Search results for: layer wise aggregation

Authors: L. N. A. Chandana Jayawardena, Ales Gregar

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Occupational Self Efficacy (OSE) reflects the conviction of a person’s ability to fulfill his job related behavior at a perfectly acceptable level to the employer. Transformational leadership improves followers’ commitment by influencing their needs, values, and self-esteem. Employees also develop a dyadic relationship with their immediate superiors. Study was conducted amongst one hundred and twenty two (122) bank managers in Sri Lanka. They were selected based on multi-stage (seniority in the hierarchy, gender, department-wise etc.) stratified random sampling. Major objectives of this study were to analyze the impact of transformational leadership style, and OSE along with socio-demographic factors, and career, job and organizational experience, to the career satisfaction of managers. SPSS software was used for parametric and non-parametric statistical analyses. Career satisfaction had positive impacts on their transformational leadership style, and their relationships with the immediate superior. Impact of socio-demographic factors, and career exposure to career satisfaction was assessed.

Keywords: career success, relationship with immediate superior, transformational leadership, occupational self efficacy (OSE)

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Authors: Jae-Ho Kim, Ryosuke Yokochi, Miho Fuzihashi, Susumu Yonezawa

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The use of silver nanoparticles in conductive inks and their printing by injecting technology has been known for years. However, the very high cost of silver limits wide industrial applications. Since copper is much cheaper but possesses a very high conductivity (only 6% less than that of Ag), Cu nanoparticles can be considered as a replacement for silver nanoparticles. However, a major problem in utilizing their copper nanoparticles is their inherent tendency to oxidize in ambient conditions. In conductive printing applications, the presence of copper oxide on the surface of nanoparticles has two negative consequences: it increases the required sintering temperature and reduces the electrical conductivity. Only a limited number of reports have attempted to address the oxidation problem, which in general is based on minimizing the exposure of the copper nanoparticles to oxygen by a protective layer composed of a second material at the surface of the particles. To form the protective layer on the surface, carbon-based materials, surfactants, metals, and so on. In this study, we tried to modify the oxide on Cu particles using fluorine gas. And the creation effects of oxyfluorides or fluorides on the oxidation resistance of Cu particles were investigated. Compared with untreated sample (a), the fluorinated samples can restrain the weight increase even at 200℃ from the TG-DTA results. It might be considered that the substantial oxyfluorides on the surface play a role in protecting metal oxidation.

Keywords: copper metal, electrical conductivity, oxidation resistance, surface fluorination

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Authors: Pouyan Motamedi, Ken Bosnick, Ken Cadien, James Hogan

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Growth of conformal ultrathin metal films has attracted a considerable amount of attention recently. Plasma-enhanced atomic layer deposition (PEALD) is a method capable of growing conformal thin films at low temperatures, with an exemplary control over thickness. The authors have recently reported on growth of metastable epitaxial nickel thin films via PEALD, along with a comprehensive characterization of the films and a study on the relationship between the growth parameters and the film characteristics. The goal of the current study is to use the mentioned films as a case study to investigate the temperature-activated phase transformation and agglomeration in ultrathin metallic films. For this purpose, metastable hexagonal nickel thin films were annealed using a controlled heating/cooling apparatus. The transformations in the crystal structure were observed via in-situ synchrotron x-ray diffraction. The samples were annealed to various temperatures in the range of 400-1100° C. The onset and progression of particle formation were studied in-situ via laser measurements. In addition, a four-point probe measurement tool was used to record the changes in the resistivity of the films, which is affected by phase transformation, as well as roughening and agglomeration. Thin films annealed at various temperature steps were then studied via atomic force microscopy, scanning electron microscopy and high-resolution transmission electron microscopy, in order to get a better understanding of the correlated mechanisms, through which phase transformation and particle formation occur. The results indicate that the onset of hcp-to-bcc transformation is at 400°C, while particle formations commences at 590° C. If the annealed films are quenched after transformation, but prior to agglomeration, they show a noticeable drop in resistivity. This can be attributed to the fact that the hcp films are grown epitaxially, and are under severe tensile strain, and annealing leads to relaxation of the mismatch strain. In general, the results shed light on the nature of structural transformation in nickel thin films, as well as metallic thin films, in general.

