Search results for: hybrid clustering model

Authors: Nur Suraya Anis Ahmad Bakhtiar, Hazizan Md Akil

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In the present work, the dielectric properties of Epoxy/MWCNTs-muscovite HYBRID and MIXED composites based on ratio 30:70 were studies. The multi-wall carbon nanotubes (MWCNTs) were prepared by two method; (a) muscovite-MWCNTs hybrids were synthesized by chemical vapor deposition (CVD) and (b) physically mixing of muscovite with MWCNTs. The effect of different preparations of the composites and filler loading was evaluated. It is revealed that the dielectric constants of HYBRID epoxy composites are slightly higher compared to MIXED epoxy composites. It is also indicated that the dielectric constant increased by increases the MWCNTs filler loading.

Keywords: muscovite, epoxy, dielectric properties, hybrid composite

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Authors: Amar Patnaik, Pankaj Agarwal

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This paper investigates the experimental study of hardness and compressive strength of hybrid glass/steel fiber reinforced polymer composites by varying the glass and steel fiber layer in the epoxy matrix. The hybrid composites with four stacking sequences HSG-1, HSG-2, HSG-3, and HSG-4 were fabricated by the VARTM process under the controlled environment. The experimentally evaluated results of Vicker’s hardness of the fabricated composites increases with an increase in the fiber layers sequence showing the high resistance. The improvement of micro-structure ability has been observed from the SEM study, which governs in the enhancement of compressive strength. The finite element model was developed on ANSYS to predict the above said properties and further compared with experimental results. The results predicted by the numerical simulation are in good agreement with the experimental results. The hybrid composites developed in this study was identified as the preferred materials due to their excellent mechanical properties to replace the conventional materialsused in the marine structures.

Keywords: finite element method, interfacial strength, polymer composites, VARTM

Procedia PDF Downloads 109

Authors: William Wong Xiu Shun, Yoonjin Hyun, Mingyu Kim, Seongi Choi, Namgyu Kim

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Recently, the demand of extracting the R&D keywords from the issues and using them in retrieving R&D information is increasing rapidly. But it is hard to identify the related issues or to distinguish them. Although the similarity between the issues cannot be identified, but with the R&D lexicon, the issues that always shared the same R&D keywords can be determined. In details, the R&D keywords that associated with particular issue is implied the key technology elements that needed to solve the problem of the particular issue. Furthermore, the related issues that sharing the same R&D keywords can be showed in a more systematic way through the issue clustering constructed from the perspective of R&D. Thus, sharing of the R&D result and reusable of the R&D technology can be facilitated. Indirectly, the redundancy of investment on the same R&D can be reduce as the R&D information can be shared between those corresponding issues and reusability of the related R&D can be improved. Therefore, a methodology of constructing an issue clustering from the perspective of common R&D keywords is proposed to satisfy the demands mentioned.

Keywords: clustering, social network analysis, text mining, topic analysis

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Authors: Arpan Dwivedi, Yogesh Pahariya

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In this paper, optimal design of hybrid standalone power supply system (SAPS) is done for off grid applications in remote areas where transmission of power is difficult. The hybrid SAPS system uses two primary energy sources, wind and solar, and in addition to these diesel generator is also connected to meet the load demand in case of failure of wind and solar system. This paper presents mathematical modeling of 1.4 MW hybrid SAPS system for rural electrification. This paper firstly focuses on mathematical modeling of PV module connected in a string, secondly focuses on modeling of permanent magnet wind turbine generator (PMWTG). The hybrid controller is also designed for selection of power from the source available as per the load demand. The power output of hybrid SAPS system is analyzed for meeting load demands at urban as well as for rural areas.

