Search results for: entropy weighted method

Authors: Jing Lin, Zou Yiming, Goei Ronn, Li Yun, Amanda Ong Jiamin, Alfred Tok Iing Yoong

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High-entropy alloy (HEA) coatings comprise multiple (five or more) principal elements that give superior mechanical, electrical, and thermal properties. However, the current synthesis methods of HEA coating still face huge challenges in facile and controllable preparation, as well as conformal integration, which seriously restricts their potential applications. Herein, we report a controllable synthesis of conformal quinary HEA coating consisting of noble metals (Rh, Ru, Ir, Pt, and Pd) by using the atomic layer deposition (ALD) with a post-annealing approach. This approach realizes low temperature (below 200 °C), precise control (nanoscale), and conformal synthesis (over complex substrates) of HEA coating. Furthermore, the resulting quinary HEA coating shows promising potential as a platform for catalysis, exhibiting substantially enhanced electrocatalytic hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performances as compared to other noble metal-based structures such as single metal coating or multi-layered metal composites.

Keywords: high-entropy alloy, thin-film, catalysis, water splitting, atomic layer deposition

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Authors: Liang Weichien

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Without adequate information and mitigation plan for natural disaster, the risk to urban populated areas will increase in the future as populations grow, especially in Taiwan. Taiwan is recognized as the world's high-risk areas, where an average of 5.7 times of floods occur per year should seek to strengthen coherence and consensus in how cities can plan for flood and climate change. Therefore, this study aims at understanding the vulnerability to flooding in Taipei city, Taiwan, by creating indicators and calculating the vulnerability of each study units. The indicators were grouped into sensitivity and adaptive capacity based on the definition of vulnerability of Intergovernmental Panel on Climate Change. The indicators were weighted by using Principal Component Analysis. However, current researches were based on the assumption that the composition and influence of the indicators were the same in different areas. This disregarded spatial correlation that might result in inaccurate explanation on local vulnerability. The study used Geographically Weighted Principal Component Analysis by adding geographic weighting matrix as weighting to get the different main flood impact characteristic in different areas. Cross Validation Method and Akaike Information Criterion were used to decide bandwidth and Gaussian Pattern as the bandwidth weight scheme. The ultimate outcome can be used for the reduction of damage potential by integrating the outputs into local mitigation plan and urban planning.

Keywords: flood vulnerability, geographically weighted principal components analysis, GWPCA, highly urbanized area, spatial correlation

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Authors: Sanjib Kr Pal, S. Bhattacharyya

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Mixed convection of Cu-water nanofluid in an enclosure with thick wavy bottom wall has been investigated numerically. A co-ordinate transformation method is used to transform the computational domain into an orthogonal co-ordinate system. The governing equations in the computational domain are solved through a pressure correction based iterative algorithm. The fluid flow and heat transfer characteristics are analyzed for a wide range of Richardson number (0.1 ≤ Ri ≤ 5), nanoparticle volume concentration (0.0 ≤ ϕ ≤ 0.2), amplitude (0.0 ≤ α ≤ 0.1) of the wavy thick- bottom wall and the wave number (ω) at a fixed Reynolds number. Obtained results showed that heat transfer rate increases remarkably by adding the nanoparticles. Heat transfer rate is dependent on the wavy wall amplitude and wave number and decreases with increasing Richardson number for fixed amplitude and wave number. The Bejan number and the entropy generation are determined to analyze the thermodynamic optimization of the mixed convection.