Keywords: atomic layer deposition, metastable, nickel, phase transformation, thin film

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Authors: R. Bennai, H. Ait Atmane, Jr., A. Tounsi

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In this work, a new analytical approach using a refined theory of hyperbolic shear deformation of a beam was developed to study the free vibration of graduated sandwiches beams under different boundary conditions. The effects of transverse shear strains and the transverse normal deformation are considered. The constituent materials of the beam are supposed gradually variable depending the height direction based on a simple power distribution law in terms of the volume fractions of the constituents; the two materials with which we worked are metals and ceramics. The core layer is taken homogeneous and made of an isotropic material; while the banks layers consist of FGM materials with a homogeneous fraction compared to the middle layer. Movement equations are obtained by the energy minimization principle. Analytical solutions of free vibration and buckling are obtained for sandwich beams under different support conditions; these conditions are taken into account by incorporating new form functions. In the end, illustrative examples are presented to show the effects of changes in different parameters such as (material graduation, the stretching effect of the thickness, boundary conditions and thickness ratio - length) on the vibration free and buckling of an FGM sandwich beams.

Keywords: functionally graded sandwich beam, refined shear deformation theory, stretching effect, free vibration

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Authors: Sara Kamalisiahroudi, Zhang Jianbo, Bin Wu, Jun Huang, Laisuo Su

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The temperature rising within a battery cell depends on the level of heat generation, the thermal properties and the heat transfer around the cell. The rising of temperature is a serious problem of Lithium-Ion batteries and the internal resistance of battery is the main reason for this heating up, so the heat generation rate of the batteries is an important investigating factor in battery pack design. The delivered power of a battery is directly related to its capacity, decreases in the battery capacity means the growth of the Solid Electrolyte Interface (SEI) layer which is because of the deposits of lithium from the electrolyte to form SEI layer that increases the internal resistance of the battery. In this study two identical cylindrical Lithium-Ion (NCR18650)batteries from the same company with noticeable different in capacity (a fresh and a used battery) were compared for more focusing on their heat generation parameters (entropy coefficient and internal resistance) according to Brandi model, by utilizing potentiometric method for entropy coefficient and EIS method for internal resistance measurement. The results clarify the effect of capacity difference on cell electrical (R) and thermal (dU/dT) parameters. It can be very noticeable in battery pack design for its Safety.

Keywords: heat generation, Solid Electrolyte Interface (SEI), potentiometric method, entropy coefficient

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Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

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Authors: Haolun Sun, Ping Wang, Mei Wu, Meng Zhang, Bin Hou, Ling Yang, Xiaohua Ma, Yue Hao

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Gallium nitride (GaN) is an attractive material for next-generation power devices. It is noted that the performance of GaN-based high electron mobility transistors (HEMTs) is always limited by the self-heating effect. In response to the problem, integrating devices with polycrystalline diamond (PCD) has been demonstrated to be an efficient way to alleviate the self-heating issue of the GaN-based HEMTs. Among all the heat-spreading schemes, using PCD to cap the epitaxial layer before the HEMTs process is one of the most effective schemes. Now, the mainstream method of fabricating the PCD-capped HEMTs is to deposit the diamond heat-spreading layer on the AlGaN surface, which is covered by a thin nucleation dielectric/passivation layer. To achieve the pattern etching of the diamond heat spreader and device preparation, we selected SiN as the hard mask for diamond etching, which was deposited by plasma-enhanced chemical vapor deposition (PECVD). The conventional diamond etching method first uses F-based etching to remove the SiN from the special window region, followed by using O₂/Ar plasma to etch the diamond. However, the results of the scanning electron microscope (SEM) and focused ion beam microscopy (FIB) show that there are lots of diamond pillars on the etched diamond surface. Through our study, we found that it was caused by the high roughness of the diamond surface and the existence of the overlap between the diamond grains, which makes the etching of the SiN hard mask insufficient and leaves micro-masks on the diamond surface. Thus, a cyclic etching method was proposed to solve the problem of the residual SiN, which was left in the F-based etching. We used F-based etching during the first step to remove the SiN hard mask in the specific region; then, the O₂/Ar plasma was introduced to etch the diamond in the corresponding region. These two etching steps were set as one cycle. After the first cycle, we further used cyclic etching to clear the pillars, in which the F-based etching was used to remove the residual SiN, and then the O₂/Ar plasma was used to etch the diamond. Whether to take the next cyclic etching depends on whether there are still SiN micro-masks left. By using this method, we eventually achieved the self-terminated etching of the diamond and the smooth surface after the etching. These results demonstrate that the cyclic etching method can be successfully applied to the integrated preparation of polycrystalline diamond thin films and GaN HEMTs.