Keywords: SAPS, DG, PMWTG, rural area, off-grid, PV module

Procedia PDF Downloads 218

Authors: Emiel Caron

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Patent databases contain patent related data, organized in a relational data model, and are used to produce various patent statistics. These databases store raw data about scientific references cited by patents. For example, Patstat holds references to tens of millions of scientific journal publications and conference proceedings. These references might be used to connect patent databases with bibliographic databases, e.g. to study to the relation between science, technology, and innovation in various domains. Problematic in such studies is the low data quality of the references, i.e. they are often ambiguous, unstructured, and incomplete. Moreover, a complete bibliographic reference is stored in only one attribute. Therefore, a computerized cleaning and disambiguation method for large patent databases is developed in this work. The method uses rule-based scoring and clustering. The rules are based on bibliographic metadata, retrieved from the raw data by regular expressions, and are transparent and adaptable. The rules in combination with string similarity measures are used to detect pairs of records that are potential duplicates. Due to the scoring, different rules can be combined, to join scientific references, i.e. the rules reinforce each other. The scores are based on expert knowledge and initial method evaluation. After the scoring, pairs of scientific references that are above a certain threshold, are clustered by means of single-linkage clustering algorithm to form connected components. The method is designed to disambiguate all the scientific references in the Patstat database. The performance evaluation of the clustering method, on a large golden set with highly cited papers, shows on average a 99% precision and a 95% recall. The method is therefore accurate but careful, i.e. it weighs precision over recall. Consequently, separate clusters of high precision are sometimes formed, when there is not enough evidence for connecting scientific references, e.g. in the case of missing year and journal information for a reference. The clusters produced by the method can be used to directly link the Patstat database with bibliographic databases as the Web of Science or Scopus.

Keywords: clustering, data cleaning, data disambiguation, data mining, patent analysis, scientometrics

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Authors: Reda Dzingelevičienė, Vytautas Abromaitis, Nerijus Dzingelevičius, Kęstutis Baranauskis, Saulius Raugelė, Malgorzata Mlynska-Szultka, Sergej Suzdalev, Reza Pashaei, Sajjad Abbasi, Boguslaw Buszewski

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A unique hybrid technology was developed for the removal of COVID-19 specific contaminants from wastewater. Reactor testing was performed using model water samples contaminated with COVID-19 pharmaceuticals and microplastics. Different hydraulic retention times, concentrations of pollutants and dissolved ozone were tested. Liquid Chromatography-Mass Spectrometry, solid phase extraction, surface area and porosity, analytical tools were used to monitor the treatment efficiency and remaining sorption capacity of the spent adsorbent. The combination of advanced oxidation and adsorption processes was found to be the most effective, with the highest 90-99% and 89-95% molnupiravir and microplastics contaminants removal efficiency from the model wastewater. The research has received funding from the European Regional Development Fund (project No 13.1.1-LMT-K-718-05-0014) under a grant agreement with the Research Council of Lithuania (LMTLT), and it was funded as part of the European Union’s measure in response to the COVID-19 pandemic.

Keywords: adsorption, hybrid reactor system, pharmaceuticals-microplastics, wastewater

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Authors: S. O. Ologe, U. P. Anaidhuno, Duru C. A.

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This research investigated the design and analysis of a rear bumper of an automobile with a hybrid polymer composite of OPEBF/Banana fibre. OPEBF/Banana fibre hybrid polymers composite is of low cost, lightweight, as well as possesses satisfactory mechanical properties. In this research work, hybrid composites have been developed using the hand layup technique based on the percentage combination of OPEBF/Banana fibre at 10:90, 20:80, 30:70, 40:60, 50:50. 60:40, 70:30. 20:80, 90:10, 95:5. The mechanical properties in the context of compressive strength of 65MPa, a flexural strength of 20MPa, and impact strength of 3.25Joule were observed, and the simulation analysis on the induction of 500N load at the factor of safety of 3 was observed to have displayed a good strength suitable for automobile bumper with the advantages of weight reduction.

Keywords: OPEBF, Banana, fibre, hybrid

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Authors: Danladi Ali

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In this paper, we measured GSM signal strength in the Dnepropetrovsk city in order to predict path loss in study area using nonlinear autoregressive neural network prediction and we also, used neural network clustering to determine average GSM signal strength receive at the study area. The nonlinear auto-regressive neural network predicted that the GSM signal is attenuated with the mean square error (MSE) of 2.6748dB, this attenuation value is used to modify the COST 231 Hata and the Okumura-Hata models. The neural network clustering revealed that -75dB to -95dB is received more frequently. This means that the signal strength received at the study is mostly weak signal

Keywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment and model

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Authors: Christian Castro Samaniego, Daniel Icaza Alvarez, Juan Portoviejo Brito

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For this research work, hybrid wind-photovoltaic (SHEF) systems were considered as renewable energy sources that take advantage of wind energy and solar radiation to transform into electrical energy. In the present research work, the feasibility of a wind-photovoltaic hybrid generation system was analyzed for the La Tranca tourist viewpoint of the Chordeleg canton in Ecuador. The research process consisted of the collection of data on solar radiation, temperature, wind speed among others by means of a meteorological station. Simulations were carried out in MATLAB/Simulink based on a mathematical model. In the end, we compared the theoretical radiation-power curves and the measurements made at the site.

