Search results for: e-content producing algorithm

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Aichun Feng, Zhi-Min Chen, Jing Tang Xing

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A two-dimensional linear wave-body interaction problem can be solved using a desingularized integral method by placing free surface Rankine sources over calm water surface and satisfying boundary conditions at prescribed collocation points on the calm water surface. A new free-surface Rankine source distribution scheme, determined by the intersection points of free surface and body surface, is developed to reduce numerical computation cost. Associated with this, a new treatment is given to the intersection point. The present scheme results are in good agreement with traditional numerical results and measurements.

Keywords: source point distribution, panel method, Rankine source, desingularized algorithm

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Authors: Mohammad K. Parvez, Mohammed S. Al-Dosari

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Hepatitis E virus (HEV) is an emerging RNA virus that causes acute and chronic liver disease with a global mortality rate of about 2%. Despite milestone developments in understanding of HEV biology, there is still lack of a robust culture system or animal model. Therefore, in a novel approach, two recombinant-baculoviruses (vBac-ORF2 and vBac-ORF3) that could overexpress HEV ORF2 (structural/capsid) and ORF3 (nonstructural/regulatory) proteins, respectively were constructed. The established HEV-SAR55 (genotype 1) replicon that contained GFP gene, in place of ORF2/ORF3 sequences was in vitro transcribed, and GFP production in RNA transfected S10-3 cells was scored by FACS. Enhanced infectivity, if any, of nascent virions produced by exogenously-supplied ORF2 and viral RNA by co-expression of ORF3 was tested on naïve HepG2 cells. Co-transduction with vBac-ORF2/vBac-ORF3 (108 pfu/microL) produced high amounts of native ORF2/ORF3 in approximately 60% of S10-3 cells, determined by immunofluorescence microscopy and Western analysis. FACS analysis showed about 9% GFP positivity of S10-3 cells on day6 post-transfection (i.e, day5 post-transduction). Further, FACS scoring indicated that lysates from S10-3 cultures receiving the RNA plus vBac-ORF2 were capable of producing HEV particles with about 4% infectivity in HepG2 cells. However, lysates of cultures co-transduced with vBac-ORF3, were found to further enhance virion infectivity by approximately 17%. This supported a previously proposed role of ORF3 as a minor-structural protein in HEV virion assembly and infectivity. In conclusion, the present model for efficient genomic RNA packaging and production of infectious virions could be a valuable tool to study various aspects of HEV molecular biology, in vitro.

Keywords: chronic liver disease, hepatitis E virus, ORF2, ORF3, replicon

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Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian

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In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.

Keywords: dispatching, solar ingot, simulation, flexsim

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Authors: Shu-Bo Yang, Wei Wu, Yuan-Heng Liu

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This research aims to design a heat-exchanger type of methanol reformer coupled with a preheating design in gPROMS® environment. The endothermic methanol steam reforming reaction (MSR) and the exothermic preferential oxidation reaction (PROX) occur in the inner tube and the outer tube of the reformer, respectively. The effective heat transfer manner between the inner and outer tubes is investigated. It is verified that the countercurrent-flow type reformer provides the higher hydrogen yield than the cocurrent-flow type. Since the hot spot temperature appears in the outer tube, an improved scheme is proposed to suppress the hot spot temperature by splitting the excess air flowing into two sites. Finally, an optimization algorithm for maximizing the hydrogen yield is employed to determine optimal operating conditions.

Keywords: methanol reformer, methanol steam reforming, optimization, simulation

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Authors: Boukhris Lahouari, Bouchetara Mostefa

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The active safety of a vehicle is mainly influenced by the properties of the installed braking system. With the increase in road traffic density and travel speeds, increasingly stringent requirements are placed on the vehicle's behaviour during braking. The achievable decelerations are limited by the physical aspect characterized by the coefficient of friction between the tires and the ground. As a result, it follows that an optimized distribution of braking forces becomes necessary for a better use of friction coefficients. This objective could only be achieved if sufficient knowledge is available on the theory of vehicle dynamics during braking and on current standards for the approval of braking systems. These will facilitate the development of a braking force calculation algorithm that will enable an optimized distribution of braking forces to be achieved. Operating safety is conditioned by the requirements of efficiency, progressiveness, regularity or fidelity of a braking system without obviously neglecting the recommendations imposed by the legislator.