Keywords: conjugate heat transfer, mixed convection, nano fluid, wall waviness

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Authors: Vera Varazashvili, Murman Tsarakhov, Tamar Mirianashvili, Teimuraz Pavlenishvili, Tengiz Machaladze, Mzia Khundadze

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Standard Gibbs energy of formation ΔGfor(298.15) of lanthanide-iron double oxides of garnet-type crystal structure R3Fe5O12 - RIG (R – are rare earth ions) from initial oxides are evaluated. The calculation is based on the data of standard entropies S298.15 and standard enthalpies ΔH298.15 of formation of compounds which are involved in the process of garnets synthesis. Gibbs energy of formation is presented as temperature function ΔGfor(T) for the range 300-1600K. The necessary starting thermodynamic data were obtained from calorimetric study of heat capacity – temperature functions and by using the semi-empirical method for calculation of ΔH298.15 of formation. Thermodynamic functions for standard temperature – enthalpy, entropy and Gibbs energy - are recommended as reference data for technological evaluations. Through the isostructural series of rare earth-iron garnets the correlation between thermodynamic properties and characteristics of lanthanide ions are elucidated.

Keywords: calorimetry, entropy, enthalpy, heat capacity, gibbs energy of formation, rare earth iron garnets

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction

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Authors: Annalakshmi G., Sakthivel Murugan S.

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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

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Authors: Zhibo Zhao, Horst Hahn, Robert Kruk, Abhisheck Sarkar

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High entropy oxides (HEOs), based on the incorporation of multiple-principal cations into the crystal lattice, offer the possibility to explore previously inaccessible oxide compositions and unconventional properties. Here it is demonstrated that despite the chemical complexity of HEOs external stimuli, such as epitaxial strain, can selectively stabilize certain magneto-electronic states. Epitaxial (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄-HEO thin films are grown in three different strain states: tensile, compressive, and relaxed. A unique coexistence of rocksalt and spinel-HEO phases, which are fully coherent with no detectable chemical segregation, is revealed by transmission electron microscopy. This dual-phase coexistence appears as a universal phenomenon in (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄ epitaxial films. Prominent changes in the magnetic anisotropy and domain structure highlight the strain-induced bidirectional control of magnetic properties in HEOs. When the films are relaxed, their magnetization behavior is isotropic, similar to that of bulk materials. However, under tensile strain, the hardness of the out-of-plane (OOP) axis increases significantly. On the other hand, compressive straining results in an easy OOP magnetization and a maze-like magnetic domain structure, indicating perpendicular magnetic anisotropy. Generally, this study emphasizes the adaptability of the high entropy design strategy, which, when combined with coherent strain engineering, opens additional prospects for fine-tuning properties in oxides.

Keywords: high entropy oxides, thin film, strain tuning, perpendicular magnetic anistropy

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Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Meetty Tomy, Arxhana G Thosar

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This paper provides the implementation of optimal control for an armature-controlled DC motor. The selection of error weighted Matrix and control weighted matrix in order to implement optimal control theory for improving the dynamic behavior of DC motor is presented. The closed loop performance of Armature controlled DC motor with derived linear optimal controller is then evaluated for the transient operating condition (starting). The result obtained from MATLAB is compared with that of PID controller and simple closed loop response of the motor.

Keywords: optimal control, DC motor, performance index, MATLAB

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Feng Guolin, Gong Zhiqiang

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In order to study the spatial structure and dynamical mechanism of extreme precipitation in East Asia, a corresponding climate network is constructed by employing the method of event synchronization. It is found that the area of East Asian summer extreme precipitation can be separated into two regions: one with high area weighted connectivity receiving heavy precipitation mostly during the active phase of the East Asian Summer Monsoon (EASM), and another one with low area weighted connectivity receiving heavy precipitation during both the active and the retreat phase of the EASM. Besides，a way for the prediction of extreme precipitation is also developed by constructing a directed climate networks. The simulation accuracy in East Asia is 58% with a 0-day lead, and the prediction accuracy is 21% and average 12% with a 1-day and an n-day (2≤n≤10) lead, respectively. Compare to the normal EASM year, the prediction accuracy is lower in a weak year and higher in a strong year, which is relevant to the differences in correlations and extreme precipitation rates in different EASM situations. Recognizing and identifying these effects is good for understanding and predicting extreme precipitation in East Asia.

