Search results for: exponentially weighted moving average
Commenced in January 2007
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Edition: International
Paper Count: 6127

Search results for: exponentially weighted moving average

5677 Human Resource Development Climate (HRDC) in Nigerian Banks: General and Gender Perceptions

Authors: Akinyemi Benjamin

Abstract:

This study investigates the prevailing HRDC Nigerian commercial banks as perceived by employees in general. The perceptional differences on the state of HRDC by gender category are also examined. Using Abraham and Rao’s HRDC 38-item questionnaire, data from 310 respondents, with 303 valid responses, were entered into excel sheet and analysed to determine frequencies, mean scores, standard deviation and percentages for four variables: HRDC, general climate, HRD mechanism, and OCTAPAC culture. Results of analysis indicate that generally, employees perceive the overall HRDC and its three dimensions of general climate, HRD mechanism and OCTAPAC culture to be at an average or moderate level. The perceptions of both male and female subjects also indicate an average HRDC level although participants report slightly higher scores than their male subjects but these scores are still at an average level on all the dimensions of HRDC measured. The implications of this result for organizations in general and the banking industry in particular are discussed.

Keywords: HRDC, HRD mechanism, general climate, OCTAPAC culture, gender

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5676 The Distribution and Environmental Behavior of Heavy Metals in Jajarm Bauxite Mine, Northeast Iran

Authors: Hossein Hassani, Ali Rezaei

Abstract:

Heavy metals are naturally occurring elements that have a high atomic weight and a density at least five times greater than that of water. Their multiple industrial, domestic, agricultural, medical, and technological applications have led to their wide distribution in the environment, raising concerns over their potential effects on human health and the environment. Environmental protection against various pollutants, such as heavy metals formed by industries, mines and modern technologies, is a concern for researchers and industry. In order to assess the contamination of soils the distribution and environmental behavior have been investigated. Jajarm bauxite mine, the most important deposits have been discovered in Iran, which is about 22 million tons of reserve, and is the main mineral of the Diaspora. With a view to estimate the heavy metals ratio of the Jajarm bauxite mine area and to evaluate the pollution level, 50 samples have been collected and have been analyzed for the heavy metals of As, Cd, Cu, Hg, Ni and Pb with the help of Inductively Coupled Plasma-Mass Spectrometer (ICP- MS). In this study, we have dealt with determining evaluation criteria including contamination factor (CF), average concentration (AV), enrichment factor (EF) and geoaccumulation index (GI) to assess the risk of pollution from heavy metals(As, Cd, Cu, Hg, Ni and Pb) in Jajarm bauxite mine. In the samples of the studied, the average of recorded concentration of elements for Arsenic, Cadmium, Copper, Mercury, Nickel and Lead are 18, 0.11, 12, 0.07, 58 and 51 (mg/kg) respectively. The comparison of the heavy metals concentration average and the toxic potential in the samples has shown that an average with respect to the world average of the uncontaminated soil amounts. The average of Pb and As elements shows a higher quantity with respect to the world average quantity. The pollution factor for the study elements has been calculated on the basis of the soil background concentration and has been categorized on the basis of the uncontaminated world soil average with respect to the Hakanson classification. The calculation of the corrected pollutant degree shows the degree of the bulk intermediate pollutant (1.55-2.0) for the average soil sampling of the study area which is on the basis of the background quantity and the world average quantity of the uncontaminated soils. The provided conclusion from calculation of the concentrated factor, for some of the samples show that the average of the lead and arsenic elements stations are more than the background values and the unnatural metal concentration are covered under the study area, That's because the process of mining and mineral extraction. Given conclusion from the calculation of Geoaccumulation index of the soil sampling can explain that the copper, nickel, cadmium, arsenic, lead and mercury elements are Uncontamination. In general, the results indicate that the Jajarm bauxite mine of heavy metal pollution is uncontaminated area and extract the mineral from the mine, not create environmental hazards in the region.

Keywords: enrichment factor, geoaccumulation index, heavy metals, Jajarm bauxite mine, pollution

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5675 Tensor Deep Stacking Neural Networks and Bilinear Mapping Based Speech Emotion Classification Using Facial Electromyography

Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

Abstract:

Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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5674 Finite Element Method for Calculating Temperature Field of Main Cable of Suspension Bridge

Authors: Heng Han, Zhilei Liang, Xiangong Zhou

Abstract:

In this paper, the finite element method is used to study the temperature field of the main cable of the suspension bridge, and the calculation method of the average temperature of the cross-section of the main cable suitable for the construction control of the cable system is proposed; By comparing and analyzing the temperature field of the main cable with five diameters, a reasonable diameter limit for calculating the average temperature of the cross section of the main cable by finite element method is proposed. The results show that the maximum error of this method is less than 1℃, which meets the requirements of construction control accuracy; For the main cable with a diameter greater than 400mm, the surface temperature measuring points combined with the finite element method shall be used to calculate the average cross-section temperature.

