Search results for: transform matrix

Authors: L. Khoshnevisan, H. R. Momeni, A. Ashraf-Modarres

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One of the robust fault detection filter (RFDF) designing method is based on sliding-mode theory. The main purpose of our study is to introduce an innovative simplified reference residual model generator to formulate the RFDF as a sliding-mode observer without any manipulation package or transformation matrix, through which the generated residual signals can be evaluated. So the proposed design is more explicit and requires less design parameters in comparison with approaches requiring changing coordinates. To the best author's knowledge, this is the first time that the sliding mode technique is applied to detect actuator and sensor faults in a real boiler. The designing procedure is proposed in a drum boiler in Synvendska Kraft AB Plant in Malmo, Sweden as a multivariable and strongly coupled system. It is demonstrated that both sensor and actuator faults can robustly be detected. Also sensor faults can be diagnosed and isolated through this method.

Keywords: Boiler, fault detection, robustness, simplified sliding-mode observer.

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled direct normal irradiance field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: Artificial Neural Networks, Resilient Propagation, Solar Radiation, Time Series Forecasting.

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Authors: Bhim Singh

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Due to increased pressure from global competitors, manufacturing organizations are switching over to lean philosophies from traditional mass production. Lean manufacturing is a manufacturing philosophy which focuses on elimination of various types of wastes and creates maximum value for the end customers. Lean thinking aims to produce high quality products and services at the lowest possible cost with maximum customer responsiveness. Indian Industry is facing lot of problems in this transformation from traditional mass production to lean production. Through this paper an attempt has been made to identify various lean implementation hurdles in Indian industries with the help of a structured survey. Identified hurdles are grouped with the help of factor analysis and rated by calculating descriptive statistics. To show the effect of lean implementation hurdles a hypothesis “Organizations having higher level of lean implementation hurdles will have poor (negative) performance” has been postulated and tested using correlation matrix between performance parameters of the organizations and identified hurdles. The findings of the paper will be helpful to prepare road map to identify and eradicate the lean implementation hurdles.

Keywords: Factor analysis, global competition, lean implementation and lean hurdles.

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Authors: A. M. Fahim, G. Saake, A. M. Salem, F. A. Torkey, M. A. Ramadan

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Data clustering is an important data exploration technique with many applications in data mining. We present an enhanced version of the well known single link clustering algorithm. We will refer to this algorithm as DCBOR. The proposed algorithm alleviates the chain effect by removing the outliers from the given dataset. So this algorithm provides outlier detection and data clustering simultaneously. This algorithm does not need to update the distance matrix, since the algorithm depends on merging the most k-nearest objects in one step and the cluster continues grow as long as possible under specified condition. So the algorithm consists of two phases; at the first phase, it removes the outliers from the input dataset. At the second phase, it performs the clustering process. This algorithm discovers clusters of different shapes, sizes, densities and requires only one input parameter; this parameter represents a threshold for outlier points. The value of the input parameter is ranging from 0 to 1. The algorithm supports the user in determining an appropriate value for it. We have tested this algorithm on different datasets contain outlier and connecting clusters by chain of density points, and the algorithm discovers the correct clusters. The results of our experiments demonstrate the effectiveness and the efficiency of DCBOR.

Keywords: Data Clustering, Clustering Algorithms, Handling Noise, Arbitrary Shape of Clusters.

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Authors: Viriyavudh Sim, Jung Kyu Choi, Yong Ju Kwak, Oh Hyeon Jeon, Woo Young Jung

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In this study, we investigated the buckling performance of basalt fiber reinforced polymer (BFRP) sandwich infill panels. Fiber Reinforced Polymer (FRP) is a major evolution for energy dissipation when used as infill material of frame structure, a basic Polymer Matrix Composite (PMC) infill wall system consists of two FRP laminates surrounding an infill of foam core. Furthermore, this type of component is for retrofitting and strengthening frame structure to withstand the seismic disaster. In-plane compression was considered in the numerical analysis with ABAQUS platform to determine the buckling failure load of BFRP infill panel system. The present result shows that the sandwich BFRP infill panel system has higher resistance to buckling failure than those of glass fiber reinforced polymer (GFRP) infill panel system, i.e. 16% increase in buckling resistance capacity.