Keywords: synchronization, climate network, prediction, rainfall

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Authors: Ismail Al-Yahmadi, Abbasher Gismelseed, Fatma Al-Mammari, Ahmed Al-Rawas, Ali Yousif, Imaddin Al-Omari, Hisham Widatallah, Mohamed Elzain

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The influence of Fe-doping on the structural, magnetic and magnetocaloric properties of Nd₀.₆Sr₀.₄FeₓMn₁₋ₓO₃ (0≤ x ≤0.5) were investigated. The samples were synthesized by auto-combustion Sol-Gel method. The phase purity, crystallinity, and the structural properties for all prepared samples were examined by X-ray diffraction. XRD refinement indicates that the samples are crystallized in the orthorhombic single-phase with Pnma space group. Temperature dependence of magnetization measurements under a magnetic applied field of 0.02 T reveals that the samples with (x=0.0, 0.1, 0.2 and 0.3) exhibit a paramagnetic (PM) to ferromagnetic (FM) transition with decreasing temperature. The Curie temperature decreased with increasing Fe content from 256 K for x =0.0 to 80 K for x =0.3 due to increasing of antiferromagnetic superexchange (SE) interaction coupling. Moreover, the magnetization as a function of applied magnetic field (M-H) curves was measured at 2 K, and 300 K. the results of such measurements confirm the temperature dependence of magnetization measurements. The magnetic entropy change|∆SM | was evaluated using Maxwell's relation. The maximum values of the magnetic entropy change |-∆SMax |for x=0.0, 0.1, 0.2, 0.3 are found to be 15.35, 5.13, 3.36, 1.08 J/kg.K for an applied magnetic field of 9 T. Our result on magnetocaloric properties suggests that the parent sample Nd₀.₆Sr₀.₄MnO₃ could be a good refrigerant for low-temperature magnetic refrigeration.

Keywords: manganite perovskite, magnetocaloric effect, X-ray diffraction, relative cooling power

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Authors: Amar Partap Singh Pharwaha, Balkrishan Jindal

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In this paper, a new method is developed for hiding image in a digital image with multilayer security. In the proposed method, the secret image is encrypted in the first instance using a flexible matrix based symmetric key to add first layer of security. Then another layer of security is added to the secret data by encrypting the ciphered data using Pythagorean Theorem method. The ciphered data bits (4 bits) produced after double encryption are then embedded within digital image in the spatial domain using Least Significant Bits (LSBs) substitution. To improve the image quality of the stego-image, an improved form of pixel adjustment process is proposed. To evaluate the effectiveness of the proposed method, image quality metrics including Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), entropy, correlation, mean value and Universal Image Quality Index (UIQI) are measured. It has been found experimentally that the proposed method provides higher security as well as robustness. In fact, the results of this study are quite promising.

Keywords: Pythagorean theorem, pixel adjustment, ciphered data, image hiding, least significant bit, flexible matrix

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Authors: Mario Alejandro Grisales, M. Daniela Chimá, Gilberto Bejarano Gaitán

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High entropy alloys (HEA) and nitride (HEN) are currently very attractive to the automotive, aerospace, metalworking and materials forming manufacturing industry, among others, for exhibiting higher mechanical properties, wear resistance, and thermal stability than binary and ternary alloys. In this work medium-entropy coatings of TiTaZrNb and the nitrides of (TiTaZrNb)Nx were synthesized on to AISI 420 and M2 steel samples by the direct current magnetron sputtering technique. The influence of the bias voltage supplied to the substrate on the microstructure, chemical- and phase composition of the matrix coating was evaluated, and the effect of nitrogen flow on the microstructural, mechanical and tribological properties of the corresponding nitrides was studied. A change in the crystalline structure from BCC for TiTaZrNb coatings to FCC for (TiTaZrNb)Nx was observed, that is associated with the incorporation of nitrogen into the matrix and the consequent formation of a solid solution of (TiTaZrNb)Nx. An increase in hardness and residual stresses was observed with increasing bias voltage for TiTaZrNb, reaching 12.8 GPa for the coating deposited with a bias of -130V. In the case of (TiTaZrNb)Nx nitride, a greater hardness of 23 GPa is achieved for the coating deposited with a N2 flow of 12 sccm, which slightly drops to 21.7 GPa for that deposited with N2 flow of 15 sccm. The slight reduction in hardness could be associated with the precipitation of the TiN and ZrN phases that are formed at higher nitrogen flows. The specific wear rate of the deposited coatings ranged between 0.5xexp13 and 0.6xexp13 N/m2. The steel substrate exhibited an average hardness of 2.0 GPa and a specific wear rate of 203.2exp13 N/m2. Both the hardness and the specific wear rate of the synthesized nitride coatings were higher than that of the steel substrate, showing a protective effect of the steel against wear.