Keywords: suspension bridge, main cable, temperature field, finite element

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5673 Numerical Simulation of Fluid-Structure Interaction on Wedge Slamming Impact by Using Particle Method

Authors: Sung-Chul Hwang, Di Ren, Sang-Moon Yoon, Jong-Chun Park, Abbas Khayyer, Hitoshi Gotoh

Abstract:

The slamming impact problem has a very important engineering background. For seaplane landing, recycling for the satellite re-entry capsule, and the impact load of the bow in the adverse sea conditions, the slamming problem always plays the important role. Due to its strong nonlinear effect, however, it seems to be not easy to obtain the accurate simulation results. Combined with the strong interaction between the fluid field and the elastic structure, the difficulty for the simulation leads to a new level for challenging. This paper presents a fully Lagrangian coupled solver for simulations of fluid-structure interactions, which is based on the Moving Particle Semi-implicit (MPS) method to solve the governing equations corresponding to incompressible flows as well as elastic structures. The developed solver is verified by reproducing the high velocity impact loads of deformable thin wedges with two different materials such as aluminum and steel on water entry. The present simulation results are compared with analytical solution derived using the hydrodynamic Wagner model and linear theory by Wan.

Keywords: fluid-structure interaction, moving particle semi-implicit (MPS) method, elastic structure, incompressible flow, wedge slamming impact

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5672 Spawning Induction and Early Larval Development of the Penshell Atrina maura (Sowerby, 1835) under Controlled Conditions in Ecuador

Authors: Jose Melena, Rosa Santander, Tanya Gonzalez, Richard Duque, Juan Illanes

Abstract:

Ecuador is one of the countries with the greatest aquatic biodiversity worldwide. In particular, there are at least a dozen native marine species with great aquaculture potential locally. This research concerns one of those species. It has proposed to implement experimental protocols in order to induce spawning and to generate the early larval development of the penshell Atrina maura under controlled conditions. Bioassays were carried out with one adult batch (n= 26) with an average valvar length of 307,6 ± 9,4 mm, which were collected in the Puerto El Morro Mangrove (2° 42' 33'' S, 80° 14' 28'' W), Guayas Province. During a short acclimation stage, five adults of penshell A. maura were sacrificed in order to determine their sexual maturity degree and to estimate their sex ratio. Dissection showed that three were ripe females (60%) and two were ripe males (40%). Later, three groups (n= 7 by each) were tested with two treatments in order to induce the broodstock spawning: thermal stress, osmotic shock, and one control. Spawning induction was achieved by the immersion in water to 0 g L⁻¹ per 1 h and immersion in sea water to 34 g L⁻¹ per 1 h. After the delivery of gametes, it was achieved 1,35 × 10⁶ viable zygotes. As results, fertilized eggs had 60 µm diameter; while first and second cell divisions were observed to 1 h post-fertilization, with individual average length of 65 ± 4 µm and polar body. Latter cell divisions, including gastrula stage, appeared at 9 h post-fertilization, with individual average length of 71 ± 4 µm; and trochophore stage at 16 h post-fertilization with individual average length of 75 ± 5 µm. In addition, veliger stage was registered at 20 h post-fertilization with individual average length of 81 ± 5 µm. Umboned larvae appeared at day 8 post-fertilization, with individual average length of 145 ± 6 µm. These pioneering results in Ecuador can strengthen the local conservation process of the overexploited A. maura and to encourage its production for commercial purposes.

Keywords: Atrina maura, Ecuador, larval development, spawning induction

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5671 The Effect of Vitamin D Supplementation on Prostate Cancer: A Systematic Review and Meta-Analysis of Clinical Trials

Authors: Simin Shahvazi, Sepideh Soltani, Seyed Mehdi Ahmadi, Russell J. De Souza, Amin Salehi-Abargouei

Abstract:

Background and Objectives: Vitamin D has received attention for its potential to disrupt cancer processes such as attenuating cell proliferation and exacerbating differentiation and apoptosis. However, whether there exists a role for vitamin D in the treatment of prostate cancer specifically remains controversial. We systematically review the literature to assess whether supplementation with vitamin D influences PSA response and overall survival in patients with prostate cancer. Methods: We searched PubMed, Scopus, ISI Web of Science and Google scholar from inception through up to 10 September 2017 for both before-and-after and randomized trials that evaluated the effect of vitamin D supplementation on the prostate specific antigen (PSA) response rate in participants with prostate cancer. The DerSimonian and Laird, inverse-weighted random-effects model was used to pool effect estimates from the studies. Heterogeneity and potential publication bias were evaluated. Subgroup analyses were also performed. Results: Twenty-two studies (16 before-after and 6 randomized controlled trials) were found and included in meta-analysis. The analysis on controlled clinical trials revealed that PSA change from baseline [weighted mean difference (WMD) = -1.66 ng/ml, 95%CI: -0.69, 0.36, P= 0.543)], PSA response (RR=1.18, 95%CI: 0.97, 1.45, P=0.104) and mortality rate (risk ratio (RR) = 1.05, 95% CI: 0.81-1.36; P=0.713) was not significantly different between vitamin D supplementation and placebo groups. Single arm trials revealed that vitamin D supplementation had had a modest effect on PSA response rate: 19% of those enrolled had at least a 50% reduction in PSA by the end of treatment (95% CI: 7% to 31%; p=0.002). Conclusion: We found that vitamin D modestly increases the PSA response rate in single arm studies. No effect on serum PSA levels, PSA response and mortality was seen in randomized controlled clinical trials. It does not seem patients with prostate cancer benefit from vitamin D supplementation.

Keywords: mortality, prostatic neoplasms, PSA response, vitamin D

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5670 Deposition of Cr-doped ZnO Thin Films and Their Ferromagnetic Properties

Authors: Namhyun An, Byungho Lee, Hwauk Lee, Youngmin Lee, Deuk Young Kim, Sejoon Lee

Abstract:

In this study, the Cr-doped ZnO thin films have been deposited by reactive magnetron sputtering method with different Cr-contents (1.0at.%, 2.5at.% and 12.5at.%) and their ferromagnetic properties have been characterized. All films revealed clear ferromagnetism above room temperature. However, the spontaneous magnetization of the films was observed to depend on the Cr contents in the films. Namely, the magnitude of effective magnetic moment (per each Cr ion) was exponentially decreased with increasing the Cr contents. We attributed the decreased spontaneous magnetization to the degraded crystal magnetic anisotropy. In other words, we found out that the high concentration of magnetic ions causes the lattice distortion in the magnetic ion-doped thin film, and it consequently degrades ferromagnetic channeling in the solid-state material system.

Keywords: Cr-doped ZnO, ferromagnetic properties, magnetization, sputtering, thin film

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5669 Anthropogenic Impact on Migration Process of River Yamuna in Delhi-NCR Using Geospatial Techniques

Authors: Mohd Asim, K. Nageswara Rao

Abstract:

The present work was carried out on River Yamuna passing through Delhi- National Capital Region (Delhi-NCR) of India for a stretch of about 130 km to assess the anthropogenic impact on the channel migration process for a period of 200 years with the help of satellite data and topographical maps with integration of geographic information system environment. Digital Shoreline Analysis System (DSAS) application was used to quantify river channel migration in ArcGIS environment. The average river channel migration was calculated to be 22.8 m/year for the entire study area. River channel migration was found to be moving in westward and eastward direction. Westward migration is more than 4 km maximum in length and eastward migration is about 4.19 km. The river has migrated a total of 32.26 sq. km of area. The results reveal that the river is being impacted by various human activities. The impact indicators include engineering structures, sand mining, embankments, urbanization, land use/land cover, canal network. The DSAS application was also used to predict the position of river channel in future for 2032 and 2042 by analyzing the past and present rate and direction of movement. The length of channel in 2032 and 2042 will be 132.5 and 141.6 km respectively. The channel will migrate maximum after crossing Okhla Barrage near Faridabad for about 3.84 sq. km from 2022 to 2042 from west to east.

Keywords: river migration, remote sensing, river Yamuna, anthropogenic impacts, DSAS, Delhi-NCR

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5668 Magnetic Resonance Imaging for Assessment of the Quadriceps Tendon Cross-Sectional Area as an Adjunctive Diagnostic Parameter in Patients with Patellofemoral Pain Syndrome

Authors: Jae Ni Jang, SoYoon Park, Sukhee Park, Yumin Song, Jae Won Kim, Keum Nae Kang, Young Uk Kim

Abstract:

Objectives: Patellofemoral pain syndrome (PFPS) is a common clinical condition characterized by anterior knee pain. Here, we investigated the quadriceps tendon cross-sectional area (QTCSA) as a novel predictor for the diagnosis of PFPS. By examining the association between the QTCSA and PFPS, we aimed to provide a more valuable diagnostic parameter and more equivocal assessment of the diagnostic potential of PFPS by comparing the QTCSA with the quadriceps tendon thickness (QTT), a traditional measure of quadriceps tendon hypertrophy. Patients and Methods: This retrospective study included 30 patients with PFPS and 30 healthy participants who underwent knee magnetic resonance imaging. T1-weighted turbo spin echo transverse magnetic resonance images were obtained. The QTCSA was measured on the axial-angled phases of the images by drawing outlines, and the QTT was measured at the most hypertrophied quadriceps tendon. Results: The average QTT and QTCSA for patients with PFPS (6.33±0.80 mm and 155.77±36.60 mm², respectively) were significantly greater than those for healthy participants (5.77±0.36 mm and 111.90±24.10 mm2, respectively; both P<0.001). We used a receiver operating characteristic curve to confirm the sensitivities and specificities for both the QTT and QTCSA as predictors of PFPS. The optimal diagnostic cutoff value for QTT was 5.98 mm, with a sensitivity of 66.7%, a specificity of 70.0%, and an area under the curve of 0.75 (0.62–0.88). The optimal diagnostic cutoff value for QTCSA was 121.04 mm², with a sensitivity of 73.3%, a specificity of 70.0%, and an area under the curve of 0.83 (0.74–0.93). Conclusion: The QTCSA was found to be a more reliable diagnostic indicator for PFPS than QTT.

Keywords: patellofemoral pain syndrome, quadriceps muscle, hypertrophy, magnetic resonance imaging

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5667 Using Data Mining Techniques to Evaluate the Different Factors Affecting the Academic Performance of Students at the Faculty of Information Technology in Hashemite University in Jordan

Authors: Feras Hanandeh, Majdi Shannag

Abstract:

This research studies the different factors that could affect the Faculty of Information Technology in Hashemite University students’ accumulative average. The research paper verifies the student information, background, their academic records, and how this information will affect the student to get high grades. The student information used in the study is extracted from the student’s academic records. The data mining tools and techniques are used to decide which attribute(s) will affect the student’s accumulative average. The results show that the most important factor which affects the students’ accumulative average is the student Acceptance Type. And we built a decision tree model and rules to determine how the student can get high grades in their courses. The overall accuracy of the model is 44% which is accepted rate.

Keywords: data mining, classification, extracting rules, decision tree

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5666 Perfomance of PAPR Reduction in OFDM System for Wireless Communications

Authors: Alcardo Alex Barakabitze, Saddam Aziz, Muhammad Zubair

Abstract:

The Orthogonal Frequency Division Multiplexing (OFDM) is a special form of multicarrier transmission that splits the total transmission bandwidth into a number of orthogonal and non-overlapping subcarriers and transmit the collection of bits called symbols in parallel using these subcarriers. In this paper, we explore the Peak to Average Power Reduction (PAPR) problem in OFDM systems. We provide the performance analysis of CCDF and BER through MATLAB simulations.

Keywords: bit error ratio (BER), OFDM, peak to average power reduction (PAPR), sub-carriers

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5665 Big Data Analysis with RHadoop

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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5664 Complex Network Approach to International Trade of Fossil Fuel

Authors: Semanur Soyyigit Kaya, Ercan Eren

Abstract:

Energy has a prominent role for development of nations. Countries which have energy resources also have strategic power in the international trade of energy since it is essential for all stages of production in the economy. Thus, it is important for countries to analyze the weakness and strength of the system. On the other side, it is commonly believed that international trade has complex network properties. Complex network is a tool for the analysis of complex systems with heterogeneous agents and interaction between them. A complex network consists of nodes and the interactions between these nodes. Total properties which emerge as a result of these interactions are distinct from the sum of small parts (more or less) in complex systems. Thus, standard approaches to international trade are superficial to analyze these systems. Network analysis provides a new approach to analyze international trade as a network. In this network countries constitute nodes and trade relations (export or import) constitute edges. It becomes possible to analyze international trade network in terms of high degree indicators which are specific to complex systems such as connectivity, clustering, assortativity/disassortativity, centrality, etc. In this analysis, international trade of crude oil and coal which are types of fossil fuel has been analyzed from 2005 to 2014 via network analysis. First, it has been analyzed in terms of some topological parameters such as density, transitivity, clustering etc. Afterwards, fitness to Pareto distribution has been analyzed. Finally, weighted HITS algorithm has been applied to the data as a centrality measure to determine the real prominence of countries in these trade networks. Weighted HITS algorithm is a strong tool to analyze the network by ranking countries with regards to prominence of their trade partners. We have calculated both an export centrality and an import centrality by applying w-HITS algorithm to data.

