Search results for: helmholt decomposition

Authors: Yingxu Wang

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This work presents basic research on the recursive structures and dual sequential patterns of primes for the formal proof of the Twin-Prime Conjecture (TPC). A rigorous methodology of Twin-Prime Decomposition (TPD) is developed in MATLAB to inductively verify potential twins in the dual sequences of primes. The key finding of this basic study confirms that the dual sequences of twin primes are not only symmetric but also infinitive in the unique base 6 cycle, except a limited subset of potential pairs is eliminated by the lack of dual primality. Both theory and experiments have formally proven that the infinity of twin primes stated in TPC holds in the P x P space.

Keywords: number theory, primes, twin-prime conjecture, dual primes (P x P), twin prime decomposition, formal proof, algorithm

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Authors: B. Palanikumaran, N. Kanagaraj, M. Sangareswari, V. Sailaja, Kapil Sihag

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The present study aimed to estimate the carbon sequestration potential of major forest types present in the foothills of Nilgiri biosphere reserve. The total biomass carbon stock was estimated in tropical thorn forest, tropical dry deciduous forest and tropical moist deciduous forest as 14.61 t C ha⁻¹ 75.16 t C ha⁻¹ and 187.52 t C ha⁻¹ respectively. The density and basal area were estimated in tropical thorn forest, tropical dry deciduous forest, tropical moist deciduous forest as 173 stems ha⁻¹, 349 stems ha⁻¹, 391 stems ha⁻¹ and 6.21 m² ha⁻¹, 31.09 m² ha⁻¹, 67.34 m² ha⁻¹ respectively. The soil carbon stock of different forest ecosystems was estimated, and the results revealed that tropical moist deciduous forest (71.74 t C ha⁻¹) accounted for more soil carbon stock when compared to tropical dry deciduous forest (31.80 t C ha⁻¹) and tropical thorn forest (3.99 t C ha⁻¹). The tropical moist deciduous forest has the maximum annual leaf litter which was 12.77 t ha⁻¹ year⁻¹ followed by 6.44 t ha⁻¹ year⁻¹ litter fall of tropical dry deciduous forest. The tropical thorn forest accounted for 3.42 t ha⁻¹ yr⁻¹ leaf litter production. The leaf litter carbon stock of tropical thorn forest, tropical dry deciduous forest and tropical moist deciduous forest found to be 1.02 t C ha⁻¹ yr⁻¹ 2.28 t⁻¹ C ha⁻¹ yr⁻¹ and 5.42 t C ha⁻¹ yr⁻¹ respectively. The results explained that decomposition percent at the soil surface in the following order.tropical dry deciduous forest (77.66 percent) > tropical thorn forest (69.49 percent) > tropical moist deciduous forest (63.17 percent). Decomposition percent at soil subsurface was studied, and the highest decomposition percent was observed in tropical dry deciduous forest (80.52 percent) followed by tropical moist deciduous forest (77.65 percent) and tropical thorn forest (72.10 percent). The decomposition percent was higher at soil subsurface. Among the three forest type, tropical moist deciduous forest accounted for the highest bacterial (59.67 x 105cfu’s g⁻¹ soil), actinomycetes (74.87 x 104cfu’s g⁻¹ soil) and fungal (112.60 x10³cfu’s g⁻¹ soil) population. The overall observation of the study helps to conclude that, the tropical moist deciduous forest has the potential of storing higher carbon content as biomass with the value of 264.68 t C ha⁻¹ and microbial populations.

Keywords: basal area, carbon sequestration, carbon stock, Nilgiri biosphere reserve

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Authors: Nasser A. M. Habib

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The impressive physical properties of graphene derivatives, including thermal properties, have made them an attractive addition to advanced construction nanomaterial. In this study, we investigated the impact of incorporating low amounts of graphene oxide (GO) into cement mixture nanocomposites on their heat storage and thermal stability. The composites were analyzed using Fourier transmission infrared, thermo-gravimetric analysis, and field emission scanning electron microscopy. Results showed that GO significantly improved specific heat by 32%, reduced thermal conductivity by 16%, and reduced thermal decomposition to only 3% at a concentration of 1.2 wt%. These findings suggest that the cement mixture can withstand high temperatures and may suit specific applications requiring thermal stability and insulation properties.