Keywords: medium entropy coatings, hard coatings, magnetron sputtering, tribology, wear resistance

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Authors: Prangya P. Sahoo, B. S. Murty

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The present study deals with phase evolution of oxide dispersed CoCrFeMnNi high entropy alloy as a function of amount of added Y2O3 during mechanical alloying and analysis of grain growth kinetics of CoCrFeMnNi high entropy alloy without and with oxide dispersion. Mechanical alloying of CoCrFeMnNi resulted in a single FCC phase. However, evolution of chromium carbide was observed after heat treatment between 1073 and 1473 K. Comparison of grain growth time exponents and activation energy barrier is also reported. Micro structural investigations, using electron microscopy and EBSD techniques, were carried out to confirm the enhanced grain growth resistance which is attributed to the presence oxide dispersoids.

Keywords: grain growth kinetics, mechanical alloying, oxide dispersion, phase evolution

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Authors: Burçak Boztemur, Yue Xu, Laima Luo, M. Lütfi Öveçoğlu, Duygu Ağaoğulları

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Tungsten (W) is used chiefly as plasma-facing material. However, it has some problems, such as brittleness after plasma exposure. High-entropy alloys (RHEAs) are a new opportunity for this deficiency. So, the neutron shielding behavior of WNbMoVTa and WNbMoVTaCr₀.₅Al compositions were examined against He⁺ irradiation in this study. The mechanical and irradiation properties of the WNbMoVTa base composition were investigated by adding the Al and Cr elements. The mechanical alloying (MA) for 6 hours was applied to obtain RHEA powders. According to the X-ray diffraction (XRD) method, the body-centered cubic (BCC) phase and NbTa phase with a small amount of WC impurity that comes from vials and balls were determined after 6 h MA. Also, RHEA powders were consolidated with the spark plasma sintering (SPS) method (1500 ºC, 30 MPa, and 10 min). After the SPS method, (Nb,Ta)C and W₂C₀.₈₅ phases were obtained with the decomposition of WC and stearic acid that is added during MA based on XRD results. Also, the BCC phase was obtained for both samples. While the Al₂O₃ phase with a small intensity was seen for the WNbMoVTaCr₀.₅Al sample, the Ta₂VO₆ phase was determined for the base sample. These phases were observed as three different regions according to scanning electron microscopy (SEM). All elements were distributed homogeneously on the white region by measuring an electron probe micro-analyzer (EPMA) coupled with a wavelength dispersive spectroscope (WDS). Also, the grey region of the WNbMoVTa sample was rich in Ta, V, and O elements. However, the amount of Al and O elements was higher for the grey region of the WNbMoVTaCr₀.₅Al sample. The high amount of Nb, Ta, and C elements were determined for both samples. Archimedes’ densities that were measured with alcohol media were closer to the theoretical densities of RHEAs. These values were important for the microhardness and irradiation resistance of compositions. While the Vickers microhardness value of the WNbMoVTa sample was measured as ~11 GPa, this value increased to nearly 13 GPa with the WNbMoVTaCr₀.₅Al sample. These values were compatible with the wear behavior. The wear volume loss was decreased to 0.16×10⁻⁴ from 1.25×10⁻⁴ mm³ by the addition of Al and Cr elements to the WNbMoVTa. The He⁺ irradiation was conducted on the samples to observe surface damage. After irradiation, the XRD patterns were shifted to the left because of defects and dislocations. He⁺ ions were infused under the surface, so they created the lattice expansion. The peak shifting of the WNbMoVTaCr₀.₅Al sample was less than the WNbMoVTa base sample, thanks to less impact. A small amount of fuzz was observed for the base sample. This structure was removed and transformed into a wavy structure with the addition of Cr and Al elements. Also, the deformation hardening was actualized after irradiation. A lower amount of hardening was obtained with the WNbMoVTaCr₀.₅Al sample based on the changing microhardness values. The surface deformation was decreased in the WNbMoVTaCr₀.₅Al sample.