Keywords: Basalt fiber reinforced polymer, buckling performance, FEM analysis, sandwich infill panel.

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Authors: Lara Alam, Laetitia Van-Schoors, Olivier Sicot, Benoit Piezel, Shahram Aivazzadeh

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Over the last decades, worldwide environmental awareness has grown due to the depletion of raw material resources and global warming. This awareness has prompted the development of new products more environmentally friendly. Among these products are biocomposite materials reinforced with natural fibers. The main challenge in developing the use of biocomposites in exterior applications is the lack of knowledge about their durability and the evolution of their mechanical and physicochemical properties in the long term. The aim of this work is to study the photooxidation of unidirectional (UD) composites based on recycled matrix. For this purpose, UD flax fiber composites based on recycled polypropylene were prepared by thermocompression. An accelerated aging test was carried out using a xenon arc WeatherOmeter. The consequences of UV exposure on the chemical composition and morphology of the surface of composites as well as on their tensile mechanical properties have been reported. The results showed that accelerated aging had a significant effect on the surface of these composites while it had little impact on their mechanical properties.

Keywords: Flax fiber, photooxidation, physico-chemical properties, recycled polypropylene, tensile properties.

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Authors: K. Arroudj, M. Lanez, M. N. Oudjit

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The introduction of siliceous mineral additions in cement production allows, in addition to the ecological and economic gain, improvement of concrete performance. This improvement is mainly due to the fixing of Portlandite, released during the hydration of cement, by fine siliceous, forming denser calcium silicate hydrates and therefore a more compact cementitious matrix. This research is part of the valuation of the Dune Sand (DS) in the cement industry in Algeria. The high silica content of DS motivated us to study its effect, at ground state, on the properties of mortars in fresh and hardened state. For this purpose, cement pastes and mortars based on ground dune sand (fine quartz) has been analyzed with a replacement to cement of 15%, 20% and 25%. This substitution has reduced the amount of heat of hydration and avoids any risk of initial cracking. In addition, the grinding of the dune sand provides amorphous thin populations adsorbed at the surface of the crystal particles of quartz. Which gives to ground quartz pozzolanic character. This character results an improvement of mechanical strength of mortar (66 MPa in the presence of 25% of ground quartz).

Keywords: Mineralogical structure, Pozzolanic reactivity, quartz, mechanical strength.

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Authors: Vasiliki Vlachou, Christos Kontzinos, Ourania Markaki, Panagiotis Kokkinakos, Vagelis Karakolis, John Psarras

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Higher Education is resisting the pull of technology, especially as this concerns the issuance and verification of degrees and certificates. It is widely known that education certificates are largely produced in paper form making them vulnerable to damage while holders of such certificates are dependent on the universities and other issuing organisations. QualiChain is an EU Horizon 2020 (H2020) research project aiming to transform and revolutionise the domain of public education and its ties with the job market by leveraging blockchain, analytics and decision support to develop a platform for the verification and sharing of education certificates. Blockchain plays an integral part in the QualiChain solution in providing a trustworthy environment to store, share and manage such accreditations. Under the context of this paper, three prominent blockchain platforms (Ethereum, Hyperledger Fabric, Hyperledger Iroha) were considered as a means of experimentation for creating a system with the basic functionalities that will be needed for trustworthy degree verification. The methodology and respective system developed and presented in this paper used Hyperledger Iroha and proved that this specific platform can be used to easily develop decentralize applications. Future papers will attempt to further experiment with other blockchain platforms and assess which has the best potential.

Keywords: Blockchain, degree verification, higher education certificates, Hyperledger Iroha.