Keywords: cement mixture composite, graphene oxide, thermal decomposition, thermal conductivity

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Authors: Yingxu Wang

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The base 6 structure and properties of mirror primes are discovered in this work towards the proof of Goldbach Conjecture. This paper reveals a fundamental pattern on pairs of mirror primes adjacent to any even number nₑ > 2 with symmetrical distances on both sides determined by a methodology of Mirror Prime Decomposition (MPD). MPD leads to a formal proof of the Goldbach conjecture, which states that the conjecture holds because any pivot even number, nₑ > 2, is a sum of at least an adjacent pair of primes divided by 2. This work has not only revealed the analytic pattern of base 6 primes but also proven the infinitive validation of the Goldbach conjecture.

Keywords: number theory, primes, mirror primes, double recursive patterns, Goldbach conjecture, formal proof, mirror-prime decomposition, applications

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Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

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The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: DT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

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Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

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Authors: Adel Mohsen

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A direct method based on the good Broyden's updates for evaluating the inverse of a nonsingular square matrix of full rank and solving related system of linear algebraic equations is studied. For a matrix A of order n whose LU-decomposition is A = LU, the multiplication count is O (n3). This includes the evaluation of the LU-decompositions of the inverse, the lower triangular decomposition of A as well as a “reduced matrix inverse”. If an explicit value of the inverse is not needed the order reduces to O (n3/2) to compute to compute inv(U) and the reduced inverse. For a symmetric matrix only O (n3/3) operations are required to compute inv(L) and the reduced inverse. An example is presented to demonstrate the capability of using the reduced matrix inverse in treating ill-conditioned systems. Besides the simplicity of Broyden's update, the method provides a mean to exploit the possible sparsity in the matrix and to derive a suitable preconditioner.

Keywords: Broyden's updates, matrix inverse, inverse factorization, solution of linear algebraic equations, ill-conditioned matrices, preconditioning

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Authors: Wendong Yang, Changhai Wang, Valeria Arrighi

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Low ink sintering temperature is desired for flexible electronics, as it would widen the application of the ink on temperature-sensitive substrates where the selection of silver precursor is very critical. In this paper, four types of organic silver precursors, silver carbonate, silver oxalate, silver tartrate and silver itaconate, were synthesized using an ion exchange method, firstly. Various characterization methods were employed to investigate their physical phase, chemical composition, morphologies and thermal decomposition behavior. It was found that silver oxalate had the ideal thermal property and showed the lowest decomposition temperature. An ink was then formulated by complexing the as-prepared silver oxalate with ethylenediamine in organic solvents. Results show that a favorable conductive film with a uniform surface structure consisting of silver nanoparticles and few voids could be produced from the ink at a sintering temperature of 150 °C.

Keywords: conductive ink, electrical property, film, organic silver

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Authors: Ahmad Awajan, Sadam Al Wadi

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In this study, a hybrid method based on Empirical Mode Decomposition and Holt-Winter (EMD-HW) is used to forecast Amman stock market data. First, the data are decomposed by EMD method into Intrinsic Mode Functions (IMFs) and residual components. Then, all components are forecasted by HW technique. Finally, forecasting values are aggregated together to get the forecasting value of stock market data. Empirical results showed that the EMD- HW outperform individual forecasting models. The strength of this EMD-HW lies in its ability to forecast non-stationary and non- linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy comparing with eight existing forecasting methods based on the five forecast error measures.

Keywords: Holt-Winter method, empirical mode decomposition, forecasting, time series

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Authors: Yinwei Lin, Cha'o-Kuang Chen

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In this article, the Laplace Adomian transform method (LADM) and double decomposition method (DDM) are used to solve the annular hyperbolic profile fins with variable thermal conductivity. As the thermal conductivity parameter ε is relatively large, the numerical solution using DDM become incorrect. Moreover, when the terms of DDM are more than seven, the numerical solution using DDM is very complicated. However, the present method can be easily calculated as terms are over seven and has more precisely numerical solutions. As the thermal conductivity parameter ε is relatively large, LADM also has better accuracy than DDM.

Keywords: fins, thermal conductivity, Laplace transform, Adomian, nonlinear

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Authors: Rene Valdiviezo-Issa

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In this paper, we use Mexico’s Households Income and Expenditures (ENIGH) survey to explain the behaviour that the urban-rural expenditure gap has had since Mexico’s incorporation to the North American Free Trade Agreement (NAFTA) in 1994 and we compare it with the latest available survey, which took place in 2014. We use real trimestral expenditure per capita (RTEPC) as the measure of welfare. We use quantile regressions and a quantile regression decomposition to describe the gap between urban and rural distributions of log RTEPC. We discover that the decrease in the difference between the urban and rural distributions of log RTEPC, or inequality, is motivated because of a deprivation of the urban areas, in very specific characteristics, rather than an improvement of the urban areas. When using the decomposition we observe that the gap is primarily brought about because differences in returns to covariates between the urban and rural areas.

