter-receiver link by solid state device is presented. Probability distribution for travelling laser beam switching time intervals and the number of switchings in the time interval is obtained. Selector function mapping is employed to regulate optical data transmission speed. It is established that regulated laser transmission from PhotoActive Laser transmitter follows principal of invariance. This considerably simplifies design of PhotoActive Laser Transmission networks.

Keywords: computational mathematics, finite difference Markov chain methods, sequence spaces, singularly perturbed differential equations

Procedia PDF Downloads 414
2877 Supply, Trade-offs, and Synergies Estimation for Regulating Ecosystem Services of a Local Forest

Authors: Jang-Hwan Jo

Abstract:

The supply management of ecosystem services of local forests is an essential issue as it is linked to the ecological welfare of local residents. This study aims to estimate the supply, trade-offs, and synergies of local forest regulating ecosystem services using a land cover classification map (LCCM) and a forest types map (FTM). Rigorous literature reviews and Expert Delphi analysis were conducted using the detailed variables of 1:5,000 LCCM and FTM. Land-use scoring method and Getis-Ord Gi* Analysis were utilized on detailed variables to propose a method for estimating supply, trade-offs, and synergies of the local forest regulating ecosystem services. The analysis revealed that the rank order (1st to 5th) of supply of regulating ecosystem services was Erosion prevention, Air quality regulation, Heat island mitigation, Water quality regulation, and Carbon storage. When analyzing the correlation between defined services of the entire city, almost all services showed a synergistic effect. However, when analyzing locally, trade-off effects (Heat island mitigation – Air quality regulation, Water quality regulation – Air quality regulation) appeared in the eastern and northwestern forest areas. This suggests the need to consider not only the synergy and trade-offs of the entire forest between specific ecosystem services but also the synergy and trade-offs of local areas in managing the regulating ecosystem services of local forests. The study result can provide primary data for the stakeholders to determine the initial conditions of the planning stage when discussing the establishment of policies related to the adjustment of the supply of regulating ecosystem services of the forests with limited access. Moreover, the study result can also help refine the estimation of the supply of the regulating ecosystem services with the availability of other forms of data.

Keywords: ecosystem service, getis ord gi* analysis, land use scoring method, regional forest, regulating service, synergies, trade-offs

Procedia PDF Downloads 62
2876 Investigating the Effects of Data Transformations on a Bi-Dimensional Chi-Square Test

Authors: Alexandru George Vaduva, Adriana Vlad, Bogdan Badea

Abstract:

In this research, we conduct a Monte Carlo analysis on a two-dimensional χ2 test, which is used to determine the minimum distance required for independent sampling in the context of chaotic signals. We investigate the impact of transforming initial data sets from any probability distribution to new signals with a uniform distribution using the Spearman rank correlation on the χ2 test. This transformation removes the randomness of the data pairs, and as a result, the observed distribution of χ2 test values differs from the expected distribution. We propose a solution to this problem and evaluate it using another chaotic signal.

Keywords: chaotic signals, logistic map, Pearson’s test, Chi Square test, bivariate distribution, statistical independence

Procedia PDF Downloads 77
2875 Female Labor Force Participation in Iranian Rural Areas: An Inter-provincial Study

Authors: Zahra Mila Elmi, Mahsa Khanekheshi

Abstract:

Almost half of the population and potential manpower in the country and rural areas are women. Manpower especially educated people, plays an important role in the production and economic growth. Also, the potential of rural areas to create employment should not be overlooked. In this research, the effects of socio-economic and demographic factors on women's economic participation in rural areas of Iran's provinces will be studied. Therefore, this study was performed by using the results of the rural households income and expenditure surveys -has been taken in 2016- in the framework of pseudo panel data. This study used the logit model and the maximum likelihood method to study the rural women's participation, with 28,265 observations. Results show the inverted U-shaped relationship between age and the probability of female participation; In other words, young women are more likely to participate in labor markets more than the other groups. Divorced and single woman has more chance of participation in comparison with who was being married. With increasing the divorce rate and singleness in Iran, economic policymakers must provide appropriate solutions for this challenge in the coming years. On the base of the results, being a student and the presence of an infant under the age of 6 in the household has a negative effect on the possibility of women's participation in the labor market. The women's education level has a U-shaped relationship with their participation rate. Illiteracy and high education have a strong positive effect on the economic participation of rural women. This shows the dual labor market for women in Iran. Illiterate women are attracted to service jobs, and educated woman are more attracted to education and health jobs. Increasing household income has a small but positive and significant effect on the probability of rural female participation. In the overlook, due to the frequency of the women population in the age group of 25 to 35 years, and more willingness of women in the age 35 to 44 years to participate in the labor market, and studying ofa significant portion of the rural women, the increase of rural female participation is expected in the years ahead. Thus, it is expected policy maker to create new job opportunities for the employment of educated women and take the necessary plan to improve the current situation for women.