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Authors: M. Parva, K. Dola, F. Pour Rahimian

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Earthquake is considered as one of the most catastrophic disasters in Iran, in terms of both short-term and long-term hazards. Due to the particular financial and time constraints in Iran, quickly constructed post-earthquake houses (PEHs) do not fulfill the minimum requirements to be considered as comfortable dwellings for people. Consequently, people often transform PEHs after they start to reside. However, lack of understanding about process, motivation, and results of housing transformation leads to construction of some houses not suitable for future transformations, hence resulting in eventually demolished or abandoned PEHs. This study investigated housing transformations in a natural bed of post-earthquake Lar. This paper reports results of the conducted survey for comparing normal condition housing transformation with post-earthquake housing transformation in order to reveal the factors that affect post-earthquake housing transformation in Iran. The findings proposed the use of a combination of ‘Temporary’ and ‘Permanent’ housing reconstruction models in Iran to provide victims with basic but permanent post-disaster dwellings. It is also suggested that needs for future transformation should be predicted and addressed during early stages of design and development. This study contributes to both research and practice regarding post-earthquake housing reconstruction in Iran by proposing new design approaches and guidelines.

Keywords: Housing transformation, Iran, Lar, post-earthquake housing.

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Authors: M. Ravindra, R. Srinivasa Rao, V. Shanmukha Naga Raju

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This paper presents state estimation with Phasor Measurement Unit (PMU) allocation to obtain complete observability of network. A matrix is designed with modeling of zero injection constraints to minimize PMU allocations. State estimation algorithm is developed with optimal allocation of PMUs to find accurate states of network. The incorporation of PMU into traditional state estimation process improves accuracy and computational performance for large power systems. The nonlinearity integrated with zero injection (ZI) constraints is remodeled to linear frame to optimize number of PMUs. The problem of optimal PMU allocation is regarded with modeling of ZI constraints, PMU loss or line outage, cost factor and redundant measurements. The proposed state estimation with optimal PMU allocation has been compared with traditional state estimation process to show its importance. MATLAB programming on IEEE 14, 30, 57, and 118 bus networks is implemented out by Binary Integer Programming (BIP) method and compared with other methods to show its effectiveness.

Keywords: Observability, phasor measurement units, synchrophasors, SCADA measurements, zero injection bus.

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Authors: Chen Wu, Jingyu Yang

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Using maximal consistent blocks of tolerance relation on the universe in incomplete decision table, the concepts of join block and meet block are introduced and studied. Including tolerance class, other blocks such as tolerant kernel and compatible kernel of an object are also discussed at the same time. Upper and lower approximations based on those blocks are also defined. Default definite decision rules acquired from incomplete decision table are proposed in the paper. An incremental algorithm to update default definite decision rules is suggested for effective mining tasks from incomplete decision table into which data is appended. Through an example, we demonstrate how default definite decision rules based on maximal consistent blocks, join blocks and meet blocks are acquired and how optimization is done in support of discernibility matrix and discernibility function in the incomplete decision table.

Keywords: rough set, incomplete decision table, maximalconsistent block, default definite decision rule, join and meet block.

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Authors: Abdelaziz Zaidi, Belkacem Ould Bouamama, Moncef Tagina

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Bond Graph as a unified multidisciplinary tool is widely used not only for dynamic modelling but also for Fault Detection and Isolation because of its structural and causal proprieties. A binary Fault Signature Matrix is systematically generated but to make the final binary decision is not always feasible because of the problems revealed by such method. The purpose of this paper is introducing a methodology for the improvement of the classical binary method of decision-making, so that the unknown and identical failure signatures can be treated to improve the robustness. This approach consists of associating the evaluated residuals and the components reliability data to build a Hybrid Bayesian Network. This network is used in two distinct inference procedures: one for the continuous part and the other for the discrete part. The continuous nodes of the network are the prior probabilities of the components failures, which are used by the inference procedure on the discrete part to compute the posterior probabilities of the failures. The developed methodology is applied to a real steam generator pilot process.

Keywords: Redundancy relations, decision-making, Bond Graph, reliability, Bayesian Networks.

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Authors: B. Tah, P. Pal, M. Mahato, R. Sarkar, G. B. Talapatra

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Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.