Keywords: quantile regression, urban-rural inequality, inequality in Mexico, income decompositon

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Authors: Ahmad Idi

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The biosynthesis and properties of polyhydroxyalkanoate (PHA) are determined by the bacterial strain and the culture condition. Hence this study elucidates the structure and properties of PHA produced by a newly isolated strain of photosynthetic bacterium, Rhodobacter sphaeroides ADZ101 grown under the optimized culture condition. The properties of the accumulated PHA were determined via FTIR, NMR, TGA, and GCMS analyses. The results showed that acetate and ammonia chloride had the highest PHA accumulation with a ratio of 32.5 mM at neutral pH. The structural analyses showed that the polymer comprises both short and medium-chain length monomers ranging from C5, C13, C14, and C18, as well as the presence of novel PHA monomers. The thermal analysis revealed that the maximum temperature of decomposition occurred at 395°C and 454°C, indicating two major decomposition reactions. Thus this bacterial strain, optimized culture condition, and the abundance of novel monomers enhanced the thermostability of the accumulated PHA.

Keywords: bioplastic polyhydroxyalkanoates Rhodobacter sphaeroides ADZ101 thermostable PHA

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Authors: Ueda Honoka, Yasuo Hasegawa, Fumihiro Nishimura, Jae-Ho Kim, Susumu Yonezawa

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Aqueous peroxotitanium acid solution prepared from the TiO₂ fluorinated by F₂ gas was used for the TiO₂ coating on glass fibrous filters in this study. The coating of TiO₂ on the surface of glass fibers was carried out at 120℃ and for 15 min ~ 24 h with aqueous peroxotitanium acid solution using a hydrothermal synthesis autoclave reactor. The morphology TiO₂ coating layer was largely dependent on the reaction time, as shown in the results of scanning electron microscopy and energy dispersive X-ray spectroscopy. Increasing the reaction times, the TiO₂ layer on the glass expanded uniformly. Moreover, the surface fluorination of glass fibers can promote the formation of the TiO₂ layer on the surface. The photocatalytic activity of prepared titania-coated glass fibrous filters was investigated by both the degradation test of methylene blue (MB) and the decomposition test of gaseous acetaldehyde. The MB decomposition ratio with fluorinated samples was about 95% for 30 min of UV irradiation time, and it was much higher than that (70%) with the untreated thing. The decomposition ratio (50%) of gaseous acetaldehyde with fluorinated samples was also higher than that (30%) with the untreated thing. Consequently, photocatalytic activity is enhanced by surface fluorination.

Keywords: aqueous peroxotitanium acid solution, titania-coated glass fibrous filters, photocatalytic activity, surface fluorination

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Authors: Wahiba Mohguen, Raïs El’hadi Bekka

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This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).

Keywords: customized thresholding, ECG signal, EMD, hard thresholding, soft-thresholding

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Authors: Kamel Al-Khaled

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Reaction-diffusion equations are commonly used in population biology to model the spread of biological species. In this paper, we propose a fractional reaction-diffusion equation, where the classical second derivative diffusion term is replaced by a fractional derivative of order less than two. Based on the symbolic computation system Mathematica, Adomian decomposition method, developed for fractional differential equations, is directly extended to derive explicit and numerical solutions of space fractional reaction-diffusion equations. The fractional derivative is described in the Caputo sense. Finally, the recent appearance of fractional reaction-diffusion equations as models in some fields such as cell biology, chemistry, physics, and finance, makes it necessary to apply the results reported here to some numerical examples.

Keywords: fractional partial differential equations, reaction-diffusion equations, adomian decomposition, biological species

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Authors: Gao Fangting

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With the accelerated pace of industrialization and urbanization, the economic level has been significantly improved, and at the same time, the air quality situation has also become a focus of attention, which not only affects people's health but also has certain impacts on the economy and ecology. As the capital city of China, the air quality situation in Beijing has attracted much attention. In this paper, based on the day-by-day PM2.5, PM10, CO, NO₂, SO₂ and O₃ conditions in Beijing from 2018 to 2022, the characterization of pollutants is launched, and the seasonal decomposition and prediction of the main pollutants, PM2.5, PM10 and O3, are performed in STL. The results of the study show that (1) the overall air quality of Beijing has significantly improved from 2018 to 2022, and the main pollutants are PM2.5, PM10, and O₃; (2) the seasonal intensities of the main pollutants are higher, and they are influenced by seasonal factors; and (3) it is predicted that the O₃ concentration will have a trend of slowly increasing from 2023 to 2026, and the PM10 and PM2.5 pollution situation slowly improves.

