Search results for: multi layer perceptrons

Authors: Reza Eslami-Farsani, Hamed Khosravi

Abstract:

The aim of this work is to study the influence of multi-walled carbon nanotubes (MWCNTs) addition at various contents with respect to the matrix (0-0.5 wt.% at a step of 0.1 wt.%) on the compressive response of unidirectional basalt fiber (UD-BF)/epoxy composites. Toward this end, MWCNTs were firstly functionalized with 3-glycidoxypropyltrimethoxysilane (3-GPTMS) to improve their dispersion state and interfacial compatibility with the epoxy. Subsequently, UD-BF/epoxy and multiscale 3-GPTMS-MWCNTs/UD-BF/epoxy composites were prepared. The mechanical properties of the composites were determined by quasi-static compression test. The compressive strength of the composites was obtained through performing the compression test on the off-axis specimens and extracting their longitudinal compressive strength. Results demonstrated that the highest value in compressive strength was attained at 0.4 wt.% MWCNTs with 41% increase, compared to the BF/epoxy composite. Potential mechanisms behind these were implied.

Keywords: multiscale polymeric composites, unidirectional basalt fibers, multi-walled carbon nanotubes, surface modification, compressive properties

Procedia PDF Downloads 296

Authors: Mojtaba Saeedinezhad, Sarah Yousefi

Abstract:

In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

Procedia PDF Downloads 337

Authors: M. Taheri Tehrani, H. Ajorloo

Abstract:

In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

Procedia PDF Downloads 504

Authors: Xin Zhao

Abstract:

3D printing is used in creating bone grafts of various architectures by printing materials in a layer-by-layer manner. Traditionally, to make materials printable, heating up or dissolving materials in organic solvents have been used, compromising their capability in loading biomolecules. Photocrosslinkable materials which are initially liquid and printable, and solidified upon light exposure are therefore developed. However, the existing photocrosslinkable materials are either too soft to bear load or non-degradable with potential long-term biocompatibility problems. Here, photocrosslinkable nanocomposite ink is developed composed of poly (lactide-co-propylene glycol-co-lactide) dimethacrylate (PmLnDMA) and hydroxyethyl methacrylate-functionalized hydroxyapatite nanoparticles (nHAMA) mimicking the hairy setae of gecko that can strongly interact with its surroundings to bear high load. Incorporation of nHAMA into PmLnDMA endows the nanocomposite ink with several advantages in (1) improved organic/inorganic interfacial compatibility to increase mechanical strength, (2) readily modulated rheological behaviors, wettability, and biodegradation, (3) enhanced osteoconductivity and osteoinductivity. Moreover, the ink can be rapidly crosslinked upon light exposure, load, and long-term release growth factors, and be printed into 3D bone scaffolds of various shapes and structures according to the patients’ needs. Altogether, this innovation will benefit patients all over the world who suffer from bone fractures, tumors, infections.

Keywords: photocrosslinkable nanocomposite, 3D printing, bone ink, personalized medicine

Procedia PDF Downloads 108

Authors: Massra M. Sabeima, Myriam lamolle, Mohamedade Farouk Nanne

Abstract:

Adapting the learning resources of an e-learning system to the characteristics of the learners is an important aspect to consider when designing an adaptive e-learning system. However, this adaptation is not a simple process; it requires the extraction, analysis, and modeling of user information. This implies a good representation of the user's profile, which is the backbone of the adaptation process. Moreover, during the e-learning process, collaboration with similar users (same geographic province or knowledge context) is important. Productive collaboration motivates users to continue or not abandon the course and increases the assimilation of learning objects. The contribution of this work is the following: we propose an adaptive e-learning semantic platform to recommend learning resources to learners, using ontology to model the user profile and the course content, furthermore an implementation of a multi-agent system able to progressively generate the learning graph (taking into account the user's progress, and the changes that occur) for each user during the learning process, and to synchronize the users who collaborate on a learning object.

Keywords: adaptative learning, collaboration, multi-agent, ontology

Procedia PDF Downloads 164

Authors: Glaoui Hachemi

Abstract:

In this paper, a scheme based on multi-input multi output Fuzzy Sliding Mode control (MIMO-FSMC) for linear speed regulation of winding system is proposed. Once the uncoupled model of the winding system was obtained, a smooth control function with a threshold was selected to indicate how far away the case was from the sliding surface. nevertheless, this control function depends closely on the higher bound of the uncertainties, which generates overlap. So, this size has to be chosen with broad care to obtain high performances. Usually, the upper bound of uncertainties is difficult to know before motor operation, so, a Fuzzy Sliding Mode controller is investigated to resolve this problem, a simple Fuzzy inference mechanism is used to decrease the chattering phenomenon by simple adjustments. A simulation study is achieved and that the indicate fuzzy sliding mode controllers have great potential for use as an alternative to the conventional sliding mode control.