Keywords: hybrid system, wind turbine, modeling, simulation, validation, experimental data, panel, Ecuador

Procedia PDF Downloads 216

Authors: Usman Abubakar, Xiaoyuan Wang, Sayyed Haleem Shah, Sadiq Ur Rahman, Rabiu Saleh Zakariyya

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High-speed Permanent magnet synchronous machine (HSPMSM) uses in different industrial applications like blowers, compressors as a result of its superb performance. Nevertheless, the over-temperature rise of both winding and PM is one of their substantial problem for a high-power HSPMSM, which affects its lifespan and performance. According to the literature, HSPMSM with a Hybrid cooling configuration has a much lower temperature rise than non-hybrid cooling. This paper presents the design 185kW, 26K rpm with two different cooling configurations, i.e., hybrid cooling configuration (forced air and housing spiral water jacket) and non-hybrid (forced air cooling assisted with winding’s potting material and sleeve’s material) to enhance the heat dissipation of winding and PM respectively. Firstly, the machine’s electromagnetic design is conducted by the finite element method to accurately account for machine losses. Then machine’s cooling configurations are introduced, and their effectiveness is validated by lumped parameter thermal network (LPTN). Investigation shows that using potting, sleeve materials to assist non-hybrid cooling configuration makes the machine’s winding and PM temperature closer to hybrid cooling configuration. Therefore, the machine with non-hybrid cooling is prototyped and tested due to its simplicity, lower energy consumption and can still maintain the lifespan and performance of the HSPMSM.

Keywords: airflow network, axial ventilation, high-speed PMSM, thermal network

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Authors: Anwar U. Haque, Waqar Asrar, Ashraf Ali Omar, Erwin Sulaeman, Jaffer Sayed Mohamed Ali

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Due to the interference effects, the intrinsic aerodynamic parameters obtained from the individual component testing are always fundamentally different than those obtained for complete model testing. Consideration and limitation for such testing need to be taken into account in any design work related to the component buildup method. In this paper, the scaled model of a straight rectangular canard of a hybrid buoyant aircraft is tested at 50 m/s in IIUM-LSWT (Low-Speed Wind Tunnel). Model and its attachment with the balance are kept rigid to have results free from the aeroelastic distortion. Based on the velocity profile of the test section’s floor; the height of the model is kept equal to the corresponding boundary layer displacement. Balance measurements provide valuable but limited information of the overall aerodynamic behavior of the model. Zero lift coefficient is obtained at -2.2o and the corresponding drag coefficient was found to be less than that at zero angles of attack. As a part of the validation of low fidelity tool, the plot of lift coefficient plot was verified by the experimental data and except the value of zero lift coefficient, the overall trend has under-predicted the lift coefficient. Based on this comparative study, a correction factor of 1.36 is proposed for lift curve slope obtained from the panel method.

Keywords: wind tunnel testing, boundary layer displacement, lift curve slope, canard, aerodynamics

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Authors: Mohamed Bendoukha, Mustapha Mosbah

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The Radiographic apparent assumed that the asymptomatic adjacent segment disease ASD is common after lumbar fusion, but this does not correlate with the functional outcomes while compensatory increased motion and stresses at the adjacent level of fusion is well-known to be associated to ASD. Newly developed, the hybrid stabilization are allocated to substituted for mostly the superior level of the fusion in an attempt to reduce the number of fusion levels and likelihood of degeneration process at the adjacent levels during the fusion with pedicle screws. Nevertheless, its biomechanical efficiencies still remain unknown and complications associated with failure of constructs such screw loosening and toggling should be elucidated In the current study, a finite element (FE) study was performed using a validated L2/S1 model subjected to a moment of 7.5 Nm and follower load of 400 N to assess the biomedical behavior of hybrid constructs based on dynamic topping off, semi rigid fusion. The residual range of motion (ROM), stress distribution at the fused and adjacent levels, stress distribution at the disc and the cage-endplate interface with respect to changes of bone quality were investigated. The hybrid instrumentation was associated with a reduction in compressive stresses compared to the fusion construct in the adjacent-level disc and showed high substantial axial force in the implant while fusion instrumentation increased the motion for both flexion and extension.

