Search results for: Random Kernel Density

Authors: Alireza Dadkhah

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A filed experiment was done to develop management practices to reduce the use of synthetic herbicides, in the arid and semi-arid agricultural ecosystems of north east of Iran. Five treatments including I: chopped residues of canola (Brasica vulgaris), II: chopped residues of wheat (Triticum aestivum) both were separately incorporated to 25 cm depth soil, 20 days before sowing, III: shoot aqueous extract of canola, IV: shoot aqueous extract of wheat which were separately sprayed at post emergence stage and V: without any residues and spraying as control. The weed control treatments reduced the total weed cover, weed density and biomass of weed. The reduction in weed density with canola and wheat residues incorporation were up to 67.5 and 62.2% respectively, at 40 days after sowing and 65.3% and 75.6%, respectively, at 90 days after sowing, compared to control. However, post emergence spraying of shoot aqueous extract of canola and wheat, suppressed weed density up to 41.8 and 36.6% at 40 days after sowing and 54.2% and 52.7% at 90 days after sowing respectively, compared to control. Weed control treatments reduced weed cover (%), weed biomass and weeds stem length. Incorporation of canola and wheat residues in soil reduced weed cover (%) by 62.5% and 63% respectively, while spraying of shoot water extract of canola and wheat suppressed weed cover (%) by 39.6% and 40.4% respectively at 90 days after sowing. Application of canola and wheat residues increased soybean yield by 45.4% and 69.5% respectively, compared to control while post emergence application of shoot aqueous extract of canola and wheat increased soybean yield by 22% and 29.8% respectively.

Keywords: allelopathy, Bio-herbicide, Brassica oleracea, plant residues, Triticum aestivum

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Authors: Yang Yi-Fei, Luo Min-Zhou, Zhang Fu-Chun, He Nai-Bao, Xing Shao-Bang

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This paper presents an electromagnetic finite element model of permanent magnet synchronous linear motor and distortion rate of the air gap flux density waveform is analyzed in detail. By designing the sample space of the parameters, nonlinear regression modeling of the orthogonal experimental design is introduced. We put forward for possible air gap flux density waveform sine electromagnetic scheme. Parameters optimization of the permanent magnet synchronous linear motor is also introduced which is based on chaotic search and adaptation function. Simulation results prove that the pole shifting does not affect the motor back electromotive symmetry based on the structural parameters, it provides a novel way for the optimum design of permanent magnet synchronous linear motor and other engineering.

Keywords: permanent magnet synchronous linear motor, finite element analysis, chaotic search, optimization design

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Authors: Wei-Kuang Liu, Ya-Hsu Chiang

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In the coming of an aging society, the issues of living quality, health care, and social security for the elderly have been gradually taken seriously. In order to maintain favorable living condition, urban societies are also facing the challenge of disasters caused by extreme climate change. However, in the practice of disaster prevention, elderly people are always weak due to their physiological conditions. That is to say, in the planning of resilient urbanism, the aging society is relatively in need of more care. Thus, this research aims to map areas where have high-density elderly population and fragile environmental condition in Taiwan, and to understand the actual situation of disaster prevention management in these areas, so as to provide suggestions for the development of intellectual resilient urban management. The research takes the cities of Taoyuan and Taichung as examples for explorations. According to GIS mapping of areas with high aging index, high-density population and high flooding potential, the communities of Sihai and Fuyuan in Taoyuan and the communities of Taichang and Nanshih in Taichung are highlighted. In these communities, it can be found that there are more elderly population and less labor population with high-density living condition. In addition, they are located in the areas where they have experienced severe flooding in the recent past. Based on a series of interviews with community organizations, there is only one community out of the four using flood information mobile app and Line messages for the management of disaster prevention, and the others still rely on the traditional approaches that manage the works of disaster prevention by their community security patrol teams and community volunteers. The interview outcome shows that most elderly people are not interested in learning the use of intellectual devices. Therefore, this research suggests to keep doing the GIS mapping of areas with high aging index, high-density population and high flooding potential for grasping the high-risk communities and to help develop smart monitor and forecast systems for disaster prevention practice in these areas. Based on case-study explorations, the research also advises that it is important to develop easy-to-use bottom-up and two-way immediate communication mechanism for the management of aging society’s disaster prevention.