Keywords: AlGaN/GaN heterojunction, O₂/Ar plasma, cyclic etching, polycrystalline diamond

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Authors: Xin Zhao

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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

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Authors: Obaid Algahtani

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An interval may be defined as a convex combination as follows: I=[a,b]={x_α=(1-α)a+αb: α∈[0,1]}. Consequently, we may adopt interval operations by applying the scalar operation point-wise to the corresponding interval points: I ∙J={x_α∙y_α ∶ αϵ[0,1],x_α ϵI ,y_α ϵJ}, With the usual restriction 0∉J if ∙ = ÷. These operations are associative: I+( J+K)=(I+J)+ K, I*( J*K)=( I*J )* K. These two properties, which are missing in the usual interval operations, will enable the extension of the usual linear system concepts to the interval setting in a seamless manner. The arithmetic introduced here avoids such vague terms as ”interval extension”, ”inclusion function”, determinants which we encounter in the engineering literature that deal with interval linear systems. On the other hand, these definitions were motivated by our attempt to arrive at a definition of interval random variables and investigate the corresponding statistical properties. We feel that they are the natural ones to handle interval systems. We will enable the extension of many results from usual state space models to interval state space models. The interval state space model we will consider here is one of the form X_((t+1) )=AX_t+ W_t, Y_t=HX_t+ V_t, t≥0, where A∈ 〖IR〗^(k×k), H ∈ 〖IR〗^(p×k) are interval matrices and 〖W 〗_t ∈ 〖IR〗^k,V_t ∈〖IR〗^p are zero – mean Gaussian white-noise interval processes. This feeling is reassured by the numerical results we obtained in a simulation examples.

Keywords: interval analysis, interval matrices, state space model, Kalman Filter

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Authors: Micheal O. Alabi

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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

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Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

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Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

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

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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

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Authors: Behnam Shakerian, Negin Razavi

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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

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

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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

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Authors: Hafida Bouarfa, Mohamed Abed

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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

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Authors: Rui Tu, Yakui Bai, Huailin Li

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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

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Authors: Nirmal Kant Singh, Anshuman Pratap Singh

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In this study the augmentation of heat transfer in a channel with delta winglet type vortex generators is evaluated. Three-dimensional numerical simulations are performed in a rectangular channel with longitudinal triangular vortex generators (LVGs). The span wise averaged Nusselt number and mean temperature are compared with and without vortex generators in the channel. The effect of variation of blade angle (15°, 30°, 45°, and 60°) is studied at a Reynolds number of 10000. The numerical results indicate that the application of LVGs effectively enhances heat transfer in the channel. The Nusselt number and mean outlet temperature were found to be greater using LVGs than in the channel without LVGs. It is observed that heat transfer increases with increase in blade angle at the same Reynolds number.

Keywords: heat transfer, rectangular channel, longitudinal vortex generators, effect of blade angle

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Authors: Istvan Szilagyi, Marko Pavlovic, Paul Rouster