Keywords: intervertebral disc, lumbar spine, degenerative nuclesion, L4-L5, range of motion finite element model, hyperelasticy

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Anmari Viljamaa, Elina Varamäki

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In this study we compare the profiles of transitory hybrid entrepreneurs and persistent hybrid entrepreneurs to determine how they differ. Hybrid entrepreneurs (HEs) represent a significant share of entrepreneurial activity yet little is known about them. We define HEs as individuals who are active as entrepreneurs but do no support themselves primarily by their enterprise. Persistent HEs (PHEs) are not planning to transition to fulltime entrepreneurship whereas transitory HEs (THEs) consider it probable. Our results show that THEs and PHEs are quite similar in background. THEs are more interested in increasing their turnover than PHEs, as expected, but also emphasize self-fulfillment as a motive for entrepreneurship more than PHEs. The clearest differences between THEs and PHEs are found in their views on how well their immediate circle supports full-time entrepreneurship, and their views of their own entrepreneurial abilities and the market potential of their firm. Our results support earlier arguments that hybrids should be considered separately in research on entrepreneurial entry and self-employment.

Keywords: hybrid entrepreneurship, part-time entrepreneurship, self-employment, Theory of Planned Behavior

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Authors: Tahri Toufik, Bouchachia Mohamed, Braikia Oussama

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The objective of this work is the design and optimization of a hybrid PV-Diesel-Wind power system with storage in order to power a relay antenna telecommunication isolated in Chlef region. The aim of the simulation of this hybrid system by the HOMER software is to determine the size and the number of each element of the system and to determine the optimal technical and economic configuration using monthly average values per year for a fixed charge antenna relay telecommunication of 22kWh/d.

Keywords: HOMER, hybrid, PV-diesel-wind system, relay antenna telecommunication

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Authors: F. J. Adeyeye, D. Eni, K. M. Okedoye

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In this paper we present a Hybrid of Adomian decomposition method (ADM). This is the substitution of a One-step method of Taylor’s series approximation of orders I and II, into the nonlinear part of Adomian decomposition method resulting in a convergent series scheme. This scheme is applied to solve some Logistic problems represented as Abelian differential equation and the results are compared with the actual solution and Runge-kutta of order IV in order to ascertain the accuracy and efficiency of the scheme. The findings shows that the scheme is efficient enough to solve logistic problems considered in this paper.

Keywords: Adomian decomposition method, nonlinear part, one-step method, Taylor series approximation, hybrid of Adomian polynomial, logistic problem, Malthusian parameter, Verhulst Model

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Authors: Blessing Atim Aderibigbe

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A series of amine/ester-linked hybrid compounds containing pharmacophores, such as ursolic acid, oleanolic acid, ferrocene and bisphosphonates, were synthesized in an attempt to develop potent antibacterial and anticancer agents. Their structures were analyzed and confirmed using Nuclear Magnetic Resonance, Fourier Transform Infrared Spectroscopy, and mass spectroscopy. All the synthesized hybrid compounds were evaluated for their antibacterial activities against eleven selected bacterial strains using a serial dilution method. Some of the compounds displayed significant antibacterial activity against most of the bacterial and fungal strains. In addition, the in vitro cytotoxicity of these compounds was also performed against selected cancer cell lines. Some of the compounds were also found to be more active than their parent compounds, revealing the efficacy of designing hybrid molecules using plant-based bioactive agents.

Keywords: ursolic acid, hybrid drugs, oleanolic acid, bisphosphonates

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Authors: Samir Hessas

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Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

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Authors: Habtemariam Alemu

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It has been known that the performance of position and force control is highly affected by both robot dynamic and environment stiffness uncertainties. In this paper, joint space hybrid force and position control strategy with self-selecting matrix using artificial neural network compensator is proposed. The objective of the work is to improve controller robustness by applying a neural network technique in order to compensate the effect of uncertainties in the robot model. Simulation results for a 6 degree of freedom (6-DoF) manipulator and different types of environments showed the effectiveness of the suggested approach. 6-DoF Puma 560 family robot manipulator is chosen as industrial robot and its efficient dynamic model is designed using Matlab/SimMechanics library.

