Search results for: depthwise separable convolutions

Authors: Shreya Banerjee, Prasanta K. Panigrahi

Abstract:

The three-way distributive entanglement is shown to be related to the parallelism of vectors. Using a measurement-based approach a set of 2−dimensional vectors is formed, representing the post-measurement states of one of the parties. These vectors originate at the same point and have an angular distance between them. The area spanned by a pair of such vectors is a measure of the entanglement of formation. This leads to a geometrical manifestation of the 3−tangle in 2−dimensions, from inequality in the area which generalizes for n− qubits to reveal that the n− tangle also has a planar structure. Quantifying the genuine n−party entanglement in every 1|(n − 1) bi-partition it is shown that the genuine n−way entanglement does not manifest in n− tangle. A new quantity geometrically similar to 3−tangle is then introduced that represents the genuine n− way entanglement. Extending the formalism to 3− qutrits, the nonlocality without entanglement can be seen to arise from a condition under which the post-measurement state vectors of a separable state show parallelism. A connection to nontrivial sum uncertainty relation analogous to Maccone and Pati uncertainty relation is then presented using decomposition of post-measurement state vectors along parallel and perpendicular direction of the pre-measurement state vectors. This study opens a novel way to understand multiparty entanglement in qubit and qudit systems.

Keywords: Geometry of quantum entanglement, Multipartite and distributive entanglement, Parallelism of vectors , Tangle

Procedia PDF Downloads 127

Authors: Fu Lin

Abstract:

We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a prespecified number of line outages that lead to the maximum interruption of power generation and load at the transmission level, subject to the active power-flow model, the load and generation capacity of the buses, and the phase-angle limit across the transmission lines. For this nonlinear model with binary constraints, we show that all decision variables are separable except for the nonlinear power-flow equations. We develop an iterative decomposition algorithm, which converts the worst-case load shedding problem into a sequence of small subproblems. We show that the subproblems are either convex problems that can be solved efficiently or nonconvex problems that have closed-form solutions. Consequently, our approach is scalable for large networks. Furthermore, we prove the convergence of our algorithm to a critical point, and the objective value is guaranteed to decrease throughout the iterations. Numerical experiments with IEEE test cases demonstrate the effectiveness of the developed approach.

Keywords: load shedding, power system, proximal alternating linearization method, vulnerability analysis

Procedia PDF Downloads 110

Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

Abstract:

The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

Procedia PDF Downloads 364

Authors: Damir Latypov

Abstract:

A closed-form solution for 4-D double surface integrals arising in boundary integrals equations of a potential theory is obtained for arbitrary coplanar polygonal surfaces. The solution method is based on the construction of exact differential forms followed by the application of Stokes' theorem for each surface integral. As a result, the 4-D double surface integral is reduced to a 2-D double line integral. By an appropriate change of variables, the integrand is transformed into a separable function of integration variables. The closed-form solutions to the corresponding 1-D integrals are readily available in the integration tables. Previously closed-form solutions were known only for the case of coincident triangle surfaces and coplanar rectangles. Solutions for these cases were obtained by surface-specific ad-hoc methods, while the present method is general. The method also works for non-polygonal surfaces. As an example, we compute in closed form the 4-D integral for the case of coincident surfaces in the shape of a circular disk. For an arbitrarily shaped surface, the proposed method provides an efficient quadrature rule. Extensions of the method for non-coplanar surfaces and other than 1/R integral kernels are also discussed.

Keywords: boundary integral equations, differential forms, integration, stokes' theorem

Procedia PDF Downloads 282

Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

Abstract:

Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

Procedia PDF Downloads 251

Authors: Oumaima Khlifati, Khadija Baba

Abstract:

Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

Procedia PDF Downloads 60

Authors: Qian Zhao

Abstract:

With global increasing demand for phosphorus and intensively depleting reserves, it is urgent need to explore innovative approaches towards capturing phosphate from sewage, which is also an effective way to reduce phosphate contamination and avoid eutrophication of water bodies. In the present article, the superparamagnetic nano-sorbents containing Fe₃O₄ core and hafnium-modified MgAl/MgFe layered double hydroxides shell (abbreviated as MgAlHf-NP and MgFeHf-NP) was developed using a simple and low-cost synthesis protocol. The obtained Hf-coated nano-materials showed well-defined crystal structure and sufficient saturation magnetization and exhibited higher adsorption capacity for phosphate. Meanwhile, high selectivity was also confirmed since coexisting foreign anions and biomacromolecules showed little competitive effect on phosphate adsorption. The enhancement via doping with Hf should be explained by the stronger ligand complexation built by the pair of hard acid Hf ion and hard base phosphate that matched up the bonding preferences. Sufficient OH⁻ concentration and clear pH shift during the desorption/regeneration allowed for regeneration rate of higher than 90% after 5 cycles of adsorption desorption. This article attempts to provide a competitive candidate for phosphate-capture, which is highly effective, easily separable and repeatedly usable.

Keywords: phosphate recovery, nanoparticles, superparamagnetic, adsorption, reusability

Procedia PDF Downloads 104

Authors: Ashutosh Kumar, Irene M. C. Lo

Abstract:

Ever since the discovery of TiO2 for decomposition of cyanide in water, it has been investigated extensively for the photocatalytic degradation of environmental pollutants, and became the most practical and prevalent photocatalyst. The superiority of TiO2 is due to its chemical and biological inertness, nontoxicity, strong oxidizing power and cost-effectiveness. However, during degradation of pollutants in wastewater, it suffers from problems, such as (a) separation after use, and (b) its poor photocatalytic performance under visible light irradiation (~45% of the solar spectrum). In order to bridge the research gaps, N-TiO2@SiO2@Fe3O4 nanophotocatalysts of average size 19 nm and effective surface area 47 m2 gm-1 were synthesized using sol-gel method. The characterization was performed using BET, TEM-EDX, VSM and XRD. The performance was improved by considering different factors involved during the synthesis, such as calcination temperature, amount of Fe3O4 nanoparticles used and amount of urea used for N-doping. The final nanophotocatalyst was calcined at 500 °C which was able to degrade 94% of the ibuprofen within 5 h of irradiation time. Under the influence of ~200 mT electromagnetic field, 95% nanophotocatalysts separation efficiency was achieved within 20-25 min. Moreover, the effect of different visible light source of similar irradiance, such as compact fluorescent lamp (CFL) and light emitting diode (LED), is also investigated in this research. The performance of nanophotocatalysts was found to be comparatively higher under ~310 µW cm-2 irradiance with peak emissive wavelengths of 543 nm emitted by CFL. Therefore, a promising visible-light-driven magnetically separable TiO2-based nanophotocatalysts was synthesized for the efficient degradation of ibuprofen.

Keywords: ibuprofen, magnetic N-TiO2, photocatalysis, visible light sources

Procedia PDF Downloads 222

Authors: Sajjad Hussain, Sabir Khan, Maria Del Pilar Taboada Sotomayor

Abstract:

This work demonstrates the synthesis of magnetic molecularly imprinted polymers (MMIPs) for determination of a selected pesticide (ametryne) using high performance liquid chromatography (HPLC). Computational simulation can assist the choice of the most suitable monomer for the synthesis of polymers. The (MMIPs) were polymerized at the surface of Fe3O4@SiO2 magnetic nanoparticles (MNPs) using 2-vinylpyradine as functional monomer, ethylene-glycol-dimethacrylate (EGDMA) is a cross-linking agent and 2,2-Azobisisobutyronitrile (AIBN) used as radical initiator. Magnetic non-molecularly imprinted polymer (MNIPs) was also prepared under the same conditions without analyte. The MMIPs were characterized by scanning electron microscopy (SEM), Brunauer, Emmett and Teller (BET) and Fourier transform infrared spectroscopy (FTIR). Pseudo first order and pseudo second order model were applied to study kinetics of adsorption and it was found that adsorption process followed the pseudo first order kinetic model. Adsorption equilibrium data was fitted to Freundlich and Langmuir isotherms and the sorption equilibrium process was well described by Langmuir isotherm mode. The selectivity coefficients (α) of MMIPs for ametryne with respect to atrazine, ciprofloxacin and folic acid were 4.28, 12.32, and 14.53 respectively. The spiked recoveries ranged between 91.33 and 106.80% were obtained. The results showed high affinity and selectivity of MMIPs for pesticide ametryne in the food samples.