Keywords: complex network approach, fossil fuel, international trade, network theory

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5663 Accurate Position Electromagnetic Sensor Using Data Acquisition System

Authors: Z. Ezzouine, A. Nakheli

Abstract:

This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: electromagnetic sensor, accurately, data acquisition, position measurement

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5662 The Sensitivity of Electrical Geophysical Methods for Mapping Salt Stores within the Soil Profile

Authors: Fathi Ali Swaid

Abstract:

Soil salinization is one of the most hazardous phenomenons accelerating the land degradation processes. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leading land degradation ultimately. Thus, it is important to monitor and map soil salinity at an early stage to enact effective soil reclamation program that helps lessen or prevent future increase in soil salinity. Geophysical method has outperformed the traditional method for assessing soil salinity offering more informative and professional rapid assessment techniques for monitoring and mapping soil salinity. Soil sampling, EM38 and 2D conductivity imaging have been evaluated for their ability to delineate and map the level of salinity variations at Second Ponds Creek. The three methods have shown that the subsoil in the study area is saline. Salt variations were successfully observed under either method. However, EM38 reading and 2D inversion data show a clear spatial structure comparing to EC1:5 of soil samples in spite of that all soil samples, EM38 and 2D imaging were collected from the same location. Because EM38 readings and 2D imaging data are a weighted average of electrical soil conductance, it is more representative of soil properties than the soil samples method. The mapping of subsurface soil at the study area has been successful and the resistivity imaging has proven to be an advantage. The soil salinity analysis (EC1:5) correspond well to the true resistivity bringing together a good result of soil salinity. Soil salinity clearly indicated by previous investigation EM38 have been confirmed by the interpretation of the true resistivity at study area.

Keywords: 2D conductivity imaging, EM38 readings, soil salinization, true resistivity, urban salinity

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5661 Use of Machine Learning Algorithms to Pediatric MR Images for Tumor Classification

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

Abstract:

Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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5660 Aerodynamic Study of an Open Window Moving Bus with Passengers

Authors: Pawan Kumar Pant, Bhanu Gupta, S. R. Kale, S. V. Veeravalli

Abstract:

In many countries, buses are the principal means of transport, of which a majority are naturally ventilated with open windows. The design of this ventilation has little scientific basis and to address this problem a study has been undertaken involving both experiments and numerical simulations. The flow pattern inside and around of an open window bus with passengers has been investigated in detail. A full scale three-dimensional numerical simulation has been used for a) a bus with closed windows and b) with open windows. In either simulation, the bus had 58 seated passengers. The bus dimensions used were 2500 mm wide × 2500 mm high (exterior) × 10500 mm long and its speed was set at 40 km/h. In both cases, the flow separates at the top front edge forming a vortex and reattaches close to the mid-length. This attached flow separates once more as it leaves the bus. However, the strength and shape of the vortices at the top front and wake region is different for both cases. The streamline pattern around the bus is also different for the two cases. For the bus with open windows, the dominant airflow inside the bus is from the rear to the front of the bus and air velocity at the face level of the passengers was found to be 1/10th of the free stream velocity. These findings are in good agreement with flow visualization experiments performed in a water channel at 10 m/s, and with smoke/tuft visualizations in a wind tunnel with a free-stream velocity of approximately 40 km/h on a 1:25 scaled Perspex model.

Keywords: air flow, moving bus, open windows, vortex, wind tunnel

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5659 Epidemiological profile of Tuberculosis Disease in Meknes, Morocco. Descriptive analysis, 2016-2020

Authors: Authors: A. Lakhal, M. Bahalou, A. Khattabi

Abstract:

Introduction: Tuberculosis is one of the world's deadliest infectious diseases. In Morocco, a total of 30,636 cases of Tuberculosis, all forms combined, were reported in 2015, representing an incidence of 89 cases per 100,000 population. The number of deaths from tuberculosis (TB) was 656 cases. In the prefecture of Meknes, its incidence remains high compared to the national level. The objective of this work is to describe the epidemiological profile of tuberculosis in the prefecture of Meknes. Methods: It is a descriptive analysis of TB cases reported between 2016 and 2020 at the regional diagnostic center of tuberculosis and respiratory diseases. We performed analysis by using Microsoft Excel and EpiInfo 7. Results: Epidemiological data from 2016 to 2020 report a total of 4100 new cases of all forms of tuberculosis, with an average of 820 new cases per year. The median age is 32 years. There is a clear male predominance, on average 58% of cases are male and 42% female. The incidence rate of bacteriologically confirmed tuberculosis per 100,000 inhabitants has increased from 35 cases per 100,000 inhabitants in 2016 to 39.4 cases per 100,000 inhabitants in 2020. The confirmation rate for pulmonary tuberculosis decreased from 84% in 2016 to 75% in 2020. Pulmonary involvement predominates by an average of 46%, followed by lymph node involvement 29%and pleural involvement by an average of 10%. Digestive, osteoarticular, genitourinary, and meningeal involvement occurs in 8% of cases. Primary tuberculosis infection occurs in an average of 0.5% of cases. The proportion of HIV-TB co-infections was 2.8 in 2020. Conclusion: The incidence of tuberculosis in Meknes remains high compared to the national level. Thus, it is imperative to reinforce the earlier detection; improve the contact tracing, detection methods of cases for their confirmation and treatment, and to reduce the proportion of the lost to follow up as well.