Keywords: aging society, disaster prevention, GIS, resilient, Taiwan

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Authors: L. Foudia, K. Haddadi, M. Reffas

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First principles study of structural, elastic, electronic and optical properties of the monoclinic perovskite type ScRhO₃ has been reported using the pseudo-potential plane wave method within the local density approximation. The calculated lattice parameters, including the lattice constants and angle β are in excellent agreement with the available experimental data, which proving the reliability of the chosen theoretical approach. Pressure dependence up to 20 GPa of the single crystal and polycrystalline elastic constants has been investigated in details using the strain-stress approach. The mechanical stability, ductility, average elastic wave velocity, Debye temperature and elastic anisotropy were also assessed. Electronic band structure and density of states (DOS) demonstrated its semiconducting nature showing a direct band gap of 1.38 eV. Furthermore, several optical properties, such as absorption coefficient, reflectivity, refractive index, dielectric function, optical conductivity and electron energy loss function have been calculated for radiation up to 40 eV.

Keywords: ab-initio, perovskite, DFT, band gap.

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Authors: Mukesh Kumar Shah, Tushar Gupta

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An Upgraded Cuckoo Search Algorithm is proposed here to solve optimization problems based on the improvements made in the earlier versions of Cuckoo Search Algorithm. Short comings of the earlier versions like slow convergence, trap in local optima improved in the proposed version by random initialization of solution by suggesting an Improved Lambda Iteration Relaxation method, Random Gaussian Distribution Walk to improve local search and further proposing Greedy Selection to accelerate to optimized solution quickly and by “Study Nearby Strategy” to improve global search performance by avoiding trapping to local optima. It is further proposed to generate better solution by Crossover Operation. The proposed strategy used in algorithm shows superiority in terms of high convergence speed over several classical algorithms. Three standard algorithms were tested on a 6-generator standard test system and the results are presented which clearly demonstrate its superiority over other established algorithms. The algorithm is also capable of handling higher unit systems.

Keywords: economic dispatch, gaussian selection operator, prohibited operating zones, ramp rate limits

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Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: Nishaben Dholakiya, Anirban Roy, Ranjan Dey

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The unprecedented rise in global temperatures has triggered complex changes in marine ecosystems, necessitating a deeper understanding of seawater's thermophysical properties by experimentally measuring ultrasonic velocity and density at varying temperatures and salinity. This study investigates the critical relationship between temperature variations and molecular-level interactions in Arabian Sea surface waters, specifically focusing on internal pressure (π) and cohesion energy density (CED) as key indicators of ecosystem disruption. Our experimental findings reveal that elevated temperatures significantly reduce internal pressure, weakening the intermolecular forces that maintain seawater's structural integrity. This reduction in π correlates directly with decreased habitat stability for marine organisms, particularly affecting pressure-sensitive species and their physiological processes. Similarly, the observed decline in cohesion energy density at higher temperatures indicates a fundamental shift in water molecule organization, impacting the dissolution and distribution of vital nutrients and gases. These molecular-level changes cascade through the ecosystem, affecting everything from planktonic organisms to complex food webs. By employing advanced machine learning techniques, including Stacked Ensemble Machine Learning (SEML) and AdaBoost (AB), we developed highly accurate predictive models (>99% accuracy) for these thermophysical parameters. The results provide crucial insights into the mechanistic relationship between climate warming and marine ecosystem degradation, offering valuable data for environmental policymaking and conservation strategies. The novelty of this research serves as no such thermodynamic investigation has been conducted before in literature, whereas this research establishes a quantitative framework for understanding how molecular-level changes in seawater properties directly influence marine ecosystem stability, emphasizing the urgent need for climate change mitigation efforts.