Keywords: Air/water interface, Catanionic micelle, Insulin, Langmuir-Blodgett film

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Authors: Muhammad Kashif Siddiq, Fang Jian Cheng, Yu Wen Bo

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State-dependent Riccati equation based controllers are becoming increasingly popular because of having attractive properties like optimality, stability and robustness. This paper focuses on the design of a roll autopilot for a fin stabilized and canard controlled 122mm artillery rocket using state-dependent Riccati equation technique. Initial spin is imparted to rocket during launch and it quickly decays due to straight tail fins. After the spin phase, the roll orientation of rocket is brought to zero with the canard deflection commands generated by the roll autopilot. Roll autopilot has been developed by considering uncoupled roll, pitch and yaw channels. The canard actuator is modeled as a second-order nonlinear system. Elements of the state weighing matrix for Riccati equation have been chosen to be state dependent to exploit the design flexibility offered by the Riccati equation technique. Simulation results under varying conditions of flight demonstrate the wide operating range of the proposed autopilot.

Keywords: Fin stabilized 122mm artillery rocket, Roll Autopilot, Six degree of freedom trajectory model, State-dependent Riccati equation.

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Authors: L. Bennaceur Farah, I. R. Farah, R. Bennaceur, Z. Belhadj, M. R. Boussema

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The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

Keywords: Remote sensing, rough surfaces, inverse problems, SAR, radar scattering, Neural networks and Fractals.

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Authors: M. A Anjum, M. Y. Javed, A. Basit

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In this paper a new approach to face recognition is presented that achieves double dimension reduction making the system computationally efficient with better recognition results. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results improve with increase in face image resolution and levels off when arriving at a certain resolution level. In the proposed model of face recognition, first image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to better computational speed and feature extraction potential of Discrete Cosine Transform (DCT) it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A trade of between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL database, Yale database and a color database. The proposed technique has performed much better compared to other techniques. The significance of the model is two fold: (1) dimension reduction up to an effective and suitable face image resolution (2) appropriate DCT coefficients are retained to achieve best recognition results with varying image poses, intensity and illumination level.

Keywords: Biometrics, DCT, Face Recognition, Feature extraction.

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Authors: Jianzheng Wei, Duo Zhen, Zhihan Yang, Huifeng Tan

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The deployable descent technology is a lightweight entry method using an inflatable heat shield. The heatshield consists of a pressurized core which is covered by different layers of thermal insulation and flexible ablative materials in order to protect against the thermal loads. In this paper, both aluminum and silicon-aluminum aerogels were prepared by freeze-drying method. The latter material has bigger specific surface area and nano-scale pores. Mullite fibers are used as the reinforcing fibers to prepare the aerogel matrix to improve composite flexibility. The flexible composite materials were performed as an insulation layer to an underlying aramid fabric by a thermal shock test at a heat flux density of 120 kW/m² and uniaxial tensile test. These results show that the aramid fabric with untreated mullite fibers as the thermal protective layer is completely carbonized at the heat of about 60 s. The aramid fabric as a thermal resistance layer of the composite material still has good mechanical properties at the same heat condition.

Keywords: Aerogel, aramid fabric, flexibility, thermal resistance.

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Authors: A. Sivakumar, K. Srinivasan

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The main objective of the study is focused in producing slag based geopolymer concrete obtained with the addition of alkali activator. Test results indicated that the reaction of silicates in slag is based on the reaction potential of sodium hydroxide and the formation of alumino-silicates. The study also comprises on the evaluation of the efficiency of polymer reaction in terms of the strength gain properties for different geopolymer mixtures. Geopolymer mixture proportions were designed for different binder to total aggregate ratio (0.3 & 0.45) and fine to coarse aggregate ratio (0.4 & 0.8). Geopolymer concrete specimens casted with normal curing conditions reported a maximum 28 days compressive strength of 54.75 MPa. The addition of glued steel fibres at 1.0% Vf in geopolymer concrete showed reasonable improvements on the compressive strength, split tensile strength and flexural properties of different geopolymer mixtures. Further, comparative assessment was made for different geopolymer mixtures and the reinforcing effects of steel fibres were investigated in different concrete matrix.

