Search results for: Random Kernel Density

Authors: A. Baqqal, O. Abduhamid, H. Abdul-Hameed, T. Messager, G. Ayoub

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In this contribution, the effect of crystal content on the cyclic response of semi-crystalline polyethylene is studied over a large strain range. Experimental observations on a high-density polyethylene with 72% crystal content and an ultralow density polyethylene with 15% crystal content are reported. The cyclic stretching does appear a thermoplastic-like response for high crystallinity and an elastomeric-like response for low crystallinity, both characterized by a stress-softening, a hysteresis and a residual strain, whose amount depends on the crystallinity and the applied strain. Based on the experimental observations, a unified viscoelastic-viscoplastic constitutive model capturing the polyethylene cyclic response features is proposed. A two-phase representation of the polyethylene microstructure allows taking into consideration the effective contribution of the crystalline and amorphous phases to the intermolecular resistance to deformation which is coupled, to capture the strain hardening, to a resistance to molecular orientation. The polyethylene cyclic response features are captured by introducing evolution laws for the model parameters affected by the microstructure alteration due to the cyclic stretching.

Keywords: cyclic loading unloading, polyethylene, semi-crystalline polymer, viscoelastic-viscoplastic constitutive model

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Authors: J. O. Bodunrin, S. J. Moloi

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This study reports on the x-ray crystallography (XRD) structure of cadmium-implanted p-type silicon, the current-voltage (I-V) and capacitance-voltage (C-V) characteristics of unimplanted and cadmium-implanted silicon-based diodes. Cadmium was implanted at the energy of 160 KeV to the fluence of 10¹⁵ ion/cm². The results obtained indicate that the diodes were well fabricated, and the introduction of cadmium results in a change in behavior of the diodes from normal exponential to ohmic I-V behavior. The C-V measurements, on the other hand, show that the measured capacitance increased after cadmium doping due to the injected charge carriers. The doping density of the p-Si material and the device's Schottky barrier height was extracted, and the doping density of the undoped p-Si material increased after cadmium doping while the Schottky barrier height reduced. In general, the results obtained here are similar to those obtained on the diodes fabricated on radiation-hard material, indicating that cadmium is a promising metal dopant to improve the radiation hardness of silicon. Thus, this study would assist in adding possible options to improve the radiation hardness of silicon to be used in high energy physics experiments.

Keywords: cadmium, capacitance-voltage, current-voltage, high energy physics experiment, x-ray crystallography, XRD

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: Nkwachukwu Chukwuchekwa, Joy Ulumma Chukwuchekwa

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Magnetic characteristics of grain-oriented electrical steel (GOES) are usually measured at high flux densities suitable for its typical applications in power transformers. There are limited magnetic data at low flux densities which are relevant for the characterization of GOES for applications in metering instrument transformers and low frequency magnetic shielding in magnetic resonance imaging medical scanners. Magnetic properties such as coercivity, B-H loop, AC relative permeability and specific power loss of conventional grain oriented (CGO) and high permeability grain oriented (HGO) electrical steels were measured and compared at high and low flux densities at power magnetising frequency. 40 strips comprising 20 CGO and 20 HGO, 305 mm x 30 mm x 0.27 mm from a supplier were tested. The HGO and CGO strips had average grain sizes of 9 mm and 4 mm respectively. Each strip was singly magnetised under sinusoidal peak flux density from 8.0 mT to 1.5 T at a magnetising frequency of 50 Hz. The novel single sheet tester comprises a personal computer in which LabVIEW version 8.5 from National Instruments (NI) was installed, a NI 4461 data acquisition (DAQ) card, an impedance matching transformer, to match the 600  minimum load impedance of the DAQ card with the 5 to 20  low impedance of the magnetising circuit, and a 4.7 Ω shunt resistor. A double vertical yoke made of GOES which is 290 mm long and 32 mm wide is used. A 500-turn secondary winding, about 80 mm in length, was wound around a plastic former, 270 mm x 40 mm, housing the sample, while a 100-turn primary winding, covering the entire length of the plastic former was wound over the secondary winding. A standard Epstein strip to be tested is placed between the yokes. The magnetising voltage was generated by the LabVIEW program through a voltage output from the DAQ card. The voltage drop across the shunt resistor and the secondary voltage were acquired by the card for calculation of magnetic field strength and flux density respectively. A feedback control system implemented in LabVIEW was used to control the flux density and to make the induced secondary voltage waveforms sinusoidal to have repeatable and comparable measurements. The low noise NI4461 card with 24 bit resolution and a sampling rate of 204.8 KHz and 92 KHz bandwidth were chosen to take the measurements to minimize the influence of thermal noise. In order to reduce environmental noise, the yokes, sample and search coil carrier were placed in a noise shielding chamber. HGO was found to have better magnetic properties at both high and low magnetisation regimes. This is because of the higher grain size of HGO and higher grain-grain misorientation of CGO. HGO is better CGO in both low and high magnetic field applications.