Keywords: thermophysical properties, Arabian Sea, internal pressure, cohesion energy density, machine learning

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Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Ameni Mahmoudi, Manel Troudi, Paolo Bondavalli, Nabil Sghaier

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In this study, the charge storage on thin-film SWCNT transistors was investigated, and C-V hysteresis tests showed that interface charge trapping effects predominate the memory window. Two electrode materials were utilized to demonstrate that selecting the appropriate metal electrode clearly improves the conductivity and, consequently, the SWCNT thin-film’s memory effect. Because their work function is similar to that of thin-film carbon nanotubes, Ti contacts produce higher charge confinement and show greater charge storage than Pd contacts. For Pd-contact CNTFETs and CNTFETs with Ti electrodes, a sizable clockwise hysteresis window was seen in the dual sweep circle with a threshold voltage shift of V11.52V and V9.7V, respectively. The SWCNT thin-film based transistor is expected to have significant trapping and detrapping charges because of the large C-V hysteresis. We have found that the predicted stored charge density for CNTFETs with Ti contacts is approximately 4.01×10-2C.m-2, which is nearly twice as high as the charge density of the device with Pd contacts. We have shown that the amount of trapped charges can be changed by sweeping the range or Vgs rate. We also looked into the variation in the flat band voltage (V FB) vs. time in order to determine the carrier retention period in CNTFETs with Ti and Pd electrodes. The outcome shows that memorizing trapped charges is about 300 seconds, which is a crucial finding for memory function mimicking.

Keywords: charge storage, thin-film SWCNT based transistors, C-V hysteresis, memory effect, trapping and detrapping charges, stored charge density, the carrier retention time

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Authors: Maria Bercea, Bernhard A. Wolf

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The thermodynamic behavior for solutions of poly (methyl methacrylate-ran-t-butyl methacrylate) of variable composition as compared with the corresponding homopolymers was investigated by light scattering measurements carried out for dilute solutions and vapor pressure measurements of concentrated solutions. The complex dependencies of the Flory Huggins interaction parameter on concentration and copolymer composition in solvents of different polarity (toluene and chloroform) can be understood by taking into account the ability of the polymers to rearrange in a response to changes in their molecular surrounding. A recent unified thermodynamic approach was used for modeling the experimental data, being able to describe the behavior of the different solutions by means of two adjustable parameters, one representing the effective number of solvent segments and another one accounting for the interactions between the components. Thus, it was investigated how the solvent quality changes with the composition of the copolymers through the Gibbs energy of mixing as a function of polymer concentration. The largest reduction of the Gibbs energy at a given composition of the system was observed for the best solvent. The present investigation proves that the new unified thermodynamic approach is a general concept applicable to homo- and copolymers, independent of the chain conformation or shape, molecular and chemical architecture of the components and of other dissimilarities, such as electrical charges.

Keywords: random copolymers, Flory Huggins interaction parameter, Gibbs energy of mixing, chemical architecture

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Authors: Newroz Nooralddin Abdulrazaq, Thuraya Mahmood Qaradaghi

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The McEliece cryptosystem is an asymmetric type of cryptography based on error correction code. The classical McEliece used irreducible binary Goppa code which considered unbreakable until now especially with parameter [1024, 524, and 101], but it is suffering from large public key matrix which leads to be difficult to be used practically. In this work Irreducible and Separable Goppa codes have been introduced. The Irreducible and Separable Goppa codes used are with flexible parameters and dynamic error vectors. A Comparison between Separable and Irreducible Goppa code in McEliece Cryptosystem has been done. For encryption stage, to get better result for comparison, two types of testing have been chosen; in the first one the random message is constant while the parameters of Goppa code have been changed. But for the second test, the parameters of Goppa code are constant (m=8 and t=10) while the random message have been changed. The results show that the time needed to calculate parity check matrix in separable are higher than the one for irreducible McEliece cryptosystem, which is considered expected results due to calculate extra parity check matrix in decryption process for g2(z) in separable type, and the time needed to execute error locator in decryption stage in separable type is better than the time needed to calculate it in irreducible type. The proposed implementation has been done by Visual studio C#.