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Antioxidant enzymes are the most efficient defense systems against reactive oxygen species, which cause severe damage in living organisms and industrial products. However, their supplementation is problematic due to their high sensitivity to the environmental conditions. Immobilization on carrier nanoparticles is a promising research direction towards the improvement of their functional and colloidal stability. In that way, their applications in biomedical treatments and manufacturing processes in the food, textile and cosmetic industry can be extended. The main goal of the present research was to prepare and formulate antioxidant bionanocomposites composed of superoxide dismutase (SOD) enzyme, anionic clay (layered double hydroxide, LDH) nanoparticle and heparin (HEP) polyelectrolyte. To characterize the structure and the colloidal stability of the obtained compounds in suspension and solid state, electrophoresis, dynamic light scattering, transmission electron microscopy, spectrophotometry, thermogravimetry, X-ray diffraction, infrared and fluorescence spectroscopy were used as experimental techniques. LDH-SOD composite was synthesized by enzyme immobilization on the clay particles via electrostatic and hydrophobic interactions, which resulted in a strong adsorption of the SOD on the LDH surface, i.e., no enzyme leakage was observed once the material was suspended in aqueous solutions. However, the LDH-SOD showed only limited resistance against salt-induced aggregation and large irregularly shaped clusters formed during short term interval even at lower ionic strengths. Since sufficiently high colloidal stability is a key requirement in most of the applications mentioned above, the nanocomposite was coated with HEP polyelectrolyte to develop highly stable suspensions of primary LDH-SOD-HEP particles. HEP is a natural anticoagulant with one of the highest negative line charge density among the known macromolecules. The experimental results indicated that it strongly adsorbed on the oppositely charged LDH-SOD surface leading to charge inversion and to the formation of negatively charged LDH-SOD-HEP. The obtained hybrid materials formed stable suspension even under extreme conditions, where classical colloid chemistry theories predict rapid aggregation of the particles and unstable suspensions. Such a stabilization effect originated from electrostatic repulsion between the particles of the same sign of charge as well as from steric repulsion due to the osmotic pressure raised during the overlap of the polyelectrolyte chains adsorbed on the surface. In addition, the SOD enzyme kept its structural and functional integrity during the immobilization and coating processes and hence, the LDH-SOD-HEP bionanocomposite possessed excellent activity in decomposition of superoxide radical anions, as revealed in biochemical test reactions. In conclusion, due to the improved colloidal stability and the good efficiency in scavenging superoxide radical ions, the developed enzymatic system is a promising antioxidant candidate for biomedical or other manufacturing processes, wherever the aim is to decompose reactive oxygen species in suspensions.

Keywords: clay, enzyme, polyelectrolyte, formulation

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Authors: Wen-Yan Chiau

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Taiwan passed the 'Basic Ocean Act' in November 2019, and in accordance with Article 4 of its provisions, the government should draft a decree on ocean space planning (MSP). In the past few years, although Taiwan has passed the 'Coastal Zone Management Act' and the 'Spatial Planning Act', in the face of multiple use of marine areas, it still lacks a comprehensive marine area use blueprint and a fundamental mechanism for multi-purpose use planning management. In particular, Taiwan's active development of offshore wind power is facing this problem, and it is impossible to fully reconcile the use of each domain and the public welfare through a holistic system, highlighting the urgency of the establishment of MSP system. Therefore, this article will review relevant Taiwan laws and regulations, refer to important international initiatives and experiences, and participate in the exchange of practical experience in international conference(s), and propose adequate framework, principles, procedures, and promotion strategies on MSP. Possible solutions to promote sustainable and wise use in Taiwan's waters will also be suggested for comments.

Keywords: basic ocean act, coastal zone management act, marine spatial planning, spatial planning act, Taiwan

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Authors: Imtiaz Sarwar

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Air conditioning in homes may account for one-third of the electricity during period in summer when most of the energy is required in large cities. It is not consuming only electricity but also has a serious impact on environment including greenhouse effect. Circular polarizer filter can be used to selectively absorb or pass clockwise or counter-clock wise circularly polarized light. My research is about putting two circular polarized glasses parallel to each other and make a circular window with it. When we will place two circular polarized glasses exactly same way (0 degree to each other) then nothing will be noticed rather it will work as a regular window through which all light and heat can pass on. While we will keep rotating one of the circular polarized glasses, the angle between the glasses will keep increasing and the window will keep blocking more and more lights. It will completely block all the lights and a portion of related heat when one of the windows will reach 90 degree to another. On the other hand, we can just open the window when fresh air is necessary. It will reduce the necessity of using Air condition too much or consumer will use electric fan rather than air conditioning system. Thus, we can save a significant amount of electricity and we can go green.

Keywords: circular polarizer, window, air condition, light, energy

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Authors: Thorsten Prante, Robert Schöch, Ruth Fleisch, Vaheh Khachatouri, Alexander Walch

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The development of industrial plant control software is a complex and often very expensive task. One of the core problems is that a lot of the implementation and adaptation work can only be done after the plant hardware has been installed. In this paper, we present our approach to virtually developing and validating plant-level control software of production plants. This way, plant control software can be virtually commissioned before actual ramp-up of a plant, reducing actual commissioning costs and time. Technically, this is achieved by linking the actual plant-wide process control software (often called plant server) and an elaborate virtual plant model together to form an emulation system. Method-wise, we are suggesting a four-step iterative process with well-defined increments and time frame. Our work is based on practical experiences from planning to commissioning and start-up of several cut-to-size plants.