Keywords: Winding system, induction machine, Mechanical tension, Proportional-integral (PI), sliding mode control, Fuzzy logic

Procedia PDF Downloads 84

Authors: Abdul Razzaq Azad

Abstract:

It is known that every human society throughout the world and throughout history, the various religions and their theologies, ethics, and traditions influence everything in their life, shaping socio-economic and political ideas, attitudes and institutions. It is observed that religious teachings and traditions shape how people respond to each other in their daily social inter-course and interaction in the community at large. The majorities of us preserves and protect our own religious beliefs and traditions as generally they symbolize our essential identities, theologically, historically, culturally, socially, and even politically. Our religious faiths symbolize our dignity as persons and our very souls as communities and individuals. It thus goes without saying that in our multi racial and multi religious society, the only way for us to live in peace and harmony is for us to live in peaceful co-existence. It is important for us to recognize, understand, accept and respect each other regardless of our respective belief. The history of interfaith is as ancient as the religions since men and women when not at war with their neighbors have always made an effort to understand them (not least because understanding is a strategy for defense, but also because for as long as there is dialogue wars are delayed).

Keywords: interfaith harmony, world piece order, Islam, religions, lightness,

Procedia PDF Downloads 615

Authors: Micheal O. Alabi

Abstract:

Additive manufacturing (AM) is the official industry standard term (ASTM F2792) for all applications of the technology which is also known as 3D printing technology. It is defined as the process of joining materials to make objects from 3D model data, and it is usually layer upon layer, as opposed to subtractive manufacturing methodologies. This technology has gained significant interest within the academic, research institute and industry because of its ability to create complex geometries with customizable material properties. Despite the late adoption of the technology, additive manufacturing has been active in South Africa for past 21 years and it is predicted that additive manufacturing technology will play a significant and game-changing role in the fourth industrial revolution and in particular it promises to play an ever-growing role in efforts to re-industrialize the economy of South Africa. At the end of 2006, there are approximately ninety 3D printers in South Africa and in 2015 it was estimated that there are 3500 additive manufacturing systems and 3D printers in circulation in South Africa. A reasonable number of these additive manufacturing machines are in the high end of the market, in science councils and higher education institutions and this shows that the future of additive manufacturing in South Africa is very brighter compared to other African countries. This paper reviews the past and current industrial applications of additive manufacturing in South Africa from the academic research and industry perspective and what are the benefits of this technology to manufacturing companies and industrial sectors in the country.

Keywords: additive manufacturing, 3D printing technology, industrial applications, manufacturing

Procedia PDF Downloads 461

Authors: Asaduzzaman Rimon, Pankaj Kumar Jha, Abdullah Al Mansur, Mohammad Mofizul Islam, Nasrin Sultana Juyena, Farida Yeasmin Bari

Abstract:

This study was conducted to determine the effects of multi-species skim milk based extenders on sperm quality at 5ºC with the advancement of preservation time. Altogether forty ejaculates, 8 ejaculates for each of the 5 home-made semen extenders: cow skim milk (CSM), goat skim milk (GSM), sheep skim milk (SSM), buffalo skim milk (BSM) and commercial dried skim milk (CDSM) were examined for motility, plasma membrane integrity and normal morphology % of sperm at 0, 24, 48, 72, 96 and 120 hours, respectively. Sperm motility was significantly decreased (P < 0.05) with the increase of preservation time. There were no significant difference in motility % among CSM (84.0±1.4, 82.3±2.1), GSM (84.5±1.0, 82.5±0.6) and CDSM (85.0±80.3±1.3) extenders at 0 and 24 hours, respectively. However, the motility in GSM extender was significantly higher than BSM, SSM and CDSM extender at 48, 72, 96 and 120 hours. The plasma membrane integrity % at 0 hour had no significant difference among the extenders. But, the plasma membrane integrity % in GSM (84.3±0.9, 81.8±1.3, 78.0±2.2, 74.8±0.5, 72.0±1.4) and CSM (82.8±0.5, 80.8±1.0, 78.0±1.4, 73.5±1.7, 70.3±0.5) extenders were significantly higher than BSM (81.0±1.4, 76.3±2.5, 72.5±1.7, 63.8±2.5, 54.0±4.6), SSM (78.5±1.5, 75.0±1.6, 71.5±2.4, 64.3±1.7, 56.5±2.4) and CDSM extenders (78.3±2.4, 75.8±3.9, 72.5±3.3, 64.8±1.0, 60.5±3.3) at 24, 48, 72, 96 and 120 hours, respectively. The sperm morphology % had no significant difference at 0 hour among the extenders but were significantly higher in GSM (83.0±0.8, 81.3±1.5, 79.3±1.3, 73.0±2.2, 70.3±1.3) and CSM (81.5±1.7, 79.3±1.5, 75.8±1.5, 70.3±1.3, 66.3±1.5) than BSM (79.0±1.2, 75.0±1.4, 69.5±1.7, 64.5±3.1, 56.8±2.2), SSM (79.8±1.3, 76.8±2.1, 71.3±3.0, 66.0±2.7, 60.3±4.5) and CDSM (80.0±1.6, 77.0±2.2, 72.0±2.5, 66.3±2.5, 62.0±4.0) extenders at 24, 48, 72, 96 and 120 hours, respectively. The motility, plasma membrane integrity and normal morphology % of sperm had shown no significant difference between GSM and CSM but were found to be higher in GSM extenders. In the end, we concluded from the above study that the goat milk based extenders (GSM) had optimum sperm preserving quality. However, further studies are required to validate followed by fertility rate.

Keywords: chilled semen, indigenous ram, multi-species skim milk based extenders, preservation

Procedia PDF Downloads 410

Authors: Chunyang Miao, Bingxin Li, Shanglong Ning, Christopher J. B. Ford

Abstract:

While it is challenging to fabricate electronic devices close to atomic dimensions in conventional top-down lithography, molecular electronics is promising to help maintain the exponential increase in component densities via using molecular building blocks to fabricate electronic components from the bottom up. It offers smaller, faster, and more energy-efficient electronic and photonic systems. A self-assembled monolayer (SAM) of molecules is a layer of molecules that self-assembles on a substrate. They are mechanically flexible, optically transparent, low-cost, and easy to fabricate. A large-area multi-layer structure has been designed and investigated by the team, where a SAM of designed molecules is sandwiched between graphene and gold electrodes. Each molecule can act as a quantum dot, with all molecules conducting in parallel. When a source-drain bias is applied, significant current flows only if a molecular orbital (HOMO or LUMO) lies within the source-drain energy window. If electrons tunnel sequentially on and off the molecule, the charge on the molecule is well-defined and the finite charging energy causes Coulomb blockade of transport until the molecular orbital comes within the energy window. This produces ‘Coulomb diamonds’ in the conductance vs source-drain and gate voltages. For different tunnel barriers at either end of the molecule, it is harder for electrons to tunnel out of the dot than in (or vice versa), resulting in the accumulation of two or more charges and a ‘Coulomb staircase’ in the current vs voltage. This nanostructure exhibits highly reproducible Coulomb-staircase patterns, together with additional oscillations, which are believed to be attributed to molecular vibrations. Molecules are more isolated than semiconductor dots, and so have a discrete phonon spectrum. When tunnelling into or out of a molecule, one or more vibronic states can be excited in the molecule, providing additional transport channels and resulting in additional peaks in the conductance. For useful molecular electronic devices, achieving the optimum orbital alignment of molecules to the Fermi energy in the leads is essential. To explore it, a drop of ionic liquid is employed on top of the graphene to establish an electric field at the graphene, which screens poorly, gating the molecules underneath. Results for various molecules with different alignments of Fermi energy to HOMO have shown highly reproducible Coulomb-diamond patterns, which agree reasonably with DFT calculations. In summary, this large-area SAM molecular junction is a promising candidate for future electronic circuits. (1) The small size (1-10nm) of the molecules and good flexibility of the SAM lead to the scalable assembly of ultra-high densities of functional molecules, with advantages in cost, efficiency, and power dissipation. (2) The contacting technique using graphene enables mass fabrication. (3) Its well-observed Coulomb blockade behaviour, narrow molecular resonances, and well-resolved vibronic states offer good tuneability for various functionalities, such as switches, thermoelectric generators, and memristors, etc.