Keywords: molecularly imprinted polymer, pesticides, magnetic nanoparticles, adsorption

Procedia PDF Downloads 466

Authors: Sabir Khan, Sajjad Hussain, Ademar Wong, Maria Del Pilar Taboada Sotomayor

Abstract:

The present work aims to develop magnetic molecularly imprinted polymers (MMIPs) for determination of a selected pesticide (ametryne) using high-performance liquid chromatography (HPLC). Computational simulation can assist the choice of the most suitable monomer for the synthesis of polymers. The (MMIPs) were polymerized at the surface of Fe3O4@SiO2 magnetic nanoparticles (MNPs) using 2-vinylpyradine as functional monomer, ethylene-glycol-dimethacrylate (EGDMA) is a cross-linking agent and 2,2-Azobisisobutyronitrile (AIBN) used as radical initiator. Magnetic non-molecularly imprinted polymer (MNIPs) was also prepared under the same conditions without analyte. The MMIPs were characterized by scanning electron microscopy (SEM), Brunauer, Emmett and Teller (BET) and Fourier transform infrared spectroscopy (FTIR). Pseudo first-order and pseudo second order model were applied to study kinetics of adsorption and it was found that adsorption process followed the pseudo-first-order kinetic model. Adsorption equilibrium data was fitted to Freundlich and Langmuir isotherms and the sorption equilibrium process was well described by Langmuir isotherm mode. The selectivity coefficients (α) of MMIPs for ametryne with respect to atrazine, ciprofloxacin and folic acid were 4.28, 12.32 and 14.53 respectively. The spiked recoveries ranged between 91.33 and 106.80% were obtained. The results showed high affinity and selectivity of MMIPs for pesticide ametryne in the food samples.

Keywords: molecularly imprinted polymer, pesticides, magnetic nanoparticles, adsorption

Procedia PDF Downloads 443

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

Abstract:

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

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

Procedia PDF Downloads 303

Authors: Shouji Yujiro, Memei Dukovic, Mist Yakubu

Abstract:

Fields are important objects of study in algebra since they provide a useful generalization of many number systems, such as the rational numbers, real numbers, and complex numbers. In particular, the usual rules of associativity, commutativity and distributivity hold. Fields also appear in many other areas of mathematics; see the examples below. When abstract algebra was first being developed, the definition of a field usually did not include commutativity of multiplication, and what we today call a field would have been called either a commutative field or a rational domain. In contemporary usage, a field is always commutative. A structure which satisfies all the properties of a field except possibly for commutativity, is today called a division ring ordivision algebra or sometimes a skew field. Also non-commutative field is still widely used. In French, fields are called corps (literally, body), generally regardless of their commutativity. When necessary, a (commutative) field is called corps commutative and a skew field-corps gauche. The German word for body is Körper and this word is used to denote fields; hence the use of the blackboard bold to denote a field. The concept of fields was first (implicitly) used to prove that there is no general formula expressing in terms of radicals the roots of a polynomial with rational coefficients of degree 5 or higher. An extension of a field k is just a field K containing k as a subfield. One distinguishes between extensions having various qualities. For example, an extension K of a field k is called algebraic, if every element of K is a root of some polynomial with coefficients in k. Otherwise, the extension is called transcendental. The aim of Galois Theory is the study of algebraic extensions of a field. Given a field k, various kinds of closures of k may be introduced. For example, the algebraic closure, the separable closure, the cyclic closure et cetera. The idea is always the same: If P is a property of fields, then a P-closure of k is a field K containing k, having property, and which is minimal in the sense that no proper subfield of K that contains k has property P. For example if we take P (K) to be the property ‘every non-constant polynomial f in K[t] has a root in K’, then a P-closure of k is just an algebraic closure of k. In general, if P-closures exist for some property P and field k, they are all isomorphic. However, there is in general no preferable isomorphism between two closures.