Keywords: brake force distribution, distribution diagram, friction coefficient, brake by wire

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Authors: Yahya Al-Wahaibi, Saif Al-Bahry, Abdulkadir Elshafie, Ali Al-Bemani, Sanket Joshi

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Microbial enhanced oil recovery is one of the most economical and efficient methods for extending the life of production wells in a declining reservoir. There are a variety of metabolites produced by microorganisms that can be useful for oil recovery, like biopolymers-polysaccharides secreted by microbes, biodegradable thus environmentally friendly. Some fungi like Schizophyllum commune (a type of mushroom), and Aureobasidium pullulans are reported to produce biopolymers-schizophyllan and pullulan. Hence, we have procured a microbial strain (Schizophyllum commune) from American Type Culture Collection, which is reported for producing a biopolymer and also isolated several Omani strains of Aureobasidium pullulans from different samples. Studies were carried out for maintenance of the strains and primary screening of production media and environmental conditions for growth of S. commune and Omani A. pullulans isolates, for 30 days. The observed optimum growth and production temperature was ≤35 °C for S. commune and Omani A. pullulans isolates. Better growth was observed for both types of fungi under shaking conditions. The initial yield of lyophilized schizophyllan was ≥3.0 g/L, and the yield of pullulan was ≥0.5g/L. Both schizophyllan and pullulan were extracted in crude form and were partially identified by Fourier transform infrared spectroscopy (FTIR), which showed partial similarity in chemical structure with published biopolymers. The produced pullulan and schizophyllan increased the viscosity from 9-20 cp of the control media (without biopolymer) to 20 - 121.4 cp of the cell free broth at 0.1 s-1 shear rate at range of temperatures from 25–45 °C. Enhanced biopolymer production and its physicochemical and rheological properties under different environmental conditions (different temperatures, salt concentrations and wide range of pH), complete characterization and effects on oil recovery enhancement were also investigated in this study.

Keywords: Aureobasidium pullulans, biopolymer, oil recovery enhancement, Schizophyllum commune

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Authors: W. Schellong

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Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.

Keywords: crossover technologies, data management, energy analysis, energy efficiency, process control

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Authors: Arámbula-Villa Gerónimo, García-Lara Kenia Y., Figueroa-Cárdenas J. D., Pérez-Robles J. F., Jiménez-Sandoval S., Salazar-López R., Herrera-Corredor J. A.

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The nixtamalization process (thermal-alkaline method) improves the nutritional part of the corn grain. In this process, the using of Ca(OH)₂ is basic, although the chemical mechanisms between this alkali and the carbohydrates (starch), proteins, lipids, and fiber have not been fully identified. In this study, the native corn starch was taken as a model, and it was subjected to cooking with different concentrations of lime (nixtamalization process) and specific studies of FTIR and XRD were carried out to identify the formation of chemical compounds, and the physical, physicochemical, rheological (paste) and structural properties of material obtained were determined. The FTIR spectra showed the formation of calcium-starch complexes. The treatments with Ca(OH)₂ showed a band shift towards 1675 cm⁻¹ and a band in 1436 cm⁻¹ (COO⁻), indicating the oxidation of starch. Three bands were identified (1575, 1550, and 1540 cm⁻¹) characteristics of carboxylic acid salts for three types of coordinated structures: monodentate, pseudo-bridged, and bidentate. The XRD spectra of starch treated with Ca(OH)₂ showed a peak corresponding to CaCO₃ (29.40°). The oxidation of starch was favored with low concentrations of Ca(OH)₂, producing carboxyl and carbonyl groups and increasing the residual CaCO₃. The increased concentration of Ca(OH)₂ showed the formation of calcium carboxylates, with a decrease in relative crystallinity and residual CaCO₃. Samples with low concentrations of Ca(OH)₂ slowed the onset of gelatinization and increased the swelling of the granules and the peak viscosity. The higher concentrations of Ca(OH)₂ difficulted the water absorption and decreased the viscosity rate and peak viscosity. These results can be used to improve the quality characteristics of the dough and tortillas and to get better acceptance by consumers.