Keywords: McEliece cryptosystem, Goppa code, separable, irreducible

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Showkat Ahmad Lone, Ahmadur Rahman, Ariful Islam

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The major assumption in accelerated life tests (ALT) is that the mathematical model relating the lifetime of a test unit and the stress are known or can be assumed. In some cases, such life–stress relationships are not known and cannot be assumed, i.e. ALT data cannot be extrapolated to use condition. So, in such cases, partially accelerated life test (PALT) is a more suitable test to be performed for which tested units are subjected to both normal and accelerated conditions. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests using progressive failure-censored hybrid data with random removals. The life data of the units under test is considered to follow exponential life distribution. The removals from the test are assumed to have binomial distributions. The point and interval maximum likelihood estimations are obtained for unknown distribution parameters and tampering coefficient. An optimum test plan is developed using the D-optimality criterion. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: binomial distribution, d-optimality, multiple censoring, optimal design, partially accelerated life testing, simulation study

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Authors: Hamid Mustafa, Heather J. Huson, Adeela Ajmal, Kim Euisoo, Tad S. Sonstegard

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In this study, 67 animals, representing six different cattle breeds of Pakistan, were genotyped with the Bovine high density (777K) SNP Beadchip. These include 13 Sahiwal, 09 Red Sindhi, 13 Tharparkar, 08 Achi, 13 Cholistani and 10 Dhanni cattle breeds. Analysis of 500, 939 SNP markers revealed that the mean minor allele frequency (MAF) was 0.21, 0.22, 0.18, 0.23, 0.22 and 0.22 for Sahiwal, Red Sindhi, Tharparkar, Achi, Cholistani and Dhanni respectively. Significant differences of minor allele frequency (MAF) were observed between the indigenous Pakistani cattle population (P<0.001). Across these Pakistani cattle breeds, a common variant MAF (≥0.10 and ≤0.5) accounted for an overall estimated 75.71 % of the 500,939 SNPs and on the average 19.58 % of the markers were monomorphic. Mean observed (HO) and expected (HE) heterozygosities were 0.656 and 0.638, respectively. This primarily study of Pakistani indigenous cattle breeds indicate that this level of SNPs variation can potentially be used for genomic studies for future breeding plans and for farm animal conservation strategies.

Keywords: Pakistan, cattle, minor allele frequency, SNP, variation

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Authors: C. Chhorn, S. H. Han, S. W. Lee

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Roller-compacted concrete (RCC) has been used for decades in many pavement applications due to its economic cost and high construction speed. However, due to the lack of deep researches and experiences, this material has not been widely employed. An RCC mixture with appropriate consistency can induce high compacted density, while high density can induce good aggregate interlock and high strength. Consistency of RCC is mainly known to define its constructability. However, it was not well specified how this property may affect other properties of a constructed RCC pavement (RCCP). This study suggested the possibility of an ideal range of consistency that may provide adequate quality of RCCP. In this research, five sections of RCCP consisted of both 13 mm and 19 mm aggregate sections were investigated. The effects of consistency on compacted depth, strength, international roughness index (IRI), skid resistance are examined. From this study, a new range of consistency is suggested for RCCP application.

Keywords: compacted depth, consistency, international roughness index (IRI), pavement, roller-compacted concrete (RCC), skid resistance, strength

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Authors: Orathai Pornsunthorntawee, Wareerom Polrut, Nopphawan Phonthammachai

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In the present work, the effects of additives, including contents of the added antioxidants and type of the selected metallic stearates (either calcium stearate (CaSt) or zinc stearate (ZnSt)), on the thermal stabilities of carbon black (CB)/high density polyethylene (HDPE) compounds were studied. The results showed that the AO contents played a key role in the thermal stabilities of the CB/HDPE compounds—the higher the AO content, the higher the thermal stabilities. Although the CaSt-containing compounds were slightly superior to those with ZnSt in terms of the thermal stabilities, the remaining solid residue of CaSt after heated to the temperature of 600 °C (mainly calcium carbonate (CaCO3) as characterized by the X-ray diffraction (XRD) technique) seemed to catalyze the decomposition of CB in the HDPE-based compounds. Hence, the quantification of CB in the CaSt-containing compounds with a muffle furnace gave an inaccurate CB content—much lower than actual value. However, this phenomenon was negligible in the ZnSt-containing system.