Keywords: tuberculosis, epidemiological profile, meknes, morocco

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5658 A Radiomics Approach to Predict the Evolution of Prostate Imaging Reporting and Data System Score 3/5 Prostate Areas in Multiparametric Magnetic Resonance

Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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5657 Voluntary Water Intake of Flavored Water in Euhydrated Horses

Authors: Brianna M. Soule, Jesslyn A. Bryk-Lucy, Linda M. Ritchie

Abstract:

Colic, defined as abdominal pain in the horse, has several known predisposing factors. Decreased water intake has been shown to predispose equines to impaction colic. The objective of this study was to determine if offering flavored water (sweet feed or banana extract) would increase voluntary water intake in horses to serve as an assessable, noninvasive method for farm managers, veterinarians, or owners to decrease the risk of impaction colic. An a priori power analysis, which was conducted using G*Power version 3.1.9.7, indicated that the minimum sample size required to achieve 80% power for detecting a large effect at a significance level of α = .05 was 19 horses for a one-way repeated measures ANOVA with three treatment levels and assuming a non-sphericity correction of ε=0.5. After a three-day control period, 21 horses were randomly divided into two sequences and offered either banana or sweet feed flavored water. Horses always had a bucket of unflavored water available. A repeated measure study design was used to measure water consumption of each horse over a 62-hour period. A one-way repeated measures ANOVA was conducted to determine whether there were statistically significant differences among the means for the three-day average water intake (ml/kg). Although not statistically significant (F(2, 38) = 1.28, p = .290, partial η2 = .063), the three-day average water intake was largest for banana flavored water (M = 53.51, SD = 9.25 ml/kg), followed by sweet feed (M = 52.93, SD = 11.99 ml/kg), and, finally, unflavored water (M = 50.40, SD = 10.82 ml/kg). Paired-samples t-tests were used to determine whether there was a statistically significant difference between the three-day average water intake (ml/kg) for flavored versus unflavored water. The average unflavored water intake (M = 29.3 ml/kg, SD = 8.9) over the measurement period was greater than the banana flavored water (M = 27.7 ml/kg, SD = 9.8), but the average consumption of the sweet feed flavored water (M = 30.4 ml/kg, SD = 14.6) was greater than unflavored water (M = 24.3 ml/kg, SD = 11.4). None of these differences in average intake were statistically significant (p > .244). Future research is warranted to determine if other flavors significantly increase voluntary water intake in horses.

Keywords: colic, equine, equine science, water intake, flavored water, horses, equine management, equine health, horse health, horse health care management, colic prevention

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5656 Electromechanical-Traffic Model of Compression-Based Piezoelectric Energy Harvesting System

Authors: Saleh Gareh, B. C. Kok, H. H. Goh

Abstract:

Piezoelectric energy harvesting has advantages over other alternative sources due to its large power density, ease of applications, and capability to be fabricated at different scales: macro, micro, and nano. This paper presents an electromechanical-traffic model for roadway compression-based piezoelectric energy harvesting system. A two-degree-of-freedom (2-DOF) electromechanical model has been developed for the piezoelectric energy harvesting unit to define its performance in power generation under a number of external excitations on road surface. Lead Zirconate Titanate (PZT-5H) is selected as the piezoelectric material to be used in this paper due to its high Piezoelectric Charge Constant (d) and Piezoelectric Voltage Constant (g) values. The main source of vibration energy that has been considered in this paper is the moving vehicle on the road. The effect of various frequencies on possible generated power caused by different vibration characteristics of moving vehicle has been studied. A single unit of circle-shape Piezoelectric Cymbal Transducer (PCT) with diameter of 32 mm and thickness of 0.3 mm be able to generate about 0.8 mW and 3 mW of electric power under 4 Hz and 20 Hz of excitation, respectively. The estimated power to be generated for multiple arrays of PCT is approximately 150 kW/ km. Thus, the developed electromechanical-traffic model has enormous potential to be used in estimating the macro scale of roadway power generation system.