Keywords: iterative system design, virtual plant engineering, plant control software, simulation and emulation, virtual commissioning

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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

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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

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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 135

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

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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

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Authors: M. D. Dogara, C. G, Afuwai, O. O. Esther, A. M. Dawai

Abstract:

For two decades, the inhabitants of Kujama Prison Farm faced problems of water for domestic and agricultural purposes, even after the drilling of three deep boreholes. The scarcity of this groundwater resource led to the geophysical investigation of the basement complex of the prison farm. Two geophysical techniques, vertical electrical sounding and seismic refraction methods were deployed to unravel the cause(s) of the non-productivity of the three boreholes. The area of investigation covered was 400,000 m2 of ten profiles with six investigative points. In all, 60 vertical electrical points were sounded, and sixty sets of seismic refraction data were collected using the forward and reverse approach. From the geoelectric sections, it is suggestive that the area is underlain by three to five geoelectric layers of varying thicknesses and resistivities. The result of the interpreted seismic data revealed two geovelocity layers, with velocities ranging between 478m/s to 1666m/s for the first layer and 1166m/s to 7141m/s for the second layer. From the combined results of the two techniques, it was suggestive that all the three unproductive boreholes were drilled at points that were neither weathered nor fractured. It was, therefore, suggested that new boreholes should be drilled at areas identified with depressed bedrock topography having geophysical evidence of intense weathering and fracturing within the fresh basement.

Keywords: groundwater, Kujama prison farm, kaduna, nigeria, seismic refraction, vertical electrical sounding

Procedia PDF Downloads 156

Authors: PR

Abstract:

Renewable energy is a sustainable substitute to fossil fuels, which are depleting and attributing to global warming as well as greenhouse gas emissions. Renewable energy innovations including solar, wind, and geothermal have grown significantly and play a critical role in meeting energy demands recently. Consequently, Artificial Intelligence (AI) could further enhance the benefits of renewable energy systems. The combination of renewable technologies and AI could facilitate the development of smart grids that can better manage energy distribution and storage. AI thus has the potential to optimize the efficiency and reliability of renewable energy systems, reduce costs, and improve their overall performance. The conventional methods of using smart micro-grids are to connect these micro-grids in series or parallel or a combination of series and parallel. Each of these methods has its advantages and disadvantages. In this study, the proposal of using the method of connecting microgrids in a spiral manner is investigated. One of the important reasons for choosing this type of structure is the two-way reinforcement and exchange of each inner layer with the outer and upstream layer. With this model, we have the ability to increase energy from a small amount to a significant amount based on exponential functions. The geometry used to close the smart microgrids is based on nature.This study provides an overview of the applications of algorithms and models of AI as well as its advantages and challenges in renewable energy systems.

Keywords: artificial intelligence, renewable energy sources, spiral model, optimize

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Authors: Soroush Momeni

Abstract:

Excellent damping capacity and superelasticity of the bulk NiTi shape memory alloy (SMA) makes it a suitable material of choice for tools in machining process as well as tribological systems. Although thin film of NiTi SMA has a same damping capacity as NiTi bulk alloys, it has a poor mechanical properties and undesirable tribological performance. This study aims at eliminating these application limitations for NiTi SMA thin films. In order to achieve this goal, NiTi thin films were magnetron sputtered as an interlayer between reactively sputtered hard TiCN coatings and hard work tool steel substrates. The microstructure, composition, crystallographic phases, mechanical and tribological properties of the deposited thin films were analyzed by using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), nanoindentation, ball–on-disc, scratch test, and three dimensional (3D) optical microscopy. It was found that under a specific coating architecture, the superelasticity of NiTi inter-layer can be combined with high hardness and wear resistance of TiCN protective layers. The obtained results revealed that the thickness of NiTi interlayers is an important factor controlling mechanical and tribological performance of bi-layer composite coating systems.

Keywords: PVD coatings, sliding wear, hardness, tool steel

Procedia PDF Downloads 285

Authors: Kaustav Mukherjee

Abstract:

In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

Procedia PDF Downloads 132