Keywords: flux density, electrical steel, LabVIEW, magnetization

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Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Yingjeng James Li, Chiao-Chih Hu

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Membrane electrode assemblies (MEAs) for proton exchange membrane fuel cell (PEMFC) applications were prepared by using 10 and 15 um PEMs. Except for different membrane thicknesses, these MEAs were prepared by the same conditions. They were prepared by using catalyst coated membrane (CCM) process. The catalyst employed is 40% Pt/C, and the Pt loading is 0.5mg/cm² for the sum of anode and cathode. Active area of the MEAs employed in this study is 5cm*5cm=25cm². In polarization measurements, the flow rates were always set at 1.2 stoic for anode and 3.0 stoic for cathode. The outlets were in open-end mode. The flow filed is tri-serpentine design. The cell temperatures and the humidification conditions were varied for the purpose of MEA performance observations. It was found that the performance of these two types of MEAs is about the same at fully or partially humidified operation conditions; however, 10um MEA exhibits higher current density in dry or low humidified conditions. For example, at 70C cell, 100% RH, and 0.6V condition, both MEAs have similar current density which is 1320 and 1342mA/cm² for 15um and 10um product, respectively. However, when in operation without external humidification, 10um MEA can produce 1085mA/cm²; whereas 15um MEA produces only 720mA/cm².

Keywords: fuel cell, membrane electrode assembly, PEFC, PEMFC, proton exchange membrane

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Authors: Sudhir Kumar Singh, Debashish Chakravarty

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Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Ashish Soni, Suman Kalyan Pal

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Transition metal dichalcogenides (TMDCs) are an emerging paradigm for the generation of advanced materials which are capable of utilizing in future device applications. In recent years TMDCs have attracted researchers for their unique band structure in monolayers. Large-area monolayers could become the most appropriate candidate for flexible and thin optoelectronic devices. For this purpose, it is crucial to understand the generation and transport of charge carriers in low dimensions. A deep understanding of photo-generated hot charges and trapped charges is essential to improve the performance of optoelectronic devices. Carrier trapping by the defect states that are introduced during the growth process of the monolayer could influence the dynamical behaviour of charge carriers. Herein, we investigated some aspects of the ultrafast evolution of the initially generated hot carriers and trapped charges in large-area monolayer WS₂ by measuring transient absorption at energies above and below the band gap energy. Our excitation density and energy-dependent measurements reveal the trapping of the initially generated charge carrier. Our results could be beneficial for the development of TMDC-based optoelectronic devices.

Keywords: transient absorption, optoelectronics, 2D materials, TMDCs, exciton

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Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: moving object detection, histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine

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Authors: Gaurav Datta, Sourav Ghosh, Rahul Roy

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The incorporation of silica fume into the normal concrete is a routine one in the present days to produce the tailor made high strength and high performance concrete. The design parameters are increasing with the incorporation of silica fume in conventional concrete and the mix proportioning is becoming complex. The main objective of this paper has been made to investigate the different mechanical properties like compressive strength, permeability, porosity, density, modulus of elasticity, compacting factor, slump of concrete incorporating silica fume. In this present paper 5 (five) mix of concrete incorporating silica fume is cast to perform experiments. These experiments were carried out by replacing cement with different percentages of silica fume at a single constant water-cementitious materials ratio keeping other mix design variables constant. The silica fume was replaced by 0%, 5%, 10%, 15% and 20% for water-cementitious materials (w/cm) ratio for 0.40. For all mixes compressive strengths were determined at 24 hours, 7 and 28 days for 100 mm and 150 mm cubes. Other properties like permeability, porosity, density, modulus of elasticity, compacting factor, and slump were also determined for five mixes of concrete.