Keywords: molecular electronics, Coulomb blokade, electron-phonon coupling, self-assembled monolayer

Procedia PDF Downloads 53

Authors: Zhou BingHai, Fradet Victor

Abstract:

Lean philosophy follows the simple principle of “creating more value with fewer resources”. In accordance with this policy, material handling can be managed by the mean of Kanban which by triggering every feeding tour only when needed regulates the flow of material in one of the most efficient way. This paper focuses on Kanban Supermarket’s parameters and their optimization on a purely cost-based point of view. Number and size of forklifts, as well as size of the containers they carry, will be variables of the cost function which includes handling costs, inventory costs but also shortage costs. With an innovative computational approach encoded into industrial engineering software Tecnomatix and reproducing real-life conditions, a fictive assembly line is established and produces a random list of orders. Multi-scenarios are then run to study the impact of each change of parameter and the variation of costs it implies. Lastly, best-case scenarios financially speaking are selected.

Keywords: Kanban, supermarket, parts-feeding policies, multi-scenario simulation, assembly line

Procedia PDF Downloads 190

Authors: Md. Kausar Alam, Mohammad Yazdi, Peiman Zogh, Ramin Motamed

Abstract:

The liquefaction-induced ground settlement has caused severe damage to structures in the past decades. However, the amount of building settlement caused by liquefaction is directly proportional to the intensity of the ground shaking. To reduce this soil liquefaction effect, it is essential to examine the influence of peak ground acceleration (PGA). Unfortunately, limited studies have been carried out on this issue. In this study, a series of moderate scale 1g shake table experiments were conducted at the University of Nevada Reno to evaluate the influence of PGA with the same duration in liquefiable soil layers. The model is prepared based on a large-scale shake table with a scaling factor of N = 5, which has been conducted at the University of California, San Diego. The model ground has three soil layers with relative densities of 50% for crust, 30% for liquefiable, and 90% for dense layer, respectively. In addition, a shallow foundation is seated over an unsaturated crust layer. After preparing the model, the input motions having various peak ground accelerations (i.e., 0.16g, 0.25g, and 0.37g) for the same duration (10 sec) were applied. Based on the experimental results, when the PGA increased from 0.16g to 0.37g, the foundation increased from 20 mm to 100 mm. In addition, the expected foundation settlement based on the scaling factor was 25 mm, while the actual settlement for PGA 0.25g for 10 seconds was 50 mm.

Keywords: foundation settlement, liquefaction, peak ground acceleration, shake table test

Procedia PDF Downloads 70

Authors: Liu Shengnan, Sun Liping, Zhu Jianxun

Abstract:

Based on three dimensional potential flow theory, hydrodynamic response analysis is carried on the multi floating bodies system composed of FPSO moored with yoke and shuttle tanker. It considered hydrodynamic interaction between FPSO and shuttle tanker, interaction between the hull and yoke mooring systems, hawsers, fenders, and then focuses on hawsers of the side-by-side offloading system. The influence of hawsers parameters on system safety is studied in respects of hawser stiffness, length and arrangement. Through analysis in different environment conditions and two typical loading conditions, it can be found that a better safety performance can be achieved through these three ways including enlarging the number of hawsers as well as the stiffness of hawsers, changing the length and arrangement of hawsers.

Keywords: yoke mooring, side-by-side offloading, multi floating body, hawser, safety

Procedia PDF Downloads 419

Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

A simulation scheme of rotational motions for predictions of bump-type gas foil bearings operating at steady-state is proposed; and, the scheme is based on multi-physics coupling computer aided engineering packages modularized with computational fluid dynamic model and structure elasticity model to numerically solve the dynamic equation of motions of a hydrodynamic loaded shaft supported by an elastic bump foil. The bump foil is assumed to be modelled as infinite number of Hookean springs mounted on stiff wall. Hence, the top foil stiffness is constant on the periphery of the bearing housing. The hydrodynamic pressure generated by the air film lubrication transfers to the top foil and induces elastic deformation needed to be solved by a finite element method program, whereas the pressure profile applied on the top foil must be solved by a finite element method program based on Reynolds Equation in lubrication theory. As a result, the equation of motions for the bearing shaft are iteratively solved via coupling of the two finite element method programs simultaneously. In conclusion, the two-dimensional center trajectory of the shaft plus the deformation map on top foil at constant rotational speed are calculated for comparisons with the experimental results.