Keywords: field theory, mechanic maths, supertech, rolltech

Procedia PDF Downloads 342

Authors: Arindam Chaudhuri

Abstract:

Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

Procedia PDF Downloads 466

Authors: Fayssal Tayalati

Abstract:

Although languages use very divergent constructional strategies, all existential constructions appear to invariably involve an implicit or explicit locative constituent. This locative constituent either surface as a true locative phrase or are realized as a possessor noun phrase. However, while much research focuses on the supposed underlying syntactic relation of locative and possessive existential constructions, not much is known about possible semantic factors that could govern the choice between these constructions. The main question that we address in this talk concerns the choice between the two related constructions in Modern Standard Arabic (MAS). Although both are used to express the existence of something somewhere, we can distinguish three contexts: First, for some types of entities, only the EL construction is possible (e.g. (1a) ṯammata raǧulun fī l-ḥadīqati vs. (1b) *(kāna) ladā l-ḥadīqati raǧulun). Second, for other types of entities, only the possessive construction is possible (e.g. (2a) ladā ṭ-ṭawilati aklun dāʾiriyyun vs. (2b) *ṯammata šaklun dāʾiriyyun ladā/fī ṭ-ṭawilati). Finally, for still other entities, both constructions can be found (e.g. (3a) ṯammata ḥubbun lā yūṣafu ladā ǧārī li-zawǧati-hi and (3b) ladā ǧārī ḥubbun lā yūṣafu li-zawǧati-hi). The data covering a range of ontologically different entities (concrete objects, events, body parts, dimensions, essential qualities, feelings, etc.) shows that the choice between the existential locative and the possessive constructions is closely linked to the conceptual autonomy of the existential theme with respect to its location or to the whole that it is a part of. The construction with ṯammata is the only possible one to express the existence of a fully autonomous (i.e. nondependent) entity (concrete objects (e.g.1) and abstract objects such as events, especially the ones that Grimshaw called ‘simple events’). The possessive construction with (kāna) ladā is the only one used to express the existence of fully non-autonomous (i.e. fully dependent on a whole) entities (body parts, dimensions (e.g. 2), essential qualities). The two constructions alternate when the existential theme is conceptually dependent but separable of the whole, either because it has an autonomous (independent) existence of the given whole (spare parts of an object), or because it receives a relative autonomy in the speech through a modifier (accidental qualities, feelings (e.g. 3a, 3b), psychological states, among some other kinds of themes). In this case, the modifier expresses an approximate boundary on a scale, and provides relative autonomy to the entity. Finally, we will show that kinship terms (e.g. son), which at first sight may seem to constitute counterexamples to our hypothesis, are nonetheless supported by it. The ontological (non-)autonomy of located or possessed entities is also reflected by morpho-syntactic properties, among them the use and the choice of determiners, pluralisation and the behavior of entities in the context of associative anaphora.

Keywords: existence, possession, autonomous entities, non-autonomous entities

Procedia PDF Downloads 322

Authors: Jiangbo Li, Wenqian Huang

Abstract:

Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest commercialization process. The automatic and nondestructive detection of infected fruits is still a challenge for the citrus industry. At present, the visual inspection of rotten citrus fruits is commonly performed by workers through the ultraviolet induction fluorescence technology or manual sorting in citrus packinghouses to remove fruit subject with fungal infection. However, the former entails a number of problems because exposing people to this kind of lighting is potentially hazardous to human health, and the latter is very inefficient. Orange is used as a research object. This study would focus on this problem and proposed an effective method based on Vis-NIR hyperspectral imaging in the wavelength range of 400-1000 nm with a spectroscopic resolution of 2.8 nm. In this work, three normalization approaches are applied prior to analysis to reduce the effect of sample curvature on spectral profiles, and it is found that mean normalization was the most effective pretreatment for decreasing spectral variability due to curvature. Then, principal component analysis (PCA) was applied to a dataset composing of average spectra from decayed and normal tissue to reduce the dimensionality of data and observe the ability of Vis-NIR hyper-spectra to discriminate data from two classes. In this case, it was observed that normal and decayed spectra were separable along the resultant first principal component (PC1) axis. Subsequently, five wavelengths (band) centered at 577, 702, 751, 808, and 923 nm were selected as the characteristic wavelengths by analyzing the loadings of PC1. A multispectral combination image was generated based on five selected characteristic wavelength images. Based on the obtained multispectral combination image, the intensity slicing pseudocolor image processing method is used to generate a 2-D visual classification image that would enhance the contrast between normal and decayed tissue. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudocolor image coupled with a simple thresholding method. For the investigated 238 independent set samples including infected fruits infected by Penicillium digitatum and normal fruits, the total success rate is 100% and 97.5%, respectively, and, the proposed algorithm also used to identify the orange infected by penicillium italicum with a 100% identification accuracy, indicating that the proposed multispectral algorithm here is an effective method and it is potential to be applied in citrus industry.