Keywords: high performance concrete, high strength concrete, silica fume, strength

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Authors: M. Dahbi, M. Sellam, A. Benatiallah, A. Harrouz

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The wind energy is one of the most significant and rapidly developing renewable energy sources in the world and it provides a clean energy resource, which is a promising alternative in the short term in Algeria The main purpose of this paper is to compared and discuss the wind power potential in three sites located in sahara of Algeria (south west of Algeria) and to perform an investigation on the wind power potential of desert of Algeria. In this comparative, wind speed frequency distributions data obtained from the web site SODA.com are used to calculate the average wind speed and the available wind power. The Weibull density function has been used to estimate the monthly power wind density and to determine the characteristics of monthly parameters of Weibull for these three sites. The annual energy produced by the BWC XL.1 1KW wind machine is obtained and compared. The analysis shows that in the south west of Algeria, at 10 m height, the available wind power was found to vary between 136.59 W/m2 and 231.04 W/m2. The highest potential wind power was found at Adrar, with 21h per day and the mean wind speed is above 6 m/s. Besides, it is found that the annual wind energy generated by that machine lie between 512 KWh and 1643.2 kWh. However, the wind resource appears to be suitable for power production on the sahara and it could provide a viable substitute to diesel oil for irrigation pumps and rural electricity generation.

Keywords: Weibull distribution, parameters of Wiebull, wind energy, wind turbine, operating hours

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Authors: Lukman Andi Priyatna, Vivi Fauzia, Ferry Anggoro Ardy Nugroho

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Zinc oxide (ZnO) based nanostructures are ubiquitous in applications due to their favourable physicochemical properties and ease of fabrication. One widely accessible route to synthesize ZnO nanorods, which show promising performance in e.g. photoelectrochemical water splitting, is hydrothermal growth of ZnO seeds, obtained via an atomic nebulizer. Despite its popularity, study on the impact of the synthesis parameters in atomic nebulizer on the performance of the synthesized ZnO nanostructures is lacking. This study presents an investigation on the impact of the distance between substrates and atomic nebulizer nozzle on the photoelectrochemical water splitting performance of ZnO nanorods. Adjusting such a distance reveals an optimum separation which results in nanostructures with highest absorbance. Such high absorbance translates into improved photoelectrochemistry, as evaluated by higher photocurrent density, from 0.11 mA/cm² to 0.14 mA/cm² and higher Applied Bias Photon-to-Current Efficiency (ABPE) from 0.12% to 0.14%. These results underscore the importance of understanding and optimizing the experimental parameters during ZnO nanostructure synthesis. In a broader context, it advertises the need to carefully assess the corresponding fabrication parameters to optimize the performance of the obtained nanostructures.

Keywords: atomic nebulizer, photocurrent density, photoelectrochemical water splitting, ZnO nanorods

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Authors: Munoz A. Tatiana, Solano R. Brandon, Montes C. Juan, Cierco G. Javier

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The hydrodynamic cavitation is a process in which the energy that the fluids have in the phase changes is used. From this energy, local temperatures greater than 5000 °C are obtained where thermal cracking of the fluid molecules takes place. The process applied to heavy oil affects variables such as viscosity, density, and composition, which constitutes an important improvement in the quality of crude oil. In this study, the need to design a software through mathematical integration models of mixing, cavitation, kinetics, and reactor, allows modeling changes in density, viscosity, and composition of a heavy oil crude, when the fluid passes through a hydrodynamic cavitation reactor. In order to evaluate the viability of this technique in the industry, a heavy oil of 18° API gravity, was simulated using naphtha as a hydrogen donor at concentrations of 1, 2 and 5% vol, where the simulation results showed an API gravity increase to 0.77, 1.21 and 1.93° respectively and a reduction viscosity by 9.9, 12.9 and 15.8%. The obtained results allow to have a favorable panorama on this technological development, an appropriate visualization on the generation of innovative knowledge of this technique and the technical-economic opportunity that benefits the development of the hydrocarbon sector related to heavy crude oil that includes the largest world oil production.