Keywords: computational fluid dynamics, fluid structure interaction multi-physics simulations, gas foil bearing, load capacity

Procedia PDF Downloads 153

Authors: Behnam Shakerian, Negin Razavi

Abstract:

The pathogenesis of coronary artery disease is multifactorial. The epicardial fat pad is a localized fat depot lying between the myocardium and the visceral layer of the pericardium. The mechanisms through which epicardial fat pad can cause atherosclerosis are complex. The epicardial fat pad can surround the coronary arteries and contributes to the development and progression of coronary artery disease. Methods: we selected 50 patients who underwent coronary artery angiography for the evaluation of coronary artery disease that results were positive for coronary artery disease. All patients underwent an echocardiographic examination after coronary angiography to measure epicardial fat pad thickness. The epicardial fat pad was defined as an echo-free space between the myocardium's outer wall and the pericardium's visceral layer. Results: The epicardial fat pad was measured on the right ventricle apex in 46 patients. Sixty- five percent of the studied patients were male. The most common vessel with stenosis was the left anterior descending artery. A significant correlation was observed between epicardial fat pad thickness and the severity of coronary artery disease. Discussions: The epicardial fat pad provides a horizon on the pathophysiology of cardiovascular diseases. It directly contributes to the development and progression of coronary artery disease by causing inflammation and endothelial damage. Further investigations are needed to determine whether medical treatment can reduce the mass of epicardial fat pad and can help to improve atherosclerosis. Conclusion: The epicardial fat pad measurement could be used as an indicator of coronary arteries’ atherosclerosis. Therefore, thickness measurement of the epicardial fat pad in the clinical practice could be of assistance in identifying patients at risk and if required, undergoing supplementary diagnosis with coronary angiography.

Keywords: epicardial, fat pad, coronary artery disease, echocardiography

Procedia PDF Downloads 153

Authors: Xuerui Niu, Bolin Wang, Xinchuang Zhang, Xiaohua Ma, Bin Hou, Ling Yang

Abstract:

The application of discrete GaN-based power switches requires the collaboration of silicon-based peripheral circuit structures. However, the packages and interconnection between the Si and GaN devices can introduce parasitic effects to the circuit, which has great impacts on GaN power transistors. GaN-based monolithic power integration technology is an emerging solution which can improve the stability of circuits and allow the GaN-based devices to achieve more functions. Complementary logic circuits consisting of GaN-based E-mode p-channel heterostructure field-effect transistors (p-HFETs) and E-mode n-channel HEMTs can be served as the gate drivers. E-mode p-HFETs with recessed gate have attracted increasing interest because of the low leakage current and large gate swing. However, they suffer from a poor interface between the gate dielectric and polarized nitride layers. The reliability of p-HFETs is analyzed and discussed in this work. In circuit applications, the inverter is always operated with dynamic gate voltage (VGS) rather than a constant VGS. Therefore, dynamic electrical stress has been simulated to resemble the operation conditions for E-mode p-HFETs. The dynamic electrical stress condition is as follows. VGS is a square waveform switching from -5 V to 0 V, VDS is fixed, and the source grounded. The frequency of the square waveform is 100kHz with the rising/falling time of 100 ns and duty ratio of 50%. The effective stress time is 1000s. A number of stress tests are carried out. The stress was briefly interrupted to measure the linear IDS-VGS, saturation IDS-VGS, As VGS switches from -5 V to 0 V and VDS = 0 V, devices are under negative-bias-instability (NBI) condition. Holes are trapped at the interface of oxide layer and GaN channel layer, which results in the reduction of VTH. The negative shift of VTH is serious at the first 10s and then changes slightly with the following stress time. However, different phenomenon is observed when VDS reduces to -5V. VTH shifts negatively during stress condition, and the variation in VTH increases with time, which is different from that when VDS is 0V. Two mechanisms exists in this condition. On the one hand, the electric field in the gate region is influenced by the drain voltage, so that the trapping behavior of holes in the gate region changes. The impact of the gate voltage is weakened. On the other hand, large drain voltage can induce the hot holes generation and lead to serious hot carrier stress (HCS) degradation with time. The poor-quality interface between the oxide layer and GaN channel layer at the gate region makes a major contribution to the high-density interface traps, which will greatly influence the reliability of devices. These results emphasize that the improved etching and pretreatment processes needs to be developed so that high-performance GaN complementary logics with enhanced stability can be achieved.