Keywords: Accelerators, Alkali activators, Geopolymer, Hot air oven curing, Polypropylene fibres, Slag, Steam curing, Steel fibres.

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Authors: Srinivasa C. V., Bharath K. N.

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Natural fibers are considered to have potential use as reinforcing agents in polymer composite materials because of their principal benefits: moderate strength and stiffness, low cost, and being an environmental friendly, degradable, and renewable material. A study has been carried out to evaluate impact properties of composites made by areca fibers reinforced urea formaldehyde, melamine urea formaldehyde and epoxy resins. The extracted areca fibers from the areca husk were alkali treated with potassium hydroxide (KOH) to obtain better interfacial bonding between fiber and matrix. Then composites were produced by means of compression molding technique with varying process parameters, such as fiber condition (untreated and alkali treated), and fiber loading percentages (50% and 60% by weight). The developed areca fiber reinforced composites were then characterized by impact test. The results show that, impact strength increase with increase in the loading percentage. It is observed that, treated areca fiber reinforcement increases impact strength when compared to untreated areca fiber reinforcement.

Keywords: Lignocellulosic Fibers Composites, Areca Fibers, Alkali Treatment, Impact Strength.

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Authors: Renzo Carta, Mario Cruccu, Francesco Desogus

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This work presents the experimental results obtained at a pilot plant which works with a slow, wet and catalytic pyrolysis process of dry fowl manure. This kind of process mainly consists in the cracking of the organic matrix and in the following reaction of carbon with water, which is either already contained in the organic feed or added, to produce carbon monoxide and hydrogen. Reactions are conducted in a rotating reactor maintained at a temperature of 500°C; the required amount of water is about 30% of the dry organic feed. This operation yields a gas containing about 59% (on a volume basis) of hydrogen, 17% of carbon monoxide and other products such as light hydrocarbons (methane, ethane, propane) and carbon monoxide in lesser amounts. The gas coming from the reactor can be used to produce not only electricity, through internal combustion engines, but also heat, through direct combustion in industrial boilers. Furthermore, as the produced gas is devoid of both solid particles and pollutant species (such as dioxins and furans), the process (in this case applied to fowl manure) can be considered as an optimal way for the disposal and the contemporary energetic valorization of organic materials, in such a way that is not damaging to the environment.

Keywords: Brushwood, fowl manure, kenaf, pilot plant, pyrolysis, pyrolysis gas.

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Authors: Mohamed Eldessouki, Ebraheem Shady, Yasser Gowayed

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Carbon nanotubes (CNTs) are known for having high elastic properties with high surface area that promote them as good candidates for reinforcing polymeric matrices. In composite materials, CNTs lack chemical bonding with the surrounding matrix which decreases the possibility of better stress transfer between the components. In this work, a chemical treatment for activating the surface of the multi-wall carbon nanotubes (MWCNT) was applied and the effect of this functionalization on the elastic properties of the epoxy nanocomposites was studied. Functional amino-groups were added to the surface of the CNTs and it was evaluated to be about 34% of the total weight of the CNTs. Elastic modulus was found to increase by about 40% of the neat epoxy resin at CNTs’ weight fraction of 0.5%. The elastic modulus was found to decrease after reaching a certain concentration of CNTs which was found to be 1% wt. The scanning electron microscopic pictures showed the effect of the CNTs on the crack propagation through the sample by forming stress concentrated spots at the nanocomposite samples.

Keywords: Carbon nanotubes functionalization, crack propagation, elastic modulus, epoxy nanocomposites.