Keywords: hydrodynamic cavitation, thermal cracking, hydrogen donor, heavy oil upgrading, simulator

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Authors: Catherine Kuforiji, Michel Nganbe

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The abrasive wear of composite materials is a major challenge in highly demanding wear applications. Therefore, this study focuses on fabricating, testing and assessing the properties of 50wt% SS316L stainless steel–50wt% Al2O3 particle composites. Composite samples were fabricated using the powder metallurgy route. The effects of the powder metallurgy processing parameters and hard particle reinforcement were studied. The microstructure, density, hardness and toughness were characterized. The wear behaviour was studied using pin-on-disc testing under dry sliding conditions. The highest hardness of 1085.2 HV, the highest theoretical density of 94.7% and the lowest wear rate of 0.00397 mm3/m were obtained at a milling speed of 720 rpm, a compaction pressure of 794.4 MPa and sintering at 1400 °C in an argon atmosphere. Compared to commercial SS316 and fabricated SS316L, the composites had 7.4 times and 11 times lower wear rate, respectively. However, the commercial 90WC-10Co showed 2.2 times lower wear rate compared to the fabricated SS316L-Al2O3 composites primarily due to the higher ceramic content of 90 wt.% in the reference WC-Co. However, eliminating the relatively high porosity of about 5 vol% using processes such as HIP and hot pressing can be expected to lead to further substantial improvements of the composites wear resistance.

Keywords: SS316L, Al2O3, powder metallurgy, wear characterization

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Authors: Muhammad Saleem

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Background: Inattentive food choices and engagement in excessive physical activities by male athletes can potentially lead to adverse health consequences. Objective: The aim was to ascertain the occurrence of risk factors associated with the Male Athlete Triad among young elite athletes in Pakistan. Methodology: In 2018, a cross-sectional study based on questionnaires was conducted at the Pakistan Sports Board. The study aimed to explore the risk factors related to the Male Athlete Triad in young elite athletes who were part of national training camps in major metropolitan areas. The study included proficient male elite athletes aged 18 to 25 years, capable of understanding the English questionnaire. The athletes completed a survey encompassing aspects like demographic information, educational background, Body Mass Index (BMI), sports involvement, and hours of participation. Additionally, they filled out the Eating Attitude Test-26 (EAT-26) and questionnaires assessing risks of amenorrhea and low bone mineral density. The prevalence of risk factors for each of the three components was individually evaluated. The collected data underwent analysis using SPSS-20, with descriptive statistics being applied. Results: The study comprised a sample of 90 elite athletes (mean age: 23.57 ± 2.37 years, mean BMI: 21.97 ± 1.90) engaged in various sports. The EAT-26 results indicated that 50% of athletes were at risk of developing an eating disorder. Moreover, 83.3% exhibited disordered eating behaviors that necessitated referral. Risks for amenorrhea were observed in 15% of the participants, and regarding low bone mineral density, notable risks were absent except for the consumption of caffeinated beverages, which was noted in 51.7% of participants. Conclusion: The study identified a significant prevalence of disordered eating risk among male elite athletes in Pakistan. However, the risks associated with amenorrhea and low bone mineral density were not a major concern in this particular group.

Keywords: 1. health and physical education risk factors male athlete associated with the male athlete traid in young elite athlete from pakistan., 2. sports sciences pakistan, 3. risk factors sports sciences pakistan, 4. triad and young elite athlete from pakistan

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Authors: Manjusha C. Padole, Parag A. Deshpande

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Density functional theory calculations were carried out for identification of an active heterogeneous catalyst to carry out Heck coupling reaction which is of pharmaceutical importance. One of the carbonaceous nanomaterials, heterofullerene, was designed for the reaction. Stability and reactivity of the proposed heterofullerenes (C59M, M = Pd/Ni) were established with insights into the metal-carbon bond, electron affinity and chemical potential. Adsorbent potentials of both the heterofullerenes were examined from the adsorption study of four halobenzenes (C6H5F, C6H5Cl, C6H5Br and C6H5I). Oxidative addition activities of all four halobenzenes were investigated by developing free energy landscapes over both the heterofullerenes for rate determining step (oxidative addition). C6H5I showed a good catalytic activity for the rate determining step. Thus, C6H5I was proposed as a suitable halobenzene and complete free energy landscapes for Heck coupling reaction were developed over C59Pd and C59Ni. Smaller activation barriers observed over C59Pd in comparison with C59Ni put us in a position to propose C59Pd to be an efficient heterofullerene for carrying Heck coupling reaction.