Keywords: GaN-based E-mode p-HFETs, dynamic electric stress, threshold voltage, monolithic power integration technology

Procedia PDF Downloads 79

Authors: Rui Tu, Yakui Bai, Huailin Li

Abstract:

The lead-bismuth eutectic (LBE) alloy is a promising candidate of coolant in the fast neutron reactors and accelerator-driven systems (ADS) because of its good properties, such as low melting point, high neutron yields and high thermal conductivity. Although the corrosion of the structure materials caused by the liquid metal (LM) coolant is a challenge to the safe operating of a lead-bismuth eutectic nuclear reactor. Thermodynamic theories, experiential formulas and experimental data can be used for explaining the maintenance of the protective oxide layers on stainless steels under satisfaction oxygen concentration, but the atomic scale insights of such anti-corrosion mechanisms are little known. In the present work, the first-principles calculations are carried out to study the effects of oxygen partial pressure on the formation energies of the liquid metal coolant relevant impurity defects in the anti-corrosion oxide films on the surfaces of the structure materials. These approaches reveal the microscope mechanisms of the corrosion of the structure materials, especially for the influences from the oxygen partial pressure. The results are helpful for identifying a crucial oxygen concentration for corrosion control, which can ensure the systems to be operated safely under certain temperatures.

Keywords: oxygen partial pressure, liquid metal coolant, TDDFT, anti-corrosion layer, formation energy

Procedia PDF Downloads 121

Authors: Yasunori Kobori, Murong Li, Feng Zhao, Shu Wu, Nobukazu Takai, Haruo Kobayashi

Abstract:

This paper proposes an electrolytic capacitor-less transformer-less AC-DC LED driver with a current ripple canceller. The proposed LED driver includes a diode bridge, a buck-boost converter, a negative feedback controller and a current ripple cancellation circuit. The current ripple canceller works as a bi-directional current converter using a sub-inductor, a sub-capacitor and two switches for controlling current flow. LED voltage is controlled in order to regulate LED current by the negative feedback controller using a current sense resistor. There are two capacitors with capacitance of 5 uF. We describe circuit topologies, operation principles and simulation results for our proposed circuit. In addition, we show the line regulation for input voltage variation from 85V to 130V. The output voltage ripple is 2V and the LED current ripple is 65 mA which is less than 20% of the average of LED current of 350 mA.

Keywords: DC-DC buck converter, four-level output voltage, single inductor multi output (SIMO), switching converter

Procedia PDF Downloads 539

Authors: G. Dan Chépo, L. Ban-Koffi, N. Kouassi Kouakou, M. Dje Kouakou, J. Nemlin, A. Sahore Drogba, L. Kouame Patrice

Abstract:

Solanum anguivi Lam, collectively called Gnagnan in Côte d'Ivoire is an eggplant with nutritional and therapeutic potentialities more or less known. The present study was undertaken to analyze the biochemical composition of berries at the different stages of maturity. Data showed that at the first stage of maturity (green berries), fruits are rich in ascorbic acid (34.48 ± 1.7 mg / 100 g dm), phenolic compounds (956.7 ± 71.14 mg / 100 g dm), iron (467.7 ± 1.84 mg / 100 g dm), magnesium (404.6 ± 16.25 mg / 100 g dm) and potassium (404.64 ± 16.25 mg/100 g dm). However, at the last stage of maturity (red berries), fruits are rich in proteins, cellulose, total sugars, fat and potassium with the values of 22.53 ± 2 g/100 g dm, 19.12 ± 0.35 g/100 g dm, 3.7 ± 0.2 g/100 g dm, 2.65 ± 0.19 g/100 g dm and 2290.84 ± 22.24 mg / 100 g dm, respectively. The chromatography on thin layer revealed the presence of glucose, ribose, xylose, arabinose and fructose at all the maturity stages. Except for alkaloids and gallic tannins, the phytochemical sorting revealed that Gnagnan contain many pharmacological components. According to the maturity stages, orange and red berries showed a higher content in sterols and polyterpens, flavonoids and saponins. The green berries contain most of polyphenols, catechintannins and quinons. As for the yellow berries, they are rich in polyphenols and catechintannins. These data contribute to enhance clinical researches on nutritional and pharmacological properties of S. anguivi Lam.