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Authors: Chen-Fu Wang, Lin-Ya Kung

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For traditional painting materials, the artisan used to combine the pigments with different binders to create colors. As time goes by, the materials used for painting evolved from natural to chemical materials. The vast variety of ingredients used in chemical materials has complicated restoration work; it makes conservation work more difficult. Conservation work also becomes harder when the materials cannot be easily identified; therefore, it is essential that we take a more scientific approach to assist in conservation work. Paintings materials are high molecular weight polymer, and their analysis is very complicated as well other contamination such as smoke and dirt can also interfere with the analysis of the material. The current methods of composition analysis of painting materials include Fourier transform infrared spectroscopy (FT-IR), mass spectrometer, Raman spectroscopy, X-ray diffraction spectroscopy (XRD), each of which has its own limitation. In this study, FT-IR was used to analyze the components of the paint coating. We have taken the most commonly seen materials as samples and deteriorated it. The aged information was then used for the database to exam the temple painting materials. By observing the FT-IR changes over time, we can tell all of the painting materials will be deteriorated by the UV light, but only the speed of its degradation had some difference. From the deterioration experiment, the acrylic resin resists better than the others. After collecting the painting materials aging information on FT-IR, we performed some test on the paintings on the temples. It was found that most of the artisan used tune-oil for painting materials, and some other paintings used chemical materials. This method is now working successfully on identifying the painting materials. However, the method is destructive and high cost. In the future, we will work on the how to know the painting materials more efficiently.

Keywords: Temple painting, painting material, conservation, FT-IR.

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Authors: Z.A. Rasid, R. Zahari, A. Ayob, D.L. Majid, A.S.M. Rafie

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Aerospace vehicles are subjected to non-uniform thermal loading that may cause thermal buckling. A study was conducted on the thermal post-buckling of shape memory alloy composite plates subjected to the non-uniform tent-like temperature field. The shape memory alloy wires were embedded within the laminated composite plates to add recovery stress to the plates. The non-linear finite element model that considered the recovery stress of the shape memory alloy and temperature dependent properties of the shape memory alloy and composite matrix along with its source codes were developed. It was found that the post-buckling paths of the shape memory alloy composite plates subjected to various tentlike temperature fields were stable within the studied temperature range. The addition of shape memory alloy wires to the composite plates was found to significantly improve the post-buckling behavior of laminated composite plates under non-uniform temperature distribution.

Keywords: Post-buckling, shape memory alloy, temperaturedependent property, tent-like temperature distribution

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Authors: M. Bagci, H. Imrek, Omari M. Khalfan

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Materials added to the matrix help improving operating properties of a composite. This experimental study has targeted to investigate this aim where Silicon Oxide particles were added to glass fibre and epoxy resin at an amount of 15% to the main material to obtain a sort of new composite material. Erosive wear behavior of epoxy-resin dipped composite materials reinforced with glass fibre and Silicon Oxide under three different impingement angles (30°, 60° and 90°), three different impact velocities (23, 34 and 53 m/s), two different angular Aluminum abrasive particle sizes (approximately 200 and 400 μm) and the fibre orientation of 45° (45/-45) were investigated. In the test results, erosion rates were obtained as functions of impingement angles, impact velocities, particle sizes and fibre orientation. Moreover, materials with addition of Silicon Oxide filler material exhibited lower wear as compared to neat materials with no added filler material. In addition, SEM views showing worn out surfaces of the test specimens were scrutinized.

Keywords: Erosive wear, fibre orientation, GF/EP, silicon oxide.

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Authors: Harpreet Kaur, Vinod Mishra, R. C. Mittal

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In this paper, we have proposed a Haar wavelet quasilinearization method to solve the well known Blasius equation. The method is based on the uniform Haar wavelet operational matrix defined over the interval [0, 1]. In this method, we have proposed the transformation for converting the problem on a fixed computational domain. The Blasius equation arises in the various boundary layer problems of hydrodynamics and in fluid mechanics of laminar viscous flows. Quasi-linearization is iterative process but our proposed technique gives excellent numerical results with quasilinearization for solving nonlinear differential equations without any iteration on selecting collocation points by Haar wavelets. We have solved Blasius equation for 1≤α ≤ 2 and the numerical results are compared with the available results in literature. Finally, we conclude that proposed method is a promising tool for solving the well known nonlinear Blasius equation.

Keywords: Boundary layer Blasius equation, collocation points, quasi-linearization process, uniform haar wavelets.