Keywords: metal-substituted fullerene, density functional theory, electron affinity, oxidative addition, Heck coupling reaction

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Authors: Monisha Pattanaik

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In scenarios where users have to work with large amounts of hierarchical data structures combined with visualizations (For example, Construction 3d Models, Manufacturing equipment's models, Gantt charts, Building Plans), the data structures have a high density in terms of consisting multiple parent nodes up to 50 levels and their siblings to descendants, therefore convey an immediate feeling of complexity. With customers moving to consumer-grade enterprise software, it is crucial to make sophisticated features made available to touch devices or smaller screen sizes. This paper evaluates the UI component that allows users to scroll through all deep density levels using a slider overlay on top of the hierarchy table, performing several actions to focus on one set of objects at any point in time. This overlay component also solves the problem of excessive horizontal scrolling of the entire table on a fixed pane for a hierarchical table. This component can be customized to navigate through parents, only siblings, or a specific component of the hierarchy only. The evaluation of the UI component was done by End Users of application and Human-Computer Interaction (HCI) experts to test the UI component's usability with statistical results and recommendations to handle complex hierarchical data visualizations.

Keywords: building information modeling, digital twin, navigation, UI component, user interface, usability, visualization

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Authors: Esther O. Adebitan, Florence Oyelade

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The Millennium Development Goals (MDGs) was initiated by the UN member nations’ aspiration for the betterment of human life. It is expressed in a set of numerical ‎and time-bound targets. In more recent time, the aspiration is shifting away from just the achievement to the sustainability of achieved MDGs beyond the 2015 target. The main objective of this study was assessing how much the hotel industry within the Nigerian Federal Capital Territory (FCT) as a member of the global community is involved in the achievement of sustainable MDGs within the FCT. The study had two population groups consisting of 160 hotels and the communities where these are located. Stratified random sampling technique was adopted in selecting 60 hotels based on large, medium ‎and small hotels categorisation, while simple random sampling technique was used to elicit information from 30 residents of three of the hotels host communities. The study was guided by tree research questions and two hypotheses aimed to ascertain if hotels see the need to be involved in, and have policies in pursuit of achieving sustained MDGs, and to determine public opinion regarding hotels contribution towards the achievement of the MDGs in their communities. A 22 item questionnaire was designed ‎and administered to hotel managers while 11 item questionnaire was designed ‎and administered to hotels’ host communities. Frequency distribution and percentage as well as Chi-square were used to analyse data. Results showed no significant involvement of the hotel industry in achieving sustained MDGs in the FCT and that there was disconnect between the hotels and their immediate communities. The study recommended that hotels should, as part of their Corporate Social Responsibility pick at least one of the goals to work on in order to be involved in the attainment of enduring Millennium Development Goals.

Keywords: MDGs, hotels, FCT, host communities, corporate social responsibility

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Authors: Mohammad Najmuddin Khan, Mohamad Khaleel Albalwi

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The prevalence of obesity has risen dramatically in past several decades. Hormonal and genetic factors are rarely the cause of childhood obesity. Because obese adult may suffer life-long physical and emotional consequences, it is imperative to discuss prevention with parents during well-child examinations. Purpose of the study was to compare the serum lipid profile of obese and non-obese males. Twenty two male students were selected from Al-Jouf University. Their age ranged from 19 to 29. They were divided into groups. One group (N=15) having more than 20% fat was considered as obese group, another group (N=7) was considered as non-obese group. Fasting blood samples were analysed for blood cholesterol, triglycerides, low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C). Independent test was applied to compare mean difference. In obese group, significantly higher cholesterol and triglycerides were observed. On the contrary, obese group had significantly lower HDL-C concentration than the non-obese group. The adult obese has relatively larger changes in serum lipids at any given level of obesity. On the average, higher amount of fat makes it more likely for an individual to be dyslipidemic and to express elements of the metabolic syndrome. Increased triglycerides level in obese impaired lipolysis which reduced the HDL-C concentrations.