Keywords: antioxidant, stearate, carbon black, polyethylene

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Authors: R. Khare, R. V. Gelamo, M. A. More, D. J. Late, Chandra Sekhar Rout

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Graphene emerges out as a promising material for various applications ranging from complementary integrated circuits to optically transparent electrode for displays and sensors. The excellent conductivity and atomic sharp edges of unique two-dimensional structure makes graphene a propitious field emitter. Graphene analogues of other 2D layered materials have emerged in material science and nanotechnology due to the enriched physics and novel enhanced properties they present. There are several advantages of using 2D nanomaterials in field emission based devices, including a thickness of only a few atomic layers, high aspect ratio (the ratio of lateral size to sheet thickness), excellent electrical properties, extraordinary mechanical strength and ease of synthesis. Furthermore, the presence of edges can enhance the tunneling probability for the electrons in layered nanomaterials similar to that seen in nanotubes. Here we report electron emission properties of multilayer graphene and effect of plasma (CO2, O2, Ar and N2) treatment. The plasma treated multilayer graphene shows an enhanced field emission behavior with a low turn on field of 0.18 V/μm and high emission current density of 1.89 mA/cm2 at an applied field of 0.35 V/μm. Further, we report the field emission studies of layered WS2/RGO and SnS2/RGO composites. The turn on field required to draw a field emission current density of 1μA/cm2 is found to be 3.5, 2.3 and 2 V/μm for WS2, RGO and the WS2/RGO composite respectively. The enhanced field emission behavior observed for the WS2/RGO nanocomposite is attributed to a high field enhancement factor of 2978, which is associated with the surface protrusions of the single-to-few layer thick sheets of the nanocomposite. The highest current density of ~800 µA/cm2 is drawn at an applied field of 4.1 V/μm from a few layers of the WS2/RGO nanocomposite. Furthermore, first-principles density functional calculations suggest that the enhanced field emission may also be due to an overlap of the electronic structures of WS2 and RGO, where graphene-like states are dumped in the region of the WS2 fundamental gap. Similarly, the turn on field required to draw an emission current density of 1µA/cm2 is significantly low (almost half the value) for the SnS2/RGO nanocomposite (2.65 V/µm) compared to pristine SnS2 (4.8 V/µm) nanosheets. The field enhancement factor β (~3200 for SnS2 and ~3700 for SnS2/RGO composite) was calculated from Fowler-Nordheim (FN) plots and indicates emission from the nanometric geometry of the emitter. The field emission current versus time plot shows overall good emission stability for the SnS2/RGO emitter. The DFT calculations reveal that the enhanced field emission properties of SnS2/RGO composites are because of a substantial lowering of work function of SnS2 when supported by graphene, which is in response to p-type doping of the graphene substrate. Graphene and 2D analogue materials emerge as a potential candidate for future field emission applications.

Keywords: graphene, layered material, field emission, plasma, doping

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Authors: Sabika Rafiq, Rubaida Mehmood, Sajid Hussain, Atia Iqbal

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Background and objectives: The pathogenesis of liver function abnormalities and cardiac dysfunction in hyperthyroid patients after I131 treatment is still unclear. This study aimed to determine the effects of radioiodine I131 on liver function parameters, lactate dehydrogenase (LDH) and low-density lipoproteins (LDL) before and after I131 therapy hyperthyroidism patients. Material & Methods: A total of 52 patients of hyperthyroidism recommended for I131were involved in this study with ages ranging from 12–65 years (mean age=38.6±14.8 & BMI=11.5±3.7). The significance of the differences between the results of 1st, 2nd and 3rd-time serum analysis was assessed by unpaired student’s t-test. Associations between the parameters were assessed by Spearman correlation analysis. Results: Significant variations were observed for thyroid profile free FT3 (p=0.04), FT4 (p=0.01), TSH (p=0.005) during the follow-up treatment. Before taking I131 (serum analyzed at 1st time), negative correlation of FT3 with AST (r=-0.458, p=0.032) and LDL (r=-0.454, p=0.039) were observed. During 2nd time (after stopping carbimazole), no correlation was assessed. Two months after the administration of I131 drops, a significant negative association of FT3 (r=-0.62, p=0.04) and FT4(r=-0.61, p=0.02) with ALB were observed. FT3(r=-0.82, p=0.00) & FT4 (r=-0.71, p=0.00) also showed negative correlation with LDL after I131 therapy. Whereas TSH showed significant positive association with ALB (r=0.61, p=0.01) and LDL (r=0.70, p=0.00) respectively. Conclusion: Current findings suggested that the association of TFTs with biochemical parameters in patients with goiter recommended for iodine therapy is an important diagnostic and therapeutic tool. The significant changes increased in transaminases and low-density lipoprotein levels after taking I131drops are alarming signs for heart and liver function abnormalities and warrant physicians' attention on an urgent basis.