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Authors: Sumathi Poobal, G. Ravindran

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Image compression is one of the most important applications Digital Image Processing. Advanced medical imaging requires storage of large quantities of digitized clinical data. Due to the constrained bandwidth and storage capacity, however, a medical image must be compressed before transmission and storage. There are two types of compression methods, lossless and lossy. In Lossless compression method the original image is retrieved without any distortion. In lossy compression method, the reconstructed images contain some distortion. Direct Cosine Transform (DCT) and Fractal Image Compression (FIC) are types of lossy compression methods. This work shows that lossy compression methods can be chosen for medical image compression without significant degradation of the image quality. In this work DCT and Fractal Compression using Partitioned Iterated Function Systems (PIFS) are applied on different modalities of images like CT Scan, Ultrasound, Angiogram, X-ray and mammogram. Approximately 20 images are considered in each modality and the average values of compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the reconstructed image is arrived by the PSNR values. Based on the results it can be concluded that the DCT has higher PSNR values and FIC has higher compression ratio. Hence in medical image compression, DCT can be used wherever picture quality is preferred and FIC is used wherever compression of images for storage and transmission is the priority, without loosing picture quality diagnostically.

Keywords: DCT, FIC, PIFS, PSNR.

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Authors: Rami N. Khushaba, Adel Al-Jumaily

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The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

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Authors: Dehong Li, Yuchen Chen, Alireza Kaboorani, Denis Rodrigue, Xiaodong (Alice) Wang

Abstract:

Utilizing solar energy for thermal energy storage has emerged as an appealing option for lowering the amount of energy that is consumed by buildings. Due to their high heat storage density, non-corrosive and non-polluting properties, alcohols can be a good alternative to petroleum-derived paraffin phase change materials (PCMs). In this paper, ternary eutectic PCMs with suitable phase change temperatures were designed and prepared using lauryl alcohol (LA), cetyl alcohol (CA), stearyl alcohol (SA) and xylitol (X). The Differential Scanning Calorimetry (DSC) results revealed that the phase change temperatures of LA-CA-SA, LA-CA-X, and LA-SA-X were 20.52 °C, 20.37 °C, and 22.18 °C, respectively. The latent heat of phase change of the ternary eutectic PCMs were all stronger than that of the paraffinic PCMs at roughly the same temperature. The highest latent heat was 195 J/g. It had good thermal energy storage capacity. The preparation mechanism was investigated using Fourier-transform Infrared Spectroscopy (FTIR), and it was found that the ternary eutectic PCMs were only physically mixed among the components. Ternary eutectic PCMs had a simple preparation process, suitable phase change temperature, and high energy storage density. They are suitable for low-temperature architectural packaging applications.

Keywords: Thermal energy storage, buildings, phase change materials, alcohols.

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Authors: Sulaiman A. Alateyah, Richard M Crowder, Gary B Wills

Abstract:

This paper discusses E-government, in particular the challenges that face adoption in Saudi Arabia. E-government can be defined based on an existing set of requirements. In this research we define E-government as a matrix of stakeholders: governments to governments, governments to business and governments to citizens, using information and communications technology to deliver and consume services. E-government has been implemented for a considerable time in developed countries. However, E-government services still face many challenges in their implementation and general adoption in many countries including Saudi Arabia. It has been noted that the introduction of E-government is a major challenge facing the government of Saudi Arabia, due to possible concerns raised by its citizens. In addition, the literature review and the discussion identify the influential factors that affect the citizens’ intention to adopt E-government services in Saudi Arabia. Consequently, these factors have been defined and categorized followed by an exploratory study to examine the importance of these factors. Therefore, this research has identified factors that determine if the citizen will adopt E-government services and thereby aiding governments in accessing what is required to increase adoption.

Keywords: E-government, adoption, factors, G2C, intention, citizens’ intention, influential factors.

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Authors: Mohammad Reza Karami Nejad

Abstract:

A hybrid learning automata-genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP-Complete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.

Keywords: Routing, Quality of Service, Multicaset, Learning Automata, Genetic, Next Generation Networks.

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