Keywords: obesity, serum lipid profile, Al-Jouf, HDL, LDL

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Authors: Kwangwon Seo, Haksoo Han

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Al-Si was synthesized and introduced in poly 2,2’-m-(phenylene)-5,5’-bibenzimidazole (PBI). As a result, a series of five Al-Si/PBI composite (ASPBI) membranes (0, 3, 6, 9, and 12 wt.%) were developed and characterized for application in high temperature polymer electrolyte membrane fuel cells (HT-PEMFCs). The chemical and morphological structure of ASPBI membranes were analyzed by Fourier transform infrared spectroscopy, X-ray diffractometer and scanning electron microscopy. According to the doping level test and thermogravimetric analysis, as the concentration of Al-Si increased, the doping level increased up to 475%. Moreover, the proton conductivity, current density at 0.6V, and maximum power density of ASPBI membranes increased up to 0.31 Scm-1, 0.320 Acm-2, and 0.370 Wcm-2, respectively, because the increased concentration of Al-Si allows the membranes to hold more PA. Alternatively, as the amount of Al-Si increased, the tensile strength of PA-doped and -undoped membranes decreased. This was resulted by both excess PA and aggregation, which can cause serious degradation of the membrane and induce cracks. Moreover, the PA-doped and -undoped ASPBI12 had the lowest tensile strength. The improved performances of ASPBI membranes imply that ASPBI membranes are possible candidates for HT-PEMFC applications. However, further studies searching to improve the compatibility between PBI matrix and inorganic and optimize the loading of Al-Si should be performed.

Keywords: composite membrane, high temperature polymer electrolyte membrane fuel cell, membrane electrode assembly, polybenzimidazole, polymer electrolyte membrane, proton conductivity

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Authors: Baleeqs, O. Adegoke, Adeola, O. Aburime

Abstract:

Juvenile delinquency is fast becoming one of the largest problems facing many societies due to many different factors ranging from parental factors to bullying at schools all which had led to different theoretical notions by different scholars. Delinquency is an illegal or immoral behaviour, especially by the young person who behaves in a way that is illegal or that society does not approve of. The purpose of the study was to investigate causes and effects of delinquent behaviours among adolescent in juvenile home in Osun State. A descriptive survey research type was employed. The random sampling technique was used to select 100 adolescents in Juvenile home in Osun State. Questionnaires were developed and given to them. The data collected from this study were analyzed using frequency counts and percentage for the demographic data in section A, while the two research hypotheses postulated for this study were tested using t-test statistics at the significance level of 0.05. Findings revealed that the greatest school effects of delinquent behaviours among adolescent in juvenile home in Osun by respondents were their aggressive behaviours. Findings revealed that there was a significant difference in the causes and effects of delinquent behaviours among adolescent in juvenile home in Osun State. It was also revealed that there was no significant difference in the causes and effects of delinquent behaviours among secondary school students in Osun based on gender. These recommendations were made in order to address the findings of this study: More number of teachers should be appointed in the observation home so that it will be possible to provide teaching to the different age group of delinquents. Developing the infrastructure facilities of short stay homes and observation home is a top priority. Proper counseling session’s interval is highly essential for these juveniles.

Keywords: behaviour, delinquency, juvenile, random sampling, statistical techniques, survey

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Authors: Sarish Rehman, Kishwar Khan, Yanglong Hou

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Among the existed myriad energy-storage technologies, lithium–sulfur batteries (LSBs) show the appealing potential for the ubiquitous growth of next-generation electrical energy storage application, owing to their unparalleled theoretical energy density of 2600 Wh/kg that is over five times larger than that of conventional lithium-ion batteries (LIBs). Despite its significant advances, its large scale implementations are plagued by multitude issues: particularly the intrinsic insulating nature of the sulfur (10-30 S/cm), mechanical degradation of the cathode due to large volume changes of sulfur up to 80 % during cycling and loss of active material (producing polysulfide shuttle effect). We design a unique structure, namely silicon/silica (Si/SiO2) crosslink with hierarchical porous carbon spheres (Si/SiO2@C), and use it as a new and efficient sulfur host to prepare Si/SiO2@C-S hybrid spheres to solve the hurdle of the polysulfides dissolution. As results of intriguing structural advantages developed hybrids spheres, it acts as efficient polysulfides reservoir for enhancing lithium sulfur battery (LSB) in the terms of capacity, rate ability and cycling stability via combined chemical and physical effects.

Keywords: high specific surface area, high power density, high content of sulfur, lithium sulfur battery

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Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

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Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

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Authors: Sindhu S Nair, Atul Thakur, Preeti Thakur, Trukhanov Alex

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Perovskite-based absorbing materials that are organic, inorganic, or hybrid have gained interest as an appealing candidate for the development of solar cell devices. Lead-based perovskites are among the most promising materials, but their application is plagued with toxicity and stability concerns. Most of the perovskite solar cell consists of conventional (n-i-p) structure with organic or inorganic charge transport materials. The commercial application of such device is limited due to higher J-V hysteresis and the need for high temperature during fabrication. This numerical analysis primarily directs to investigate the performance of various inorganic lead-free valency ordered double perovskite absorber materials and to develop an inverted perovskite solar cell device structure. Simulation efforts using SCAPS-1D was carried out with various organic and inorganic charge transport materials with absorber layer materials, and their performance has been evaluated for various factors of thickness, absorber thickness, absorber defect density, and interface defect density to achieve the optimized structure.