Keywords: maize starch, nixtamalization, gelatinization, calcium carboxylates

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Authors: Houda Abadlia, Nadia Smairi, Khaled Ghedira

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Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Keywords: particle swarm optimization, migration, variable neighborhood search, multiobjective optimization

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Authors: M. Zaïgouche, A. Kouvahe, F. Stefanelli

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IMPERTIO is a high technology based project aiming at offering efficient assistance help in communication for persons affected by Cerebral Palsy. The systems currently available are hardly used by these patients who are not satisfied by ergonomics and response time. The project rests upon the concept that, opposite to usual master-slave communication giving power to the entity with larger range of possibilities, providing conversely the mastery to the entity with smaller range of possibilities will allow a better understanding ground for both parties. Entirely customizable, the application developed from this idea gives full freedom to the user. Through pictograms (one button linked to a word or a sentence) and adapted keyboard, noticeable improvements are brought to the response time and ease to use ergonomics.

Keywords: cerebral palsy, master-slave relation, communication interface, virtual keyboard, word construction algorithm

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Authors: Z. Zerdoumi, D. Benatia, , D. Chicouche

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This paper investigates the application of artificial neural network to the problem of nonlinear channel equalization. The difficulties caused by channel distortions such as inter symbol interference (ISI) and nonlinearity can overcome by nonlinear equalizers employing neural networks. It has been shown that multilayer perceptron based equalizer outperform significantly linear equalizers. We present a multilayer perceptron based equalizer with decision feedback (MLP-DFE) trained with the back propagation algorithm. The capacity of the MLP-DFE to deal with nonlinear channels is evaluated. From simulation results it can be noted that the MLP based DFE improves significantly the restored signal quality, the steady state mean square error (MSE), and minimum Bit Error Rate (BER), when comparing with its conventional counterpart.

Keywords: Artificial Neural Network, signal restoration, Nonlinear Channel equalization, equalization

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Authors: H. Katkhuda

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A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: dynamic force identification, dynamic responses, sub-structure, time domain

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Authors: M. Lloret-Climent, J. Nescolarde-Selva

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The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

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Authors: Slimane Souag, Amel Graa, Farid Benhamida

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In this paper we present a new method for solving the secured power flow problem by the economic dispatch using DC power flow method and Generation Shift Distribution Factor (GSDF), in this work we create a graphical interface in LabVIEW as a virtual instrument. Hence the dc power flow reduces the power flow problem to a set of linear equations, which make the iterative calculation very fast and the GSFD matrix present the effects of single and multiple generator MW change on the transmission line. The effectiveness of the method developed is identified through its application to an IEEE-14 bus test system. The calculation results show excellent performance of the proposed method, in regard to computation time and quality of results.

Keywords: electrical power system security, economic dispatch, sensitivity matrix, labview

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Authors: Sandra Cuenca, Danilo Santana, Anderson Reyes

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The following project is based on the manipulation of audio signals through the Matlab software, which has an audio signal that is modified, and its resultant obtained through the auxiliary port of the computer is passed through a signal amplifier whose amplified signal is connected to a tesla coil which has a behavior like a vumeter, the flashes at the output of the tesla coil increase and decrease its intensity depending on the audio signal in the computer and also the voltage source from which it is sent. The amplified signal then passes to the tesla coil being shown in the plasma sphere with the respective flashes; this activation is given through the specified parameters that we want to give in the MATLAB algorithm that contains the digital filters for the manipulation of our audio signal sent to the tesla coil to be displayed in a plasma sphere with flashes of the combination of colors commonly pink and purple that varies according to the tone of the song.

Keywords: auxiliary port, tesla coil, vumeter, plasma sphere

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Authors: Evar C. Umeozor, Experience I. Nduagu, Ian D. Gates

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The energy requirements of carbon dioxide utilization (CDU) technologies/processes are diverse, so also are their environmental footprints. This paper explores the energy and environmental impacts of systems for CO₂ conversion to fuels, chemicals, and materials. Energy needs of the technologies and processes deployable in CO₂ conversion systems are met by one or combinations of hydrogen (chemical), electricity, heat, and light. Likewise, the environmental footprint of any CO₂ utilization pathway depends on the systems involved. So far, evaluation of CDU systems has been constrained to particular energy source/type or a subset of the overall system needed to make CDU possible. This introduces limitations to the general understanding of the energy and environmental implications of CDU, which has led to various pitfalls in past studies. A CDU system has an energy source, CO₂ supply, and conversion units. We apply a holistic approach to consider the impacts of all components in the process, including various sources of energy, CO₂ feedstock, and conversion technologies. The electricity sources include nuclear power, renewables (wind and solar PV), gas turbine, and coal. Heat is supplied from either electricity or natural gas, and hydrogen is produced from either steam methane reforming or electrolysis. The CO₂ capture unit uses either direct air capture or post-combustion capture via amine scrubbing, where applicable, integrated configurations of the CDU system are explored. We demonstrate how the overall energy and environmental impacts of each utilization pathway are obtained by aggregating the values for all components involved. Proper accounting of the energy and emission intensities of CDU must incorporate total balances for the utilization process and differences in timescales between alternative conversion pathways. Our results highlight opportunities for the use of clean energy sources, direct air capture, and a number of promising CO₂ conversion pathways for producing methanol, ethanol, synfuel, urea, and polymer materials.