Keywords: refractory high entropy alloy, microhardness, wear resistance, He⁺ irradiation

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Abolfazl Hedayatipoor, Mohammad Younesi Alamooti

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In order to study the effect of conservative tillage on a number of physical properties of soil and the yield of rainfed wheat, an experiment in the form of a randomized complete block design (RCBD) with three replications was conducted in a field in Aliabad County, Iran. The study treatments included: T1) Conventional method, T2) Combined moldboard plow method, T3) Chisel-packer method, and T4) Direct planting method. During early October, the study soil was prepared based on these treatments in a field which was used for rainfed wheat farming in the previous year. The apparent specific gravity of soil, weighted mean diameter (WMD) of soil aggregates, soil mechanical resistance, and soil permeability were measured. Data were analyzed in MSTAT-C. Results showed that the tillage practice had no significant effect on grain yield (p < 0.05). Soil permeability was 10.9, 16.3, 15.7 and 17.9 mm/h for T1, T2, T3 and T4, respectively.

Keywords: rainfed agriculture, conservative tillage, energy consumption, wheat

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Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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Authors: Aleksander Mendoza

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Glushkov's construction has many interesting properties, and they become even more evident when applied to transducers. This article strives to show the vast range of possible extensions and optimisations for this algorithm. Special flavour of regular expressions is introduced, which can be efficiently converted to e-free functional subsequential weighted finite state transducers. Produced automata are very compact, as they contain only one state for each symbol (from input alphabet) of original expression and only one transition for each range of symbols, no matter how large. Such compactified ranges of transitions allow for efficient binary search lookup during automaton evaluation. All the methods and algorithms presented here were used to implement open-source compiler of regular expressions for multitape transducers.

Keywords: weighted automata, transducers, Glushkov, follow automata, regular expressions

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Authors: Liang Liu, Xiaopeng Luo

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In this paper, we propose an accelerated stochastic gradient method with momentum. The momentum term is the weighted average of generated gradients, and the weights decay inverse proportionally with the iteration times. Stochastic gradient descent with momentum (SGDM) uses weights that decay exponentially with the iteration times to generate the momentum term. Using exponential decay weights, variants of SGDM with inexplicable and complicated formats have been proposed to achieve better performance. However, the momentum update rules of our method are as simple as that of SGDM. We provide theoretical convergence analyses, which show both the exponential decay weights and our inverse proportional decay weights can limit the variance of the parameter moving directly to a region. Experimental results show that our method works well with many practical problems and outperforms SGDM.

Keywords: exponential decay rate weight, gradient descent, inverse proportional decay rate weight, momentum

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Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: Attallah Bilal, Hendel Fatiha

Abstract:

This paper proposes the bimodal biometrics system for identity verification iris and fingerprint, at matching score level architecture using weighted sum of score technique. The features are extracted from the pre processed images of iris and fingerprint. These features of a query image are compared with those of a database image to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on CASIA database and gives an overall accuracy of 91.04% with FAR of 2.58% and FRR of 8.34%.