Keywords: hyperthyroidism, carbimazole, radioiodine I131, liver functions, low-density lipoprotein

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Authors: Ruoyang Tang, Jianguo Nie

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Lateral-torsional bracing members are critical to the stability of girder systems during the construction phase of steel-concrete composite bridges, and the interaction effect of multiple girders plays an essential role in the determination of buckling load. In this paper, an investigation is conducted on the lateral-torsional buckling behavior of the steel girder system which is composed of three or four I-shaped girders and braced by solid web crossbeams. The buckling load for such girder system is comprehensively analyzed and an analytical solution is developed for uniform pressure loading conditions. Furthermore, post-buckling analysis including initial geometric imperfections is performed and parametric studies in terms of bracing density, stiffness ratio as well as the number and spacing of girders are presented in order to find the optimal bracing plans for an arbitrary girder layout. The theoretical solution of critical load on account of local buckling mode shows good agreement with the numerical results in eigenvalue analysis. In addition, parametric analysis results show that both bracing density and stiffness ratio have a significant impact on the initial stiffness, global stability and failure mode of such girder system. Taking into consideration the effect of initial geometric imperfections, an increase in bracing density between adjacent girders can effectively improve the bearing capacity of the structure, and higher beam-girder stiffness ratio can result in a more ductile failure mode.

Keywords: bracing member, construction stage, lateral-torsional buckling, steel girder system

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Authors: Nikhil Jain, Bin Yu

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The material behavior of graphene, a single layer of carbon lattice, is extremely sensitive to its dielectric environment. We demonstrate improvement in electronic performance of graphene nanowire interconnects with full encapsulation by lattice-matching, chemically inert, 2D layered insulator hexagonal boron nitride (h-BN). A novel layer-based transfer technique is developed to construct the h-BN/MLG/h-BN heterostructures. The encapsulated graphene wires are characterized and compared with that on SiO2 or h-BN substrate without passivating h-BN layer. Significant improvements in maximum current-carrying density, breakdown threshold, and power density in encapsulated graphene wires are observed. These critical improvements are achieved without compromising the carrier transport characteristics in graphene. Furthermore, graphene wires exhibit electrical behavior less insensitive to ambient conditions, as compared with the non-passivated ones. Overall, h-BN/graphene/h-BN heterostructure presents a robust material platform towards the implementation of high-speed carbon-based interconnects.

Keywords: two-dimensional nanosheet, graphene, hexagonal boron nitride, heterostructure, interconnects

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Authors: Roopam Gaur, K. Chandramani Singh, Radhapiyari Laishram

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In order to produce lead free piezoceramics with optimum piezoelectric and dielectric properties, KNN modified with Li+ (as an A site dopant) and Sb5+ (as a B site dopant) (K0.49Na0.49Li0.02) (Nb0.96Sb0.04) O3 (referred as KNLNS in this paper) have been synthesized using solid state reaction method and conventional sintering technique. The ceramics were sintered in the narrow range of 10500C-10900C for 2-3 hours to get precise information about sintering parameters. Detailed study of dependence of microstructural, dielectric and piezoelectric properties on sintering conditions was then carried out. The study suggests that the volatility of the highly hygroscopic KNN ceramics is not only sensitive to sintering temperatures but also to sintering durations. By merely reducing the sintering duration for a given sintering temperature we saw an increase in the density of the samples which was supported by the increase in dielectric constants of the ceramics. And since density directly or indirectly affects almost all the associated properties, other dielectric and piezoelectric properties were also enhanced as we approached towards the most suitable sintering temperature and duration combination.