Keywords: air pollutants, Beijing, characteristic analysis, STL

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Authors: T. Bryan , V. Kepuska, I. Kostnaic

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A method of data compression and denoising is introduced that is based on atomic decomposition of audio data using “basis vectors” that are learned from the audio data itself. The basis vectors are shown to have higher data compression and better signal-to-noise enhancement than the Gabor and gammatone “seed atoms” that were used to generate them. The basis vectors are the input weights of a Sparse AutoEncoder (SAE) that is trained using “envelope samples” of windowed segments of the audio data. The envelope samples are extracted from the audio data by performing atomic decomposition with Gabor or gammatone seed atoms. This process identifies segments of audio data that are locally coherent with the seed atoms. Envelope samples are extracted by identifying locally coherent audio data segments with Gabor or gammatone seed atoms, found by matching pursuit. The envelope samples are formed by taking the kronecker products of the atomic envelopes with the locally coherent data segments. Oracle signal-to-noise ratio (SNR) verses data compression curves are generated for the seed atoms as well as the basis vectors learned from Gabor and gammatone seed atoms. SNR data compression curves are generated for speech signals as well as early American music recordings. The basis vectors are shown to have higher denoising capability for data compression rates ranging from 90% to 99.84% for speech as well as music. Envelope samples are displayed as images by folding the time series into column vectors. This display method is used to compare of the output of the SAE with the envelope samples that produced them. The basis vectors are also displayed as images. Sparsity is shown to play an important role in producing the highest denoising basis vectors.

Keywords: sparse dictionary learning, autoencoder, sparse autoencoder, basis vectors, atomic decomposition, envelope sampling, envelope samples, Gabor, gammatone, matching pursuit

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Authors: Kourosh Modarresi

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The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

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Authors: Jae-Hyun Ro, Jong-Kwang Kim, Chang-Hee Kang, Hyoung-Kyu Song

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In multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, QR decomposition-M algorithm (QRD-M) has suboptimal error performance. However, the QRD-M has still high complexity due to many calculations at each layer in tree structure. To reduce the complexity of the QRD-M, proposed QRD-M modifies existing tree structure by eliminating unnecessary candidates at almost whole layers. The method of the elimination is discarding the candidates which have accumulated squared Euclidean distances larger than calculated threshold. The simulation results show that the proposed QRD-M has same bit error rate (BER) performance with lower complexity than the conventional QRD-M.

Keywords: complexity, MIMO-OFDM, QRD-M, squared Euclidean distance

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Authors: Mohammad A. Bani-Khaled

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In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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Authors: Seyed Mohamad Rasool Mirkarimi, David Chiaramonti, Samir Bensaid

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Catalytic methane decomposition (CMD, reaction 4) is a one-step process for hydrogen production where carbon in the methane molecule is sequestered in the form of stable and higher-value carbon materials. Metallic catalysts and carbon-based catalysts are two major types of catalysts utilized for the CDM process. Although carbon-based catalysts have lower activity compared to metallic ones, they are less expensive and offer high thermal stability and strong resistance to chemical impurities such as sulfur. Also, it would require less costly separation methods as some of the carbon-based catalysts may not have an active metal component in them. Since the regeneration of metallic catalysts requires burning of the C on their surfaces, which emits CO/CO2, in some cases, using carbon-based catalysts would be recommended because regeneration can be completely avoided, and the catalyst can be directly used in other processes. This work focuses on the effect of biochar as a carbon-based catalyst for the conversion of methane into hydrogen and carbon. Biochar produced from the pyrolysis of poplar wood and activated biochar are used as catalysts for this process. In order to observe the impact of carbon-based catalysts on methane conversion, methane cracking in the absence and presence of catalysts for a gas stream with different levels of methane concentration should be performed. The results of these experiments prove conversion of methane in the absence of catalysts at 900 °C is negligible, whereas in the presence of biochar and activated biochar, significant growth has been observed. Comparing the results of the tests related to using char and activated char shows the enhancement obtained in BET surface area of the catalyst through activation leads to more than 10 vol.% methane conversion.