Keywords: citrus fruit, early rotten, fungal infection, hyperspectral imaging

Procedia PDF Downloads 272

Authors: Zihao He

Abstract:

The majority of existing studies on the Taiping Movement (1851-1864) viewed their anti-Manchu attitudes as nationalist agendas: Taiping was aimed at revolting against the Manchu government and establishing a new political regime. To explain these aggressive and violent attitudes towards Manchu, these studies mainly found socio-economic factors and stressed the status of “being deprived”. Even the ‘demon-slaying’ narrative of the Taiping to dehumanize the Manchu tends to be viewed as a “religious tool” to achieve their political, nationalist aim. This paper argues that these studies on Taiping’s anti-Manchu attitudes and behaviors are analyzed from an external angle and have two major problems. Firstly, they distinguished “religion” from “nationalist” or “political”, focusing on the “political” nature of the movement. “Religion” and the religious experience within Taiping were largely ignored. This paper argues that there was no separable and independent “religion” in the Taiping Movement, as opposed to secular, nationalist politics. Secondly, these analyses held an external perspective on Taiping’s anti-Manchu agenda. Demonizing and killing Manchu were viewed as purely political actions. On the contrary, this paper focuses on the internal perspective of anti-Manchu narratives in the Taiping Movement. The method of this paper is mainly textual analysis, focusing on the official documents, edicts, and proclamations of the Taiping movement. It views the writing of the Taiping as a coherent narrative and rhetoric, which was attractive and convincing for its followers. In terms of the main findings, firstly, internal and external perspectives on anti-Manchu violence are different. Externally, violence was viewed as a tool and necessary process to achieve the political goal. However, internally speaking, in Taiping’s writing, violence was a result of Godlessness, which would be solved as far as the faith in God is restored in China. Having a framework of universal love among human beings as sons and daughters of the Heavenly Father and killing was forbidden, the Taiping excluded Manchus from the family of human beings and demonized them. “Demon-slaying” was not violence. It was constructed as a necessary process to achieve the Great Peace. Moreover, Taiping’s anti-Manchu violence was not merely “political.” Rather, the category “religion” and its binary opposition, “secular,” is not suitable for Taiping. A key point related to this argument is the revolutionary violence against the Manchu government, which inherited the traditional “Heavenly Mandate” model. From an internal, theological perspective, anti-Manchu was ordained and commanded by the Heavenly Father. Manchu, as a regime, was standing as a hindrance in the path toward God. Besides, Manchu was not only viewed as a regime, but they were also “demons.” Therefore, the paper examines how Manchus were dehumanized in Taiping’s writings and were situated outside of the consideration of nonviolent and love. Manchu as a regime and Manchu as demons are in a dynamic relationship. As a regime, the Manchu government was preventing Chinese people from worshipping the Heavenly Father, so they were demonized. As they were demons, killing Manchus during the revolt was justified and not viewed as being contradicted the universal love among human beings.

Keywords: anti-manchu, demon-slaying, heavenly mandate, religion and violence, the taiping movement.

Procedia PDF Downloads 52

Authors: Hanna Abbo, Siyasanga Noganta, Salam Titinchi

Abstract:

The global lack of clean water for human sanitation and other purposes has become an emerging dilemma for human beings. The presence of organic pollutants in wastewater produced by textile industries, leather manufacturing and chemical industries is an alarming matter for a safe environment and human health. For the last decades, conventional methods have been applied for the purification of water but due to industrialization these methods fall short. Advanced oxidation processes and their reliable application in degradation of many contaminants have been reported as a potential method to reduce and/or alleviate this problem. Lately it has been assumed that incorporation of some metal nanoparticles such as magnetite nanoparticles as photocatalyst for Fenton reaction which could improve the degradation efficiency of contaminants. Core/shell nanoparticles, are extensively studied because of their wide applications in the biomedical, drug delivery, electronics fields and water treatment. The current study is centred on the synthesis of silver-doped Fe3O4/SiO2/TiO2 photocatalyst. Magnetically separable Fe3O4@SiO2@TiO2 composite with core–shell structure were synthesized by the deposition of uniform anatase TiO2 NPs on Fe3O4@SiO2 by using titanium butoxide (TBOT) as titanium source. Then, the silver is doped on SiO2 layer by hydrothermal method. Integration of magnetic nanoparticles was suggested to avoid the post separation difficulties associated with the powder form of the TiO2 catalyst, increase of the surface area and adsorption properties. The morphology, structure, composition, and magnetism of the resulting composites were characterized and their photocatalytic activities were also evaluated. The results demonstrate that TiO2 NPs were uniformly deposited on the Fe3O4@SiO2 surface. The silver nanoparticles were also uniformly distributed on the surface of TiO2 nanoparticles. The aim of this work is to study the suitability of photocatalysis for the treatment of aqueous streams containing organic pollutants such as methylene blue which is selected as a model compound to represent one of the pollutants existing in wastewaters. Various factors such as initial pollutant concentration, photocatalyst dose and wastewater matrix were studied for their effect on the photocatalytic degradation of the organic model pollutants using the as synthesized catalysts and compared with the commercial titanium dioxide (Aeroxide P25). Photocatalysis was found to be a potential purification method for the studied pollutant also in an industrial wastewater matrix with the removal percentages of over 81 % within 15 minutes. Methylene blue was removed most efficiently and its removal consumed the least of energy in terms of the specific applied energy. The magnetic Ag/SiO2/TiO2 composites show high photocatalytic performance and can be recycled three times by magnetic separation without major loss of activity, which meant that they can be used as efficient and conveniently renewable photocatalyst.

Keywords: Magnetite nanoparticles, Titanium, Photocatalyst, Organic pollutant, Water treatment

Procedia PDF Downloads 239

Authors: Cristina Opris, Bogdan Cojocaru, Madalina Tudorache, Simona M. Coman, Vasile I. Parvulescu, Camelia Bala, Bahir Duraki, Jeroen A. Van Bokhoven

Abstract:

The tremendous achievements in the development of the society concretized by more sophisticated materials and systems are merely based on non-renewable resources. Consequently, after more than two centuries of intensive development, among others, we are faced with the decrease of the fossil fuel reserves, an increased impact of the greenhouse gases on the environment, and economic effects caused by the fluctuations in oil and mineral resource prices. The use of biomass may solve part of these problems, and recent analyses demonstrated that from the perspective of the reduction of the emissions of carbon dioxide, its valorization may bring important advantages conditioned by the usage of genetic modified fast growing trees or wastes, as primary sources. In this context, the abundance and complex structure of lignin may offer various possibilities of exploitation. However, its transformation in fuels or chemicals supposes a complex chemistry involving the cleavage of C-O and C-C bonds and altering of the functional groups. Chemistry offered various solutions in this sense. However, despite the intense work, there are still many drawbacks limiting the industrial application. Thus, the proposed technologies considered mainly homogeneous catalysts meaning expensive noble metals based systems that are hard to be recovered at the end of the reaction. Also, the reactions were carried out in organic solvents that are not acceptable today from the environmental point of view. To avoid these problems, the concept of this work was to investigate the synthesis of superparamagnetic core shell catalysts for the fragmentation of lignin directly in the aqueous phase. The magnetic nanoparticles were covered with a nanoshell of an oxide (niobia) with a double role: to protect the magnetic nanoparticles and to generate a proper (acidic) catalytic function and, on this composite, cobalt nanoparticles were deposed in order to catalyze the C-C bond splitting. With this purpose, we developed a protocol to prepare multifunctional and magnetic separable nano-composite Co@Nb2O5@Fe3O4 catalysts. We have also established an analytic protocol for the identification and quantification of the fragments resulted from lignin depolymerization in both liquid and solid phase. The fragmentation of various lignins occurred on the prepared materials in high yields and with very good selectivity in the desired fragments. The optimization of the catalyst composition indicated a cobalt loading of 4wt% as optimal. Working at 180 oC and 10 atm H2 this catalyst allowed a conversion of lignin up to 60% leading to a mixture containing over 96% in C20-C28 and C29-C37 fragments that were then completely fragmented to C12-C16 in a second stage. The investigated catalysts were completely recyclable, and no leaching of the elements included in the composition was determined by inductively coupled plasma optical emission spectrometry (ICP-OES).

Keywords: superparamagnetic core-shell catalysts, environmental production of fuels, renewable lignin, recyclable catalysts

Procedia PDF Downloads 305