Keywords: robot manipulator, force/position control, artificial neural network, Matlab/Simulink

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Mircea Pastrav, Horia Constantinescu

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The construction industry is currently trying to develop sustainable reinforced concrete structures. In trying to aid in the effort, the research presented in this paper aims to prove the efficiency of modified special hybrid moment frames composed of discretely jointed precast and post-tensioned concrete members. This aim is due to the fact that current design standards do not cover the spatial design of moment frame structures assembled by post-tensioning with special hybrid joints. This lack of standardization is coupled with the fact that previous experimental programs, available in scientific literature, deal mainly with plane structures and offer little information regarding spatial behavior. A spatial model of a modified hybrid moment frame is experimentally analyzed. The experimental results of a natural scale model test of a corner column-beams sub-structure, cut from an actual multilevel building tested to seismic type loading are presented in order to highlight the behavior of this type of structure. The test is performed under alternative cycles of imposed lateral displacements, up to a storey drift ratio of 0.035. Seismic response of the spatial model is discussed considering the acceptance criteria for reinforced concrete frame structures designed based on experimental tests, as well as some of its major sustainability features. The results obtained show an overall excellent behavior of the system. The joint detailing allows for quick and cheap repairs after an accidental event and a self-balancing behavior of the system that ensures it can be used almost immediately after an accidental event it.

Keywords: modified hybrid joint, seismic type loading response, self-balancing structure, acceptance criteria

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

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Authors: Rama Bhargava

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In the current paper, numerical simulation has been performed for the two-dimensional time dependent Pennes’ heat transfer model which is solved for irregular diseased tumor cells. An elliptic cryoprobe of varying sizes is taken at the center of the computational domain in such a manner that the location of the probe is fixed throughout the computation. The phase transition occurs due to the effect of probe with infusion of different nanoparticles Au, Al₂O₃, Fe₃O₄. The cooling performance of these nanoparticles injected at very low temperature, has been studied by implementing a hybrid FEM/EFGM method in which the whole domain is decomposed into two subdomains. The results are shown in terms of temperature profile inside the computational domain. Rate of cooling is obtained for various nanoparticles and it is observed that infusion of Au nanoparticles is very much efficient in increasing the heating rate than other nanoparticles. Such numerical scheme has direct applications where the domain is irregular.

Keywords: cryosurgery, hybrid EFGM/FEM, nanoparticles, simulation

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Authors: S. M. Azad, H. Ghodsi Pour, F. Roshannafasa

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In recent years ‘technology management and policymaking’ is one of the most important problems in management science. In this field, different generations of innovation and technology management are presented which the earliest one is Innovation System (IS) approach. In a general classification, innovation systems are divided in to 4 approaches: Technical, sectoral, regional, and national. There are many researches in relation to each of these approaches in different academic fields. Every approach has some benefits. If two or more approaches hybrid, their benefits would be combined. In addition, according to the sectoral structure of the governance model in Iran, in many sectors such as information technology, the combination of three other approaches with sectoral approach is essential. Hence, in this paper, combining two IS approaches (technical and sectoral) and using system dynamics, a generic model is presented for a sample of software industry. As a complimentary point, this article is introducing a new hybrid approach called Techno-Sectoral Innovation System. This TSIS model is accomplished by Changing concepts of the ‘functions’ which came from Technological IS literature and using them into sectoral system as measurable indicators.