Keywords: hydrogen production, catalytic methane decomposition, biochar, activated biochar, carbon-based catalyts

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Mehmet Bozca

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Singular value decomposition based optimisation of geometric design parameters of a 5-speed gearbox is studied. During the optimisation, a four-degree-of freedom torsional vibration model of the pinion gear-wheel gear system is obtained and the minimum singular value of the transfer matrix is considered as the objective functions. The computational cost of the associated singular value problems is quite low for the objective function, because it is only necessary to compute the largest and smallest singular values (µmax and µmin) that can be achieved by using selective eigenvalue solvers; the other singular values are not needed. The design parameters are optimised under several constraints that include bending stress, contact stress and constant distance between gear centres. Thus, by optimising the geometric parameters of the gearbox such as, the module, number of teeth and face width it is possible to obtain a light-weight-gearbox structure. It is concluded that the all optimised geometric design parameters also satisfy all constraints.

Keywords: Singular value, optimisation, gearbox, torsional vibration

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Authors: Ji-Seok Hong, Hee-Jang Moon, Hong-Gye Sung

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The details of flow structures and the coupling mechanism between vortex shedding and acoustic excitation in a solid rocket motor with two inhibitors have been investigated using 3D Large Eddy Simulation (LES) and Proper Orthogonal Decomposition (POD) analysis. The oscillation frequencies and vortex shedding periods from two inhibitors compare reasonably well with the experimental data and numerical result. A total of four different locations of the rear inhibitor has been numerically tested to characterize the coupling relation of vortex shedding frequency and acoustic mode. The major source of triggering pressure oscillation in the combustor is the resonance with the acoustic longitudinal half mode. It was observed that the counter-rotating vortices in the nozzle flow produce roll torque.

Keywords: large eddy simulation, proper orthogonal decomposition, SRM instability, flow-acoustic coupling

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Authors: Malay Bhattacharyya, Saparya Suresh

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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

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Authors: Samim Khair Mohammad, Takeshi Tsuji, Chanmaly Chhun

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The Afghan Tajik (foreland) basin, located in the depression zone between mountain axes, is under compression and deformation during the collision of India with the Eurasian plate. The southern part of the Afghan Tajik basin in the Northern part of Afghanistan has not been well studied and explored, but considered for the significant potential for oil and gas resources. The Afghan Tajik basin depositional environments (< 8km) resulted from mixing terrestrial and marine systems, which has potential prospects of Jurrasic (deep) and Tertiary (shallow) petroleum systems. We used 2D regional seismic profiles with a total length of 674.8 km (or over an area of 2500 km²) in the southern part of the basin. To characterize hydrocarbon systems and structures in this study area, we applied advanced seismic attributes such as spectral decomposition (10 - 60Hz) based on time-frequency analysis with continuous wavelet transform. The spectral decomposition results yield the (averaging 20 - 30Hz group) spectral amplitude anomaly. Based on this anomaly result, seismic, and structural interpretation, the potential hydrocarbon accumulations were inferred around the main thrust folds in the tertiary (Paleogene+Neogene) petroleum systems, which appeared to be accumulated around the central study area. Furthermore, it seems that hydrocarbons dominantly migrated along the main thrusts and then concentrated around anticline fold systems which could be sealed by mudstone/carbonate rocks.

Keywords: The Afghan Tajik basin, seismic lines, spectral decomposition, thrust folds, hydrocarbon reservoirs

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Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

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Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: FSDWT, key frame extraction, shot detection, singular value decomposition

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Authors: Allah Bakhsh Javid, Ali Mashayekh-Salehi, Fatemeh Davardoost

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This study presents the preparation, characterization and catalytic activity of a novel natural mineral-based catalyst for destructive adsorption of tetracycline (TTC) as water emerging compounds. Degradation potential of raw and calcined magnetite catalyst was evaluated at different experiments situations such as pH, catalyst dose, reaction time and pollutant concentration. Calcined magnetite attained greater catalytic potential than the raw ore in the degradation of tetracycline, around 69% versus 3% at reaction time of 30 min and TTC aqueous solution of 50 mg/L, respectively. Complete removal of TTC could be obtained using 2 g/L calcined nanoparticles at reaction time of 60 min. The removal of TTC increased with the increase in solution temperature. Accordingly, considering its abundance in nature together with its very high catalytic potential, calcined pyrite is a promising and reliable catalytic material for destructive decomposition for catalytic decomposition and mineralization of such pharmaceutical compounds as TTC in water and wastewater.