Keywords: piezoelectric, dielectric, Li, Sb, KNN, conventional sintering

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Authors: Aysheh Maslemani, Ruth Mayo, Greg Maio, Ariel Knafo-Noam

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Values are abstract ideals that serve as guiding principles in one's life. As inherently positive and desirable concepts, values are seen as motivators for actions and behaviors. However, research has largely ignored the possibility that values may elicit negative feelings despite being explicitly important to us. In the current study, we aim to examine this possibility. Four hundred participants over 18 years(M=41.6, SD=13.7, Female=178) from the UK completed a questionnaire in which they were asked to indicate their level of positive/negative feelings towards a comprehensive list of values and then report the importance of these values to them. The results support our argument by showing that people can have negative feelings towards their values and that people can feel both positive and negative emotions towards their values simultaneously, which means feeling ambivalence. We ran a mixed-effect model with ambivalence, value type, and their interaction as fixed effects, with by subject random intercept and by subject random slope for ambivalence. The results reveal that values that elicit less ambivalence predicted higher ratings for value importance. This research contributes to the field of values on multiple levels. Theoretically, it will uncover new insights about values, such as the existence of negative emotions towards them and the presence of ambivalence towards values. These findings may inspire future studies to explore the effects of ambivalence on people's well-being, behaviors, cognition, and their affect. We discuss the findings and consider their implications for understanding the social psychological mechanisms underpinning value ambivalence.

Keywords: emotion, social cognition, values., ambivalence

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Authors: Aysheh Maslemani, Ruth Mayo, Greg Maio, Ariel Knafo-Noam

Abstract:

Values are abstract ideals that serve as guiding principles in one's life. As inherently positive and desirable concepts, values are seen as motivators for actions and behaviors. However, research has largely ignored the possibility that values may elicit negative feelings despite being explicitly important to us. In the current study we aim to examine this possibility. Four hundred participants over 18 years(M=41.6,SD=13.7,Female=178) from the UK completed a questionnaire in which they were asked to indicate their level of positive/negative feelings towards a comprehensive list of values and then report the importance of these values to them. The results support our argument by showing that people can have negative feelings towards their values and that people can feel both positive and negative emotions towards their values simultaneously, which means feeling ambivalence. We ran a mixed-effect model with ambivalence, value type, and their interaction as fixed effects, with by subject random intercept, and by subject random slope for ambivalence. The results reveal that values that elicit less ambivalence predicted higher ratings for value importance. This research contributes to the field of values on multiple levels. Theoretically, it will uncover new insights about values, such as the existence of negative emotions towards them, the presence of ambivalence towards values. These findings may inspire future studies to explore the effects of ambivalence on people's well-being, behaviors, cognition, and their affect. We discuss the findings and consider their implications for understanding the social psychological mechanisms underpinning value ambivalence.

Keywords: ambivalence, emotion, social cognition, values

Procedia PDF Downloads 67

Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

Abstract:

The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: Behnam Zahednejad, Saeed Kosari

Abstract:

Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

Procedia PDF Downloads 102

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

Abstract:

Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

Procedia PDF Downloads 86

Authors: Farideh Gheitasi, Amir Hossain Jaberansari, Payam Abedini

Abstract:

The World Health Organization (WHO) Manifesto for Safe Communities states that "All human beings have an equal right to health and safety". The purpose of a safe Community is to minimize the damages threatening people. It seems that not sufficient attention has been given to relate environment and objectives of the safe Community. The reason for that can be assigned to the lack of enough information about environmental parameters and their relation with indices of the safe community like type and effect time of damages resulting from air pollution. Air pollution can be characterized as one of main environmental problems of Tehran. This problem is mostly due to the special geographic and climate situation, high population density and irregular growth in the number of vehicles. This paper is aimed at investigating the necessity of considering environmental factors to obtain a safe community through determining the effects of environmental pollution, particularly air pollution, on 490000 elders (+65) of Tehran. The methodology used in this study was on the basis of Random sampling and social surveying. The number of questionnaires was determined to be 321 through using Cochran method and the questionnaires were filled out by elders during personal interviews. The analysis of obtained results indicated that elders believe the major effects of air pollution include heart and respiratory diseases, obligation to stay at home on polluted days and its associated mental problems. Moreover, it was found that there is direct link between the number of polluted days and mortality frequency of elders. Having an environmental view may have an appreciable influence on the qualitative and quantitative development of activities and also facilitate obtaining the goals of the Safe Communities. In addition to reduce damages caused by pollutions, this view will encourage friends of the environment to cooperate with authorities of the safe community.