Keywords: innovation system, technology, techno-sectoral system, functional indicators, system dynamics

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Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

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Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

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Authors: Jae-Yong Sim, Jung-Hun Kwon, Ji-Sung Park, Kee-Joe Lim

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One of the latest trends for insulation systems to improve the insulation performance is the use of eco-friendly hybrid insulation using compressed dry-air. Despite the excellent insulation performance of sulphurhexafluoride (SF6) gas, its use has been restricted due to the problems with significant global warming potential (GWP). Accordingly, lightning impulse performance of the hybrid insulation system covered with an aluminum trihydrate/silicone rubber (ATH/SIR) nanocomposite was examined in air at atmospheric pressure and in compressed air at pressures between 0.2 and 0.6 MPa. In the experiments, the most common breakdown path took place along the surface of the covered rod. The insulation reliability after several discharges should be guaranteed in hybrid insulation. On the other hand, the surface of the covered rod was carbonized after several discharges. Therefore, nanoscale ATH can be used as a reinforcement of covered dielectrics to inhibit carbonization on the surface of a covered rod. The results were analyzed in terms of the surface resistivity of the cover dielectrics.

Keywords: nanocomposite, hybrid insulation, ATH, dry-air

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Authors: Ritu Vashistha, Jitender Kumar

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Clustering using the K-means algorithm is a very common way to understand and analyze the obtained output data. When a similar object is grouped, this is called the basis of Clustering. There is K number of objects and C number of cluster in to single cluster in which k is always supposed to be less than C having each cluster to be its own centroid but the major problem is how is identify the cluster is correct based on the data. Formulation of the cluster is not a regular task for every tuple of row record or entity but it is done by an iterative process. Each and every record, tuple, entity is checked and examined and similarity dissimilarity is examined. So this iterative process seems to be very lengthy and unable to give optimal output for the cluster and time taken to find the cluster. To overcome the drawback challenge, we are proposing a formula to find the clusters at the run time, so this approach can give us optimal results. The proposed approach uses the Euclidian distance formula as well melanosis to find the minimum distance between slots as technically we called clusters and the same approach we have also applied to Ant Colony Optimization(ACO) algorithm, which results in the production of two and multi-dimensional matrix.

Keywords: ant colony optimization, data clustering, centroids, data mining, k-means

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Authors: Aniket Aaba Kadam, Manish Mangesh Panchal, Roushan Ashit Sharma

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This project focuses on the design and development of a lab-scale hybrid rocket motor to accurately determine the regression rate of a fuel/oxidizer combination consisting of solid paraffin and gaseous oxygen (GOX). Hybrid motors offer the advantage of on-demand thrust control over both solid and liquid systems in certain applications. The thermodynamic properties of the propellant combination were calculated using NASA CEA at different chamber pressures and corresponding O/F values to determine initial operating conditions with suitable peak temperatures and optimal O/F values. The project also includes the design of the injector orifice and the determination of the final design configurations of the motor casing, pressure control setup, and valve configuration. This research will be valuable in advancing the understanding of paraffin-based propulsion and improving the performance of hybrid rocket motors.

Keywords: hybrid rocket, NASA CEA, injector, thrust control

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Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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Authors: Iftikhar Ahmad, Abulhakim Almajid

Abstract:

Alumina (Al2O3) is an attractive structural ceramic however; brittleness turns Al2O3 down for advanced applications. Development of multi-phase phase ceramics systems is promising to curtail the brittleness and the incorporation of strong/elastic graphene, as third phase, into dual phase (Al2O3-SiC) is striking for mechanical upgrading purpose. Thin graphene nanosheets (GNS) were prepared by thermal exfoliation process and reinforced into dual phase ceramic system. The hybrid nanocomposite was consolidated by novel HF-IH (high-frequency induction heating) sintering furnace at 1500 °C under 50 MPa in vacuum conditions. Structural features and grain size of the resulting nanocomposite were analyzed by SEM and TEM whilst the mechanical properties were assessed by microhardness and nanoindentation techniques. The fracture toughness of the hybrid nanocomposites was appraised by direct crack measurement method. Electron microscopic investigations confirmed the preparation of thin (< 10 nm) graphene nanosheets (GNS). HF-IH sintering route condensed the three-phase (GNS-Al2O3-SiC) hybrid nanocomposite system to > 99% relative densities. SEM of the hybrid nanocomposites fractured surfaces revealed even distribution of the nanocomposite constituents and changed in fracture-mode. Structurally, 88% grain reduction into hybrid nanocomposite was also obtained. Mechanically, enhanced fracture toughness (50%) and hardness (53%) were also achieved for hybrid nanocomposites were attained against bench marked monolithic Al2O3.

Keywords: alumina, graphene, hybrid nanocomposites, rapid sintering

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