Keywords: carbon dioxide utilization, processes, energy options, environmental impacts

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Authors: O. Anan, D. Böhning, A. Maruotti

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The purpose of the study is to estimate the elusive target population size under a truncated count model that accounts for heterogeneity. The purposed estimator is based on the generalized Poisson distribution (GPD), which extends the Poisson distribution by adding a dispersion parameter. Thus, it becomes an useful model for capture-recapture data where concurrent events are not homogeneous. In addition, it can account for over-dispersion and under-dispersion. The ratios of neighboring frequency counts are used as a tool for investigating the validity of whether generalized Poisson or Poisson distribution. Since capture-recapture approaches do not provide the zero counts, the estimated parameters can be achieved by modifying the EM-algorithm technique for the zero-truncated generalized Poisson distribution. The properties and the comparative performance of proposed estimator were investigated through simulation studies. Furthermore, some empirical examples are represented insights on the behavior of the estimators.

Keywords: capture, recapture methods, ratio plot, heterogeneous population, zero-truncated count

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: Mohammadreza Nezamirad, Azadeh Yazdi, Sepideh Amirahmadian, Nasim Sabetpour, Amirmasoud Hamedi

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In this study, the Reynolds-Stress-Navier-Stokes framework is utilized to investigate the flow inside the diesel injector nozzle. The flow is assumed to be multiphase as the formation of vapor by pressure drop is visualized. For pressure and velocity linkage, the coupled algorithm is used. Since the cavitation phenomenon inherently is unsteady, the quasi-steady approach is utilized for saving time and resources in the current study. Schnerr-Sauer cavitation model is used, which was capable of predicting flow behavior both at the initial and final steps of the cavitation process. Two different turbulent models were used in this study to clarify which one is more capable in predicting cavitation inception and super-cavitation. It was found that K-ε was more compatible with the Shnerr-Sauer cavitation model; therefore, the mentioned model is used for the rest of this study.

Keywords: CFD, RANS, cavitation, fuel, injector

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Authors: M. Bouferhane, A. Boukhebza, L. Hatab

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In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.

Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control

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Authors: Vikram Prabhu, Mohammad Shikh Bahaei

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This paper depicts the implementation of a new infallible technique to protect an Unmanned Aerial Vehicle from cyber-attacks. An Unmanned Aerial Vehicle (UAV) could be vulnerable to cyber-attacks because of jammers or eavesdroppers over the network which pose as a threat to the security of the UAV. In the field of network security, there are quite a few protocols which can be used to establish a secure connection between UAVs and their Operators. In this paper, we discuss how the Interlock Protocol could be implemented to foil the Man-in-the-Middle Attack. In this case, Wireshark has been used as the sniffer (man-in-the-middle). This paper also shows a comparison between the Interlock Protocol and the TCP Protocols using cryptcat and netcat and at the same time highlights why the Interlock Protocol is the most efficient security protocol to prevent eavesdropping over the communication channel.

Keywords: interlock protocol, Diffie-Hellman algorithm, unmanned aerial vehicles, control station, man-in-the-middle attack, Wireshark

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Authors: Sony, Ashok N. Bhaskarwar