Keywords: piezoelectric energy harvesting, cymbal transducer, PZT (lead zirconate titanate), 2-DOF

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5655 Mean Field Model Interaction for Computer and Communication Systems: Modeling and Analysis of Wireless Sensor Networks

Authors: Irina A. Gudkova, Yousra Demigha

Abstract:

Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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5654 New to Vancouver: The Effects of Residential Relocation on Cardiovascular Disease Risk

Authors: Rachel Karasenty Saltoun, Charlotte Roddick, Chelsea D. Christie, Frances Chen

Abstract:

Moving has become an integral part of many people’s lives. This research explores whether relocating to a new city is associated with an increase in loneliness and cardiovascular disease risk and if this increased risk diminishes with continued residency. To test this, various psychosocial variables and three cardiovascular disease risk markers (C-reactive protein, albumin, blood pressure) were assessed on two groups of individuals: those who have moved to Vancouver, Canada in the previous 6 weeks (‘Movers’) and those who have lived in Vancouver for at least five years (‘Non-Movers’). It was hypothesized that individuals who had recently relocated would have heightened levels of loneliness, blood pressure (BP), albumin, and C-reactive protein (CRP) compared to those who had not recently relocated. Length of residency was hypothesized to moderate these effects, such that after a few months, loneliness levels and cardiovascular disease risk would decrease among those who had recently relocated. Correlational analysis indicated a trend between the change in CRP and albumin levels and loneliness overtime on an individual level. However, these results must be interpreted with caution due to the small sample size. As Vancouver’s immigration rates continue to grow, this study has important implications regarding the social support resources offered to new immigrants, as well as bringing awareness at the healthcare level of the potential increase in cardiovascular disease risk among those who have recently relocated.

Keywords: cardiovascular disease risk, loneliness, moving, residential mobility

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5653 Model Averaging for Poisson Regression

Authors: Zhou Jianhong

Abstract:

Model averaging is a desirable approach to deal with model uncertainty, which, however, has rarely been explored for Poisson regression. In this paper, we propose a model averaging procedure based on an unbiased estimator of the expected Kullback-Leibler distance for the Poisson regression. Simulation study shows that the proposed model average estimator outperforms some other commonly used model selection and model average estimators in some situations. Our proposed methods are further applied to a real data example and the advantage of this method is demonstrated again.

Keywords: model averaging, poission regression, Kullback-Leibler distance, statistics

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5652 Coupled Analysis with Fluid and Flexible Multibody Dynamics of 6-DOF Platform with Liquid Sloshing Tank

Authors: Sung-Pill Kim, Dae-Gyu Sung, Hee-Sung Shin, Jong-Chun Park

Abstract:

When a sloshing tank filled partially with liquid is excited with the motion of platform, it can be observed that the center of mass inside the tank is changed and impact loads is instantaneously applied to the wall, which causes dynamic loads additionally to the supporting links of platform. In this case, therefore, the dynamic behavior of platform associated with fluid motion should be considered in the early stage of design for safety and economics of the system. In this paper, the dynamic loads due to liquid sloshing motion in a rectangular tank which is loaded up on the upper deck of a Stewart platform are simulated using a coupled analysis of Moving Particle Simulation (MPS) and Flexible Multi-Body Dynamics (FMBD). The co-simulation is performed using two commercial softwares, Recurdyn for solving FMBD and Particleworks for analyzing fluid motion based on MPS method. For validating the present coupled system, a rectangular sloshing tank being enforced with inline sway motion by 1-DOF motion platform is assumed, and time-varied free-surface elevation and reaction force at a fixed joint are compared with experiments.

Keywords: dynamic loads, liquid sloshing tank, Stewart platform, moving particle semi-implicit (MPS) method, flexible multi-body dynamics (FMBD)

Procedia PDF Downloads 675
5651 Quality of Life and Renal Biomarkers in Feline Chronic Kidney Disease

Authors: Bárbara Durão, Pedro Almeida, David Ramilo, André Meneses, Rute Canejo-Teixeira

Abstract:

The importance of quality of life (QoL) assessment in veterinary medicine is an integral part of patient care. This is especially true in cases of chronic diseases, such as chronic kidney disease (CKD), where the ever more advanced treatment options prolong the patient’s life. Whether this prolongment of life comes with an acceptable quality of life remains has been called into question. The aim of this study was to evaluate the relationship between CKD disease biomarkers and QoL in cats. Thirty-seven cats diagnosed with CKD and with no known concurrent illness were enrolled in an observational study. Through the course of several evaluations, renal biomarkers were assessed in blood and urine samples, and owners retrospectively described their cat’s quality of life using a validated instrument for this disease. Correlations between QoL scores (AWIS) and the biomarkers were assessed using Spearman’s rank test. Statistical significance was set at p-value < 0.05, and every serial sample was considered independent. Thirty-seven cats met the inclusion criteria, and all owners completed the questionnaire every time their pet was evaluated, giving a total of eighty-four questionnaires, and the average-weighted-impact-score was –0.5. Results showed there was a statistically significant correlation between the quality of life and most of 17 the studied biomarkers and confirmed that CKD has a negative impact on QoL in cats especially due to the management of the disease and secondary appetite disorders. To our knowledge, this is the attempt to assess the correlation between renal biomarkers and QoL in cats. Our results reveal a strong potential of this type of approach in clinical management, mainly in situations where it is not possible to measure biomarkers. Whilst health-related QoL is a reliable predictor of mortality and morbidity in humans; our findings can help improve the clinical practice in cats with CKD.

Keywords: chronic kidney disease, biomarkers, quality of life, feline

Procedia PDF Downloads 155
5650 PLO-AIM: Potential-Based Lane Organization in Autonomous Intersection Management

Authors: Berk Ecer, Ebru Akcapinar Sezer

Abstract:

Traditional management models of intersections, such as no-light intersections or signalized intersection, are not the most effective way of passing the intersections if the vehicles are intelligent. To this end, Dresner and Stone proposed a new intersection control model called Autonomous Intersection Management (AIM). In the AIM simulation, they were examining the problem from a multi-agent perspective, demonstrating that intelligent intersection control can be made more efficient than existing control mechanisms. In this study, autonomous intersection management has been investigated. We extended their works and added a potential-based lane organization layer. In order to distribute vehicles evenly to each lane, this layer triggers vehicles to analyze near lanes, and they change their lane if other lanes have an advantage. We can observe this behavior in real life, such as drivers, change their lane by considering their intuitions. Basic intuition on selecting the correct lane for traffic is selecting a less crowded lane in order to reduce delay. We model that behavior without any change in the AIM workflow. Experiment results show us that intersection performance is directly connected with the vehicle distribution in lanes of roads of intersections. We see the advantage of handling lane management with a potential approach in performance metrics such as average delay of intersection and average travel time. Therefore, lane management and intersection management are problems that need to be handled together. This study shows us that the lane through which vehicles enter the intersection is an effective parameter for intersection management. Our study draws attention to this parameter and suggested a solution for it. We observed that the regulation of AIM inputs, which are vehicles in lanes, was as effective as contributing to aim intersection management. PLO-AIM model outperforms AIM in evaluation metrics such as average delay of intersection and average travel time for reasonable traffic rates, which is in between 600 vehicle/hour per lane to 1300 vehicle/hour per lane. The proposed model reduced the average travel time reduced in between %0.2 - %17.3 and reduced the average delay of intersection in between %1.6 - %17.1 for 4-lane and 6-lane scenarios.

Keywords: AIM project, autonomous intersection management, lane organization, potential-based approach

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5649 Determination of Natural Gamma Radioactivity in Sand along the Black Sea Coastal Region of Giresun, North Turkey

Authors: A. Karadeniz, Belgin Kucukomeroglu

Abstract:

In this study natural gamma radioactivity levels are determined on sands along the coastal regions of Giresun/Turkey. The coast of Giresun about 290 km long in investigated to collect 101 sand samples. Natural and artificial radioactivity concentrations of sand samples were measured by using HPGe gamma spectrometry. The average activity concentrations of 238U, 232Th, 40K and 137Cs on sand samples of Giresun were found to be 10.83±2.92 Bq/kg, 21.28±3.22 Bq/kg, 6.42±1.06 Bq/kg, 230.94±10.67 Bq/kg respectively. The average activity concentrations for these radionuclides were compared with the reported data of other parts of Turkey and other countries. The average absorbed dose rate for Giresun was calculated to be 38.68 nGy/h respectively. This value is significantly lower than the World averaged value of 60 nGy/h. The external annual effective dose rate concentration in Giresun was found to be 0.047 mSv/y respectively. This result is much lower than the recommeded limit of 5 mSv/y. The external hazard dose rate for Giresun weas calculated to be 0.21 respectively. This result is much lower than the recommended limit of 1.0.

Keywords: concentration, radioactivity, Giresun, natural gamma radioactivity

Procedia PDF Downloads 374
5648 Model Averaging in a Multiplicative Heteroscedastic Model

Authors: Alan Wan

Abstract:

In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

Procedia PDF Downloads 344