Keywords: female participation rate, rural area, provincial data, pseudo-panel data method

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2874 Economic and Technical Study for Hybrid (PV/Wind) Power System in the North East of Algeria

Authors: Nabila Louai, Fouad Khaldi, Houria Benharchache

Abstract:

In this paper, the case of meeting a household’s electrical energy demand with hybrid systems has been examined. The objective is to study technological feasibility and economic viability of the electrification project by a hybrid system (PV/ wind) of a residential home located in Batna-Algeria and to reduce the emissions from traditional power by using renewable energy. An autonomous hybrid wind/photovoltaic (PV)/battery power system and a PV/Wind grid connected system, has been carried out using Hybrid Optimization Model for Electric Renewable (HOMER) simulation software. As a result, it has been found that electricity from the grid can be supplied at a lower price than electricity from renewable energy at this moment.

Keywords: batna, household, hybrid system, renewable energy, techno-economy

Procedia PDF Downloads 582
2873 The Gasoil Hydrofining Kinetics Constants Identification

Authors: C. Patrascioiu, V. Matei, N. Nicolae

Abstract:

The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: hydrofining, kinetic, modeling, optimization

Procedia PDF Downloads 418
2872 Phase II Monitoring of First-Order Autocorrelated General Linear Profiles

Authors: Yihua Wang, Yunru Lai

Abstract:

Statistical process control has been successfully applied in a variety of industries. In some applications, the quality of a process or product is better characterized and summarized by a functional relationship between a response variable and one or more explanatory variables. A collection of this type of data is called a profile. Profile monitoring is used to understand and check the stability of this relationship or curve over time. The independent assumption for the error term is commonly used in the existing profile monitoring studies. However, in many applications, the profile data show correlations over time. Therefore, we focus on a general linear regression model with a first-order autocorrelation between profiles in this study. We propose an exponentially weighted moving average charting scheme to monitor this type of profile. The simulation study shows that our proposed methods outperform the existing schemes based on the average run length criterion.

Keywords: autocorrelation, EWMA control chart, general linear regression model, profile monitoring

Procedia PDF Downloads 439
2871 Modelling Spatial Dynamics of Terrorism

Authors: André Python

Abstract:

To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

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2870 First Principle Calculation of The Magnetic Properties of Mn-doped 6H-SiC

Authors: M. Al Azri, M. Elzain, K. Bouziane, S. M. Chérif

Abstract:

The electronic and magnetic properties of 6H-SiC with Mn impurities have been calculated using ab-initio calculations. Various configurations of Mn sites and Si and C vacancies were considered. The magnetic coupling between the two Mn atoms at substitutional and interstitials sites with and without vacancies is studied as a function of Mn atoms interatomic distance. It was found that the magnetic interaction energy decreases with increasing distance between the magnetic atoms. The energy levels appearing in the band gap due to vacancies and due to Mn impurities are determined. The calculated DOS’s are used to analyze the nature of the exchange interaction between the impurities. The band coupling model based on the p-d and d-d level repulsions between Mn and SiC has been used to describe the magnetism observed in each configuration. Furthermore, the impacts of applying U to Mn-d orbital on the magnetic moment have also been investigated. The results are used to understand the experimental data obtained on Mn- 6H-SiC (as-implanted and as –annealed) for various Mn concentration (CMn = 0.7%, 1.6%, 7%).

Keywords: ab-initio calculations, diluted magnetic semiconductors, magnetic properties, silicon carbide

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2869 Estimation and Forecasting Debris Flow Phenomena on the Highway of the 'TRACECA' Corridor

Authors: Levan Tsulukidze

Abstract:

The paper considers debris flow phenomena and forecasting of them in the corridor of ‘TRACECA’ on the example of river Naokhrevistkali, as well as the debris flow -type channel passing between the villages of Vale-2 and Naokhrevi. As a result of expeditionary and reconnaissance investigations, as well as using empiric dependencies, the debris flow expenditure has been estimated in case of different debris flow provisions.