Keywords: catalytic degradation, tetracycline, pyrite, emerging pollutants

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Authors: Nada R. Abuknesha, John P. Morgan, Andrew J. Searle

Abstract:

Information regarding post-mortem interval (PMI) in criminal investigations is vital to establish a time frame when reconstructing events. PMI is defined as the time period that has elapsed between the occurrence of death and the discovery of the corpse. Adipocere, commonly referred to as ‘grave-wax’, is formed when post-mortem adipose tissue is converted into a solid material that is heavily comprised of fatty acids. Adipocere is of interest to forensic anthropologists, as its formation is able to slow down the decomposition process. Therefore, analysing the changes in the patterns of fatty acids during the early decomposition process may be able to estimate the period of burial, and hence the PMI. The current study concerned the investigation of the fatty acid composition and patterns in buried pig fat tissue. This was in an attempt to determine whether particular patterns of fatty acid composition can be shown to be associated with the duration of the burial, and hence may be used to estimate PMI. The use of adipose tissue from the abdominal region of domestic pigs (Sus-scrofa), was used to model the human decomposition process. 17 x 20cm piece of pork belly was buried in a shallow artificial grave, and weekly samples (n=3) from the buried pig fat tissue were collected over an 11-week period. Marker fatty acids: palmitic (C16:0), oleic (C18:1n-9) and linoleic (C18:2n-6) acid were extracted from the buried pig fat tissue and analysed as fatty acid methyl esters using the gas chromatography system. Levels of the marker fatty acids were quantified from their respective standards. The concentrations of C16:0 (69.2 mg/mL) and C18:1n-9 (44.3 mg/mL) from time zero exhibited significant fluctuations during the burial period. Levels rose (116 and 60.2 mg/mL, respectively) and fell starting from the second week to reach 19.3 and 18.3 mg/mL, respectively at week 6. Levels showed another increase at week 9 (66.3 and 44.1 mg/mL, respectively) followed by gradual decrease at week 10 (20.4 and 18.5 mg/mL, respectively). A sharp increase was observed in the final week (131.2 and 61.1 mg/mL, respectively). Conversely, the levels of C18:2n-6 remained more or less constant throughout the study. In addition to fluctuations in the concentrations, several new fatty acids appeared in the latter weeks. Other fatty acids which were detectable in the time zero sample, were lost in the latter weeks. There are several probable opportunities to utilise fatty acid analysis as a basic technique for approximating PMI: the quantification of marker fatty acids and the detection of selected fatty acids that either disappear or appear during the burial period. This pilot study indicates that this may be a potential semi-quantitative methodology for determining the PMI. Ideally, the analysis of particular fatty acid patterns in the early stages of decomposition could be an additional tool to the already available techniques or methods in improving the overall processes in estimating PMI of a corpse.

Keywords: adipocere, fatty acids, gas chromatography, post-mortem interval

Procedia PDF Downloads 131

Authors: Muna Khushaim

Abstract:

Aluminum-based alloys play a key role in modern engineering, especially in the aerospace industry. Introduction of solute atoms such as Li and Cu is the main approach to improve the strength in age-hardenable Al alloys via the precipitation hardening phenomenon. Knowledge of the decomposition process of the microstructure during the precipitation reaction is particularly important for future technical developments. The objective of this study is to investigate the nano-scale chemical composition in the Al-Cu, Al-Li and Al-Li-Cu during the early stage of the precipitation sequence and to describe whether this compositional difference correlates with variations in the observed precipitation kinetics. Comparing the random binomial frequency distribution and the experimental frequency distribution of concentrations in atom probe tomography data was used to investigate the early stage of decomposition in the different binary and ternary alloys which were experienced different heat treatments. The results show that an Al-1.7 at.% Cu alloy requires a long ageing time of approximately 8 h at 160 °C to allow the diffusion of Cu atoms into Al matrix. For the Al-8.2 at.% Li alloy, a combination of both the natural ageing condition (48 h at room temperature) and a short artificial ageing condition (5 min at 160 °C) induces increasing on the number density of the Li clusters and hence increase number of precipitated δ' particles. Applying this combination of natural ageing and short artificial ageing conditions onto the ternary Al-4 at.% Li-1.7 at.% Cu alloy induces the formation of a Cu-rich phase. Increasing the Li content in the ternary alloy up to 8 at.% and increasing the ageing time to 30 min resulted in the precipitation processes ending with δ' particles. Thus, the results contribute to the understanding of Al-alloy design.

Keywords: aluminum alloy, atom probe tomography, early stage, decomposition

Procedia PDF Downloads 343