Keywords: iris, fingerprint, sum rule, fusion

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Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

Abstract:

In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

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Authors: Leila Keshavarz Afshar, Hedieh Sajedi

Abstract:

Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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Authors: Lorena Mihelac, Janez Povh

Abstract:

In 2017, we conducted a research study using data consisting of 160 musical excerpts from different musical styles, to analyze the impact of entropy of the harmony on the acceptability of music. In measuring the entropy of harmony, we were interested in unigrams (individual chords in the harmonic progression) and bigrams (the connection of two adjacent chords). In this study, it has been found that 53 musical excerpts out from 160 were evaluated by participants as very complex, although the entropy of the harmonic progression (unigrams and bigrams) was calculated as low. We have explained this by particularities of chord progression, which impact the listener's feeling of complexity and acceptability. We have evaluated the same data twice with new participants in 2018 and with the same participants for the third time in 2019. These three evaluations have shown that the same 53 musical excerpts, found to be difficult and complex in the study conducted in 2017, are exhibiting a high feeling of complexity again. It was proposed that the content of these musical excerpts, defined as “irregular,” is not meeting the listener's expectancy and the basic perceptual principles, creating a higher feeling of difficulty and complexity. As the “irregularities” in these 53 musical excerpts seem to be perceived by the participants without being aware of it, affecting the pleasantness and the feeling of complexity, they have been defined as “subliminal irregularities” and the 53 musical excerpts as “irregular.” In our recent study (2019) of the same data (used in previous research works), we have proposed a new measure of the complexity of harmony, “regularity,” based on the irregularities in the harmonic progression and other plausible particularities in the musical structure found in previous studies. We have in this study also proposed a list of 10 different particularities for which we were assuming that they are impacting the participant’s perception of complexity in harmony. These ten particularities have been tested in this paper, by extending the analysis in our 53 irregular musical excerpts from harmony to melody. In the examining of melody, we have used the computational model “Information Dynamics of Music” (IDyOM) and two information-theoretic measures: entropy - the uncertainty of the prediction before the next event is heard, and information content - the unexpectedness of an event in a sequence. In order to describe the features of melody in these musical examples, we have used four different viewpoints: pitch, interval, duration, scale degree. The results have shown that the texture of melody (e.g., multiple voices, homorhythmic structure) and structure of melody (e.g., huge interval leaps, syncopated rhythm, implied harmony in compound melodies) in these musical excerpts are impacting the participant’s perception of complexity. High information content values were found in compound melodies in which implied harmonies seem to have suggested additional harmonies, affecting the participant’s perception of the chord progression in harmony by creating a sense of an ambiguous musical structure.

Keywords: entropy and information content, harmony, subliminal (ir)regularity, IDyOM

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Authors: Zhihui Liu, Dongmei Hao, Qian Qiu, Yang An, Lin Yang, Song Zhang, Yimin Yang, Xuwen Li, Dingchang Zheng

Abstract:

Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor.

Keywords: electrohysterogram, feature, preterm labor, term labor

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Authors: Mahdad M’hamed, Belaidi Idir

Abstract:

This paper develops a meshless approach, called Element Free Galerkin (EFG) method, which is based on the weak form Moving Least Squares (MLS) of the partial differential governing equations and employs the interpolation to construct the meshless shape functions. The variation weak form is used in the EFG where the trial and test functions are approximated bye the MLS approximation. Since the shape functions constructed by this discretization have the weight function property based on the randomly distributed points, the essential boundary conditions can be implemented easily. The local weak form of the partial differential governing equations is obtained by the weighted residual method within the simple local quadrature domain. The spline function with high continuity is used as the weight function. The presently developed EFG method is a truly meshless method, as it does not require the mesh, either for the construction of the shape functions, or for the integration of the local weak form. Several numerical examples of two-dimensional static structural analysis are presented to illustrate the performance of the present EFG method. They show that the EFG method is highly efficient for the implementation and highly accurate for the computation. The present method is used to analyze the static deflection of beams and plate hole

Keywords: numerical computation, element-free Galerkin (EFG), moving least squares (MLS), meshless methods

Procedia PDF Downloads 268