Keywords: debris flow, Traceca corridor, forecasting, river Naokhrevistkali

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2868 Bit Error Rate (BER) Performance of Coherent Homodyne BPSK-OCDMA Network for Multimedia Applications

Authors: Morsy Ahmed Morsy Ismail

Abstract:

In this paper, the structure of a coherent homodyne receiver for the Binary Phase Shift Keying (BPSK) Optical Code Division Multiple Access (OCDMA) network is introduced based on the Multi-Length Weighted Modified Prime Code (ML-WMPC) for multimedia applications. The Bit Error Rate (BER) of this homodyne detection is evaluated as a function of the number of active users and the signal to noise ratio for different code lengths according to the multimedia application such as audio, voice, and video. Besides, the Mach-Zehnder interferometer is used as an external phase modulator in homodyne detection. Furthermore, the Multiple Access Interference (MAI) and the receiver noise in a shot-noise limited regime are taken into consideration in the BER calculations.

Keywords: OCDMA networks, bit error rate, multiple access interference, binary phase-shift keying, multimedia

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2867 Evaluating Daylight Performance in an Office Environment in Malaysia, Using Venetian Blind Systems

Authors: Fatemeh Deldarabdolmaleki, Mohamad Fakri Zaky Bin Ja'afar

Abstract:

This paper presents fenestration analysis to study the balance between utilizing daylight and eliminating the disturbing parameters in a private office room with interior venetian blinds taking into account different slat angles. Mean luminance of the scene and window, luminance ratio of the workplane and window, work plane illumination and daylight glare probability(DGP) were calculated as a function of venetian blind design properties. Recently developed software, analyzing High Dynamic Range Images (HDRI captured by CCD camera), such as radiance based evalglare and hdrscope help to investigate luminance-based metrics. A total of Eight-day measurement experiment was conducted to investigate the impact of different venetian blind angles in an office environment under daylight condition in Serdang, Malaysia. Detailed result for the selected case study showed that artificial lighting is necessary during the morning session for Malaysian buildings with southwest windows regardless of the venetian blind’s slat angle. However, in some conditions of afternoon session the workplane illuminance level exceeds the maximum illuminance of 2000 lx such as 10° and 40° slat angles. Generally, a rising trend is discovered toward mean window luminance level during the day. All the conditions have less than 10% of the pixels exceeding 2000 cd/m² before 1:00 P.M. However, 40% of the selected hours have more than 10% of the scene pixels higher than 2000 cd/m² after 1:00 P.M. Surprisingly in no blind condition, there is no extreme case of window/task ratio, However, the extreme cases happen for 20°, 30°, 40° and 50° slat angles. As expected mean window luminance level is higher than 2000 cd/m² after 2:00 P.M for most cases except 60° slat angle condition. Studying the daylight glare probability, there is not any DGP value higher than 0.35 in this experiment, due to the window’s direction, location of the building and studied workplane. Specifically, this paper reviews different blind angle’s response to the suggested metrics by the previous standards, and finally conclusions and knowledge gaps are summarized and suggested next steps for research are provided. Addressing these gaps is critical for the continued progress of the energy efficiency movement.

Keywords: daylighting, office environment, energy simulation, venetian blind

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2866 Numerical Analysis of End Plate Bolted Connection with Corrugated Beam

Authors: M. A. Sadeghian, J. Yang, Q. F. Liu

Abstract:

Steel extended end plate bolted connections are recommended to be widely utilized in special moment-resisting frame subjected to monotonic loading. Improper design of steel beam to column connection can lead to the collapse and fatality of structures. Therefore comprehensive research studies of beam to column connection design should be carried out. Also the performance and effect of corrugated on the strength of beam column end plate connection up to failure under monotonic loading in horizontal direction is presented in this paper. The non-linear elastic–plastic behavior has been considered through a finite element analysis using the multi-purpose software package LUSAS. The effect of vertically and horizontally types of corrugated web was also investigated.

Keywords: corrugated beam, monotonic loading, finite element analysis, end plate connection

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2865 A Modified Decoupled Semi-Analytical Approach Based On SBFEM for Solving 2D Elastodynamic Problems

Authors: M. Fakharian, M. I. Khodakarami

Abstract:

In this paper, a new trend for improvement in semi-analytical method based on scale boundaries in order to solve the 2D elastodynamic problems is provided. In this regard, only the boundaries of the problem domain discretization are by specific sub-parametric elements. Mapping functions are uses as a class of higher-order Lagrange polynomials, special shape functions, Gauss-Lobatto -Legendre numerical integration, and the integral form of the weighted residual method, the matrix is diagonal coefficients in the equations of elastodynamic issues. Differences between study conducted and prior research in this paper is in geometry production procedure of the interpolation function and integration of the different is selected. Validity and accuracy of the present method are fully demonstrated through two benchmark problems which are successfully modeled using a few numbers of DOFs. The numerical results agree very well with the analytical solutions and the results from other numerical methods.

Keywords: 2D elastodynamic problems, lagrange polynomials, G-L-Lquadrature, decoupled SBFEM

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