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Production of hydrogen from a renewable raw material without any co-synthesis of harmful greenhouse gases is the current need for sustainable energy solutions. The sulfur-iodine (SI) thermochemical cycle, using intermediate chemicals, is an efficient process for producing hydrogen at a much lower temperature than that required for the direct splitting of water. No net byproduct forms in the cycle. Hydrogen iodide (HI) decomposition is a crucial reaction in this cycle, as the product, hydrogen, forms only in this step. It is an endothermic, reversible, and equilibrium-limited reaction. The theoretical equilibrium conversion at 550°C is just a meagre of 24%. There is a growing interest, therefore, in enhancing the HI conversion to near-equilibrium values at lower reaction temperatures and by possibly improving the rate. The reaction is relatively slow without a catalyst, and hence catalytic decomposition of HI has gained much significance. Bi-metallic Ni-Co, Ni-Mn, Co-Mn, and tri-metallic Ni-Co-Mn catalysts over zirconia support were tested for HI decomposition reaction. The catalysts were synthesized via a sol-gel process wherein Ni was 3wt% in all the samples, and Co and Mn had equal weight ratios in the Co-Mn catalyst. Powdered X-ray diffraction and Brunauer-Emmett-Teller surface area characterizations indicated the polycrystalline nature and well-developed mesoporous structure of all the samples. The experiments were performed in a vertical laboratory-scale packed bed reactor made of quartz, and HI (55 wt%) was fed along with nitrogen at a WHSV of 12.9 hr⁻¹. Blank experiments at 500°C for HI decomposition suggested conversion of less than 5%. The activities of all the different catalysts were checked at 550°C, and the highest conversion of 23.9% was obtained with the tri-metallic 3Ni-Co-Mn-ZrO₂ catalyst. The decreasing order of the performance of catalysts could be expressed as: 3Ni-Co-Mn-ZrO₂ > 3Ni-2Co-ZrO₂ > 3Ni-2Mn-ZrO₂ > 2.5Co-2.5Mn-ZrO₂. The tri-metallic catalyst remained active till 360 mins at 550°C without any observable drop in its activity/stability. Among the explored catalyst compositions, the tri-metallic catalyst certainly has a better performance for HI conversion when compared to the bi-metallic ones. Owing to their low costs and ease of preparation, these trimetallic catalysts could be used for large-scale hydrogen production.

Keywords: sulfur-iodine cycle, hydrogen production, hydrogen iodide decomposition, bi-, and tri-metallic catalysts

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Authors: Yuriy A. Shevchenko, Konstantin V. Nefedev

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We consider the antiferromagnetic systems of Ising spins located at the sites of the hexagonal, triangular and pyrochlore lattices. Such systems can be diluted to a certain concentration level by randomly replacing the magnetic spins with nonmagnetic ones. Quite recently we studied density of states (DOS) was calculated by the Wang-Landau method. Based on the obtained data, we calculated the dependence of the residual entropy (entropy at a temperature tending to zero) on the dilution concentration for quite large systems (more than 2000 spins). In the current study, we obtained the same data for small systems (less than 20 spins) by a complete search of all possible magnetic configurations and compared the result with the result for large systems. The shape of the curve remains unchanged in both cases, but the specific values of the residual entropy are different because of the finite size effect.

Keywords: entropy, pyrochlore, spin ice, Wang-Landau algorithm

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Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao

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In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.

Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose

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Authors: Lutendo Nendauni

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Colonialism breaks things, colonisers exploded native cultural solidarity, producing the spiritual confusion, psychic wounding, and economic exploitation of a new and dominated ‘other’. Colonialism as the cultural and economic exploitation began when the West defended in their seizure of foreign territories for the exploitation of its natural resources; this resulted in brutal socio-economic imbalances. The Western profited at the detriment of the weak Africa. However, colonialism has since passed, but the effects are still evident culturally, socially, and economically. This paper explored how postcolonial writers and critics attempt to reverse the socio-economic imbalances resulting from the fragmentation of colonialism, with a focus on the play 'I will Marry When I Want' by Ngugi wa Thiong’o and Ngugi wa Mirii, as a primary text. Using qualitative discourse-textual analysis as the research methodology, the researcher purposively extracts discourse segments from the text for analysis and interpretation. The findings reveal that Postcolonial critics and writers attempt to reverse the socio-economic effects of colonialism through various counter discourses; their literature is concerned with the destruction of colonised identity, the search for this identity, and its assertion. It is manifest in the text that writers offer corrective views about Africans; they stress that they write their literary texts to conscientise their fellow Africans. Postcolonial writers and critics argue that language is a carrier of culture and that the only way to break free from colonial influence is by not adopting a foreign language. They further through their poems, novels, plays, and music strategically shine the spotlight on the previously nameless and destitute people so that they can develop the human spirit’s desire to overcome defeat, socio-political deprivation, and isolation.

Keywords: colonialism, postcoloniality, critics, socio-economic imbalances

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Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

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Authors: K. Roushanger, A. Soleymanzadeh

Abstract:

Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs.

Keywords: discharge coefficient, genetic expression programming, trapezoidal weir

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

Abstract:

This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

Procedia PDF Downloads 339

Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

Abstract:

Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

Procedia PDF Downloads 575