Keywords: Gnagnan, maturity stage, chemical composition, chromatography thin layer, phytochemical sorting

Procedia PDF Downloads 487

Authors: Abdelali Laamari, Morad Faiz, Ali Amamou And Mohamed Elkoudrim

Abstract:

This research seeks to develop multi-disciplinary, multi-criteria, and multi-institutional approaches that consider the three main pillars of sustainability (environmental, economic, and social aspects) at the level of decision making regarding the adoption of improved technologies in the targeted case study region in Morocco. The study is aimed at combining sound R&I with extensive skills in applied research and policy evaluation. The intention is to provide new simple, and transferable tools and agricultural practices that will enable the uptake of sustainability and the resiliency of agro-ecosystems. The study will understand the state-of-the-art of the impact of climate change and identify the core bottlenecks and climate change’s impact on crop and livestock productivity of the targeted value chains in Morocco. Studies conducted during 2021-2022 showed that most of the farmers are using since 2010 the direct seeding and the system can be improved by adopting new fertilizer and varieties of wheat. The alley-cropping technology is based on Atriplex plant or olive trees. The introduction of new varieties of oat and quinoa has improved biomass and grain production in a dry season. The research is targeting other issues, such as social enterprises, to diversify women’s income resources and create new job opportunities through diversification of end uses of durum wheat and barley grains. Women’s local knowledge is rich on the different end uses of durum and barley grains that can improve their added value if they are transformed as couscous, pasta, or any other products.

Keywords: agriculture, climate, production system, integration

Procedia PDF Downloads 66

Authors: Zachary Huffman, Joana Rocha

Abstract:

Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

Procedia PDF Downloads 130

Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

Abstract:

Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

Procedia PDF Downloads 70

Authors: Vaishali D. Khairnar

Abstract:

The main aim is to provide lower-latency and highly reliable communication facilities for vehicles in the automobile industry; vehicle-to-everything (V2X) communication basically intends to increase expressway road security and its effectiveness. The Ultra-Reliable Low-Latency Communications (URLLC) algorithm and cellular networks are applied in combination with Mobile Broadband (MBB). This is particularly used in express way safety-based driving applications. Expressway vehicle drivers (humans) will communicate in V2X systems using the sixth-generation (6G) communication systems which have very high-speed mobility features. As a result, we need to determine how to ensure reliable and consistent wireless communication links and improve the quality to increase channel gain, which is becoming a challenge that needs to be addressed. To overcome this challenge, we proposed a unique multi-user scheduling algorithm for ultra-massive multiple-input multiple-output (MIMO) systems using 6G. In wideband wireless network access in case of high traffic and also in medium traffic conditions, moreover offering quality-of-service (QoS) to distinct service groups with synchronized contemporaneous traffic on the highway like the Mumbai-Pune expressway becomes a critical problem. Opportunist MAC (OMAC) is a way of proposing communication across a wireless communication link that can change in space and time and might overcome the above-mentioned challenge. Therefore, a multi-user scheduling algorithm is proposed for MIMO systems using a cross-layered MAC protocol to achieve URLLC and high reliability in V2X communication.

Keywords: ultra-reliable low latency communications, vehicle-to-everything communication, multiple-input multiple-output systems, multi-user scheduling algorithm

Procedia PDF Downloads 81

Authors: Ritesh Joshi, Kishan Fuse, Gopal Zinzala, Nishit Nirmal

Abstract:

Ti-6Al-4V is a titanium alloy having high strength, low weight and corrosion resistant which is a required characteristic for a material to be used in aerospace industry. Titanium, being a hard alloy is difficult to the machine via conventional methods, so it is a call to use non-conventional processes. In present work, the effects on Ti-6Al-4V by drilling a hole of Ø 6 mm using copper (99%) electrode in Electric Discharge Machining (EDM) process is analyzed. Effect of various input parameters like peak current, pulse-on time and pulse-off time on output parameters viz material removal rate (MRR) and electrode wear rate (EWR) is studied. Multi-objective optimization technique Grey relational analysis is used for process optimization. Experiments are designed using an L9 orthogonal array. ANOVA is used for finding most contributing parameter followed by confirmation tests for validating the results. Improvement of 7.45% in gray relational grade is observed.