Keywords: air pollution, elderly people, environment, waste management

Procedia PDF Downloads 482

Authors: Aicha Beya Mammeria, Idir Bitam

Abstract:

Our study focuses on the distribution of the white stork "Ciconia ciconia L. 1758" in the wetlands of El Tarf (North eastern of Algeria): recognized by its remarkable number of breeding pairs, monitoring of nesting, using a GPS has been performed in an attempt to explain the functioning of populations and population strategies for an overall design of its distribution, which has not so far been investigated in this region. Between 2012 and 2013, the number of breeding pairs has increased considerably from 174 in 1996 to 475 in 2007 and 968 in 2013. It should be noted that in the distribution of breeding pairs between 1996 and 2011, there is a significant development since the density of nests increased from 25.22 in 1996 to 84.16 couples/100 km² in 2013. More endemic bread apears in the region, this fluctuation is related to climatic change and changing season. Changes related to local climatic conditions might induce binding conditions for the development of this species.

Keywords: white stork, Ciconia ciconia, wetland El Tarf, northeast Algeria, climatic changing, density

Procedia PDF Downloads 534

Authors: Dong-Woo Kang

Abstract:

This paper presents an optimal magnet shape of a spoke-shaped interior permanent magnet synchronous motor by using ferrite magnets. Generally, the permanent magnet motor used the ferrite magnets has lower output power and efficiency than a rare-earth magnet motor, because the ferrite magnet has lower magnetic energy than the rare-earth magnet. Nevertheless, the ferrite magnet motor is used to many industrial products owing to cost effectiveness. In this paper, the authors propose a high power density design of the ferrite permanent magnet synchronous motor. Furthermore, because the motor design has to be taken a manufacturing process into account, the design is simulated by using the finite element method for analyzing the demagnetization, the magnetizing, and the structure stiffness. Especially, the magnet shape and dimensions are decided for satisfying these properties. Finally, the authors design an optimal motor for applying our system. That final design is manufactured and evaluated from experimentations.

Keywords: demagnetization, design optimization, magnetic analysis, permanent magnet motors

Procedia PDF Downloads 377

Authors: Meidesta Pitria, Akiko Okabe

Abstract:

In high-density informal settlement, extension area at the outside of the houses could primarily happen as a spatial modification response. House extension in high-density informal settlement is not only becoming a physical spatial modification that makes a blur zone between private and public but also supporting the growth and existence of informal economy and other daily activities in both individuals and communities. This research took a case study in an informal settlement named Kampung Cikini, a densely populated area in Central Jakarta. The aim of this study is to identify and clarify house extension as a strategy in dealing with urbanization in an informal settlement. By using the perspective and information from housewives, the analysis is based on the assumption that land ownership transformation and the activities in house extension area influence the different kinds of house extension’s spatial modification and local planning policy in relation with the implementation of house extension strategy. The data collection was done in four sites, two sites are located in outer-wide alley and another two sites are located in inner-narrow alley. In this research, data of 104 housewives in 86 houses were collected through representatives of housewives and local leader of each sites. The research was started from participatory mapping process, deep interview with local leader, and initiated collaboration with housewives community in having a celebration as communal event to cultivate together the issue. This study shows that land ownership, activities, and alley are indispensable in the decision of extension space making. The more permanency status of land ownership the more permanent and various extension could be implemented. However, in some blocks, the existence of origin house or first land owner also has a significant role in coordination and agreement in using and modifying extension space. In outer-wide alley, the existence of more various activities in front area of the houses is significantly related with the chance given by having wider alley, particularly for informal income generating activities. In the inner-narrow alley, limited space in front of the houses affects more negotiations in the community for having more shared spaces, even inside their private space.

Keywords: house extension, housewives, informal settlement, kampung, high density

Procedia PDF Downloads 206