Keywords: perovskite materials, solar cell, inverted solar cell, inorganic perovskite solar cell materials, cell efficiency

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: Sogol Zarafshan

Abstract:

The present study aimed to identify important factors affecting the effectiveness of quality control circles in a hospital, as well as rank them using a combination of fuzzy VIKOR and Grey Relational Analysis (GRA). The study population consisted of five academic members and five experts in the field of nursing working in a hospital, who were selected using a purposive sampling method. Also, a sample of 107 nurses was selected through a simple random sampling method using their employee codes and the random-number table. The required data were collected using a researcher-made questionnaire which consisted of 12 factors. The validity of this questionnaire was confirmed through giving the opinions of experts and academic members who participated in the present study, as well as performing confirmatory factor analysis. Its reliability also was verified (α=0.796). The collected data were analyzed using SPSS 22.0 and LISREL 8.8, as well as VIKOR–GRA and IPA methods. The results of ranking the factors affecting the effectiveness of quality control circles showed that the highest and lowest ranks were related to ‘Managers’ and supervisors’ support’ and ‘Group leadership’. Also, the highest hospital performance was for factors such as ‘Clear goals and objectives’ and ‘Group cohesiveness and homogeneity’, and the lowest for ‘Reward system’ and ‘Feedback system’, respectively. The results showed that although ‘Training the members’, ‘Using the right tools’ and ‘Reward system’ were factors that were of great importance, the organization’s performance for these factors was poor. Therefore, these factors should be paid more attention by the studied hospital managers and should be improved as soon as possible.

Keywords: Quality control circles, Fuzzy VIKOR, Grey Relational Analysis, Importance–Performance Analysis

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Authors: Swati Bhasin, Ali Ahmed, Valence Xavier, Ben Liu

Abstract:

Aims: Diarrhea is a problem that is a frequent clinic referral to the gastroenterology and surgical team from the General practitioner. To establish a diagnosis, these patients undergo colonoscopy. The current practice at our district general hospital is to perform random left and right colonic biopsies. National guidelines issued by the British Society of Gastroenterology advise all patients presenting with chronic diarrhea should have an Ileoscopy as an indicator for colonoscopy completion. Our primary aim was to check if Terminal ileum (TI) biopsy is required to establish a diagnosis of inflammatory bowel disease (IBD). Methods: Data was collected retrospectively from November 2018 to November 2019. The target population were patients who underwent colonoscopies for diarrhea. Demographic data, endoscopic and histology findings of TI were assessed and analyzed. Results: 140 patients with a mean age of 57 years (19-84) underwent a colonoscopy (M: F; 1:2.3). 92 patients had random colonic biopsies taken and based on the histological results of these, 15 patients (16%) were diagnosed with IBD. The TI was successfully intubated in 40 patients, of which 32 patients had colonic biopsies taken as well. 8 patients did not have a colonic biopsy taken. Macroscopic abnormality in the TI was detected in 5 patients, all of whom were biopsied. Based on histological results of the biopsy, 3 patients (12%) were diagnosed with IBD. These 3 patients (100%) also had colonic biopsies taken simultaneously and showed inflammation. None of the patients had a diagnosis of IBD confirmed on TI intubation alone (where colonic biopsies were not done). None of the patients has a diagnosis of IBD confirmed on TI intubation alone (where colonic biopsies were negative). Conclusion: TI intubation is a highly-skilled, time-consuming procedure with a higher risk of perforation, which as per our study, has little additional diagnostic value in finding IBD for symptoms of diarrhea if colonic biopsies are taken. We propose that diarrhea is a colonic symptom; therefore, colonic biopsies are positive for inflammation if the diarrhea is secondary to IBD. We conclude that all of the IBDs can be diagnosed simply with colonic biopsies.

Keywords: biopsy, colon, IBD, terminal ileum

Procedia PDF Downloads 122