Keywords: ANOVA, electric discharge machining, grey relational analysis, Ti-6Al-4V

Procedia PDF Downloads 354

Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

Abstract:

Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

Procedia PDF Downloads 166

Authors: H. H. Lee, D. Y. Kim, S. W. Lee, J. H. Kim, J. H. Kim, W. Z. Oh, S. J. Choi

Abstract:

In recent years, carbon nanotubes (CNTs) have been widely employed as a sorbent for the removal of various metal ions from water due to their unique properties such as large surface area, light mass density, high porous and hollow structure, and strong interaction between the pollutant molecules and CNTs. To apply CNTs to the sorption of Cs+ from aqueous solutions, they must first be functionalized to increase their hydrophilicity and therefore, enhance their applicability to the sorption of polar and relatively low-molecular-weight species. The objective of this study is to investigate the preparation of magnetically separable multi-walled carbon nanotubes (MWCNTs-m) as a sorbents for the removal of Cs+ from aqueous solutions. The MWCNTs-m was prepared using pristine MWCNTs and iron precursor Fe(acac)3. For the selective removal of Cs+ from aqueous solutions, the MWCNTs-m was functionalized with zinc hexacyanoferrate (MWCNTs-m-ZnFC). The physicochemical properties of the synthesized sorbents were characterized with various techniques, including transmission electron microscopy (TEM), specific surface area analysis, Fourier transform-infrared (FT-IR) spectroscopy, and vibrating-sample magnetometer. The MWCNTs-m-ZnFC was found to be easily separated from aqueous solutions by using magnetic field. The MWCNTs-m-ZnFC exhibited a high capacity for sorbing Cs+ from aqueous solutions because of their strong affinity for Cs+ and specific surface area. The sorption ability of the MWCNTs-m-ZnFC for Cs+ was maintained even in the presence of co-existing ions (Na+). Considering these results, the CNT-m-ZnFCs have great potential for use as an effective sorbent for the selective removal of radioactive Cs+ ions from aqueous solutions.

Keywords: multi-walled carbon nanotubes, magnetic materials, cesium, zinc hexacyanoferrate, sorption

Procedia PDF Downloads 322

Authors: Jingjue Bao, Ye Li, Yujie Qi

Abstract:

The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

Procedia PDF Downloads 65

Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

Procedia PDF Downloads 205

Authors: S. Ramesh, A. S. Sasiraaju, K. Sidhaarth, N. Sudhan Rajkumar, V. Manivel Muralidaran

Abstract:

This work presents the result of investigations aimed at determining the hardness of the welded Chromoly (A 4130) steel plate of 2” thickness. Multi pass welding for the thick sections was carried out and analyzed for the Chromoly alloy steel plates. The study of hardness at the weld metal reveals that there is the presence of different micro structure products which yields diverse properties. The welding carried out using GMAW with ER70s-2 electrode. Single V groove design was selected for the butt joint configuration. The presence of hydrogen has been suppressed by selecting low hydrogen electrode. Preheating of the plate prior to welding reduces the cooling rate which also affects the weld metal microstructure. The shielding gas composition used in this analysis is 80% Ar-20% CO2. The experimental analysis gives the detailed study of the hardness of the material.

Keywords: chromoly, gas metal arc weld (GMAW), hardness, multi pass weld, shielding gas composition

Procedia PDF Downloads 209

Authors: Yulan Wu

Abstract:

The spread of fake news on social media has posed significant societal harm to the public and the nation, with its threats spanning various domains, including politics, economics, health, and more. News on social media often covers multiple domains, and existing models studied by researchers and relevant organizations often perform well on datasets from a single domain. However, when these methods are applied to social platforms with news spanning multiple domains, their performance significantly deteriorates. Existing research has attempted to enhance the detection performance of multi-domain datasets by adding single-domain labels to the data. However, these methods overlook the fact that a news article typically belongs to multiple domains, leading to the loss of domain knowledge information contained within the news text. To address this issue, research has found that news records in different domains often use different vocabularies to describe their content. In this paper, we propose a fake news detection framework that combines domain knowledge and expert knowledge. Firstly, it utilizes an unsupervised domain discovery module to generate a low-dimensional vector for each news article, representing domain embeddings, which can retain multi-domain knowledge of the news content. Then, a feature extraction module uses the domain embeddings discovered through unsupervised domain knowledge to guide multiple experts in extracting news knowledge for the total feature representation. Finally, a classifier is used to determine whether the news is fake or not. Experiments show that this approach can improve multi-domain fake news detection performance while reducing the cost of manually labeling domain labels.

Keywords: fake news, deep learning, natural language processing, multiple domains

Procedia PDF Downloads 62