Search results for: mixed sensitivity function

Authors: Saleem Z. Ramadan

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The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: Optimization, Material selection, Process selection, Genetic algorithm.

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Authors: Khosrow Maleknejad, Yaser Rostami

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In this paper, Semi-orthogonal B-spline scaling functions and wavelets and their dual functions are presented to approximate the solutions of integro-differential equations.The B-spline scaling functions and wavelets, their properties and the operational matrices of derivative for this function are presented to reduce the solution of integro-differential equations to the solution of algebraic equations. Here we compute B-spline scaling functions of degree 4 and their dual, then we will show that by using them we have better approximation results for the solution of integro-differential equations in comparison with less degrees of scaling functions

Keywords: Integro-differential equations, Quartic B-spline wavelet, Operational matrices.

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Authors: S. Balaji, V. Swaminathan, K. Kannan

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The Minimum Weighted Vertex Cover (MWVC) problem is a classic graph optimization NP - complete problem. Given an undirected graph G = (V, E) and weighting function defined on the vertex set, the minimum weighted vertex cover problem is to find a vertex set S V whose total weight is minimum subject to every edge of G has at least one end point in S. In this paper an effective algorithm, called Support Ratio Algorithm (SRA), is designed to find the minimum weighted vertex cover of a graph. Computational experiments are designed and conducted to study the performance of our proposed algorithm. Extensive simulation results show that the SRA can yield better solutions than other existing algorithms found in the literature for solving the minimum vertex cover problem.

Keywords: Weighted vertex cover, vertex support, approximation algorithms, NP-complete problem.

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Authors: María I. Jiménez, Alberto Izquierdo, Juan J. Villacorta, Lara del Val, Mariano Raboso

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There are very complex communication systems, as the multifunction radar, MFAR (Multi-Function Array Radar), where functions are integrated all together, and simultaneously are performed the classic functions of tracking and surveillance, as all the functions related to the communication, countermeasures, and calibration. All these functions are divided into the tasks to execute. The task scheduler is a key element of the radar, since it does the planning and distribution of energy and time resources to be shared and used by all tasks. This paper presents schedulers based on the use of multiple queue. Several schedulers have been designed and studied, and it has been made a comparative analysis of different performed schedulers. The tests and experiments have been done by means of system software simulation. Finally a suitable set of radar characteristics has been selected to evaluate the behavior of the task scheduler working.

Keywords: Queue Theory, Radar, Scheduler, Task.

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Authors: Mukesh Singh Boori, Venerando Eustáquio Amaro

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The objective of this study was to improve our understanding of vulnerability and environmental change; it's causes basically show the intensity, its distribution and human-environment effect on the ecosystem in the Apodi Valley Region, This paper is identify, assess and classify vulnerability and environmental change in the Apodi valley region using a combined approach of landscape pattern and ecosystem sensitivity. Models were developed using the following five thematic layers: Geology, geomorphology, soil, vegetation and land use/cover, by means of a Geographical Information Systems (GIS)-based on hydro-geophysical parameters. In spite of the data problems and shortcomings, using ESRI-s ArcGIS 9.3 program, the vulnerability score, to classify, weight and combine a number of 15 separate land cover classes to create a single indicator provides a reliable measure of differences (6 classes) among regions and communities that are exposed to similar ranges of hazards. Indeed, the ongoing and active development of vulnerability concepts and methods have already produced some tools to help overcome common issues, such as acting in a context of high uncertainties, taking into account the dynamics and spatial scale of asocial-ecological system, or gathering viewpoints from different sciences to combine human and impact-based approaches. Based on this assessment, this paper proposes concrete perspectives and possibilities to benefit from existing commonalities in the construction and application of assessment tools.

Keywords: Vulnerability, Land use/cover, Ecosystem, Remotesensing, GIS.

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Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA), is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: Balanced truncation, Clustering, Dominant pole, Hankel norm, Model reduction.

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Authors: Omid Adibi, Nategheh Najafpour, Bijan Farhanieh, Hossein Afshin

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Gas release from the pipelines is one of the main factors in the gas industry accidents. Released gas ejects from the pipeline as a free jet and in the growth process, the fuel gets mixed with the ambient air. Accordingly, an accidental spark will release the chemical energy of the mixture with an explosion. Gas explosion damages the equipment and endangers the life of staffs. So due to importance of safety in gas industries, prevision of accident can reduce the number of the casualties. In this paper, natural gas leakages from the low pressure pipelines are studied in two steps: 1) the simulation of mixing process and identification of flammable zones and 2) the simulation of wind effects on the mixing process. The numerical simulations were performed by using the finite volume method and the pressure-based algorithm. Also, for the grid generation the structured method was used. The results show that, in just 6.4 s after accident, released natural gas could penetrate to 40 m in vertical and 20 m in horizontal direction. Moreover, the results show that the wind speed is a key factor in dispersion process. In fact, the wind transports the flammable zones into the downstream. Hence, to improve the safety of the people and human property, it is preferable to construct gas facilities and buildings in the opposite side of prevailing wind direction.

Keywords: Flammable zones, gas pipelines, numerical simulation, wind effects.

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Authors: Shiva Abdoli, Daniel T. Semere

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Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.

Keywords: Process parameters, cutting process, energy efficiency, Material Removal Rate (MRR).

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Authors: C. Rattanakawin, S. Vasailor

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Acid leaching of flotation concentrate of oxide copper ore containing mainly of malachite was performed in a standard agitation tank with various parameters. The effects of solid to liquid ratio, sulfuric acid concentration, agitation speed, leaching temperature and time were examined to get proper conditions. The best conditions are 1:8 solid to liquid ratio, 10% concentration by weight, 250 rev/min, 30 ^oC and 5-min leaching time in respect. About 20% Cu grade assayed by atomic absorption technique with 98% copper recovery was obtained from these combined optimum conditions. Dissolution kinetics of the concentrate was approximated as a logarithmic function. As a result, the first-order reaction rate is suggested from this leaching study.

Keywords: Agitation leaching, dissolution kinetics, flotation concentrate, oxide copper ore, sulfuric acid.

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Authors: Fawzi Irshaid, Fatiha Dilmi, Khaled Tarawneh, Raji Hadeth, Adnan Jaran, Ahad Al-Khatib

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P16/INK4A is tumor suppressor protein that plays a critical role in cell cycle regulation. Loss of P16 protein expression has been implicated in pathogenesis of many cancers, including lymphoma. Therefore, we sought to investigate if loss of P16 protein expression is associated with lymphoma and/or any specific lymphoma subtypes (Hodgkin-s lymphoma (HL) and nonHodgkin-s lymphoma (NHL)). Fifty-five lymphoma cases consisted of 30 cases of HL and 25 cases of NHL, with an age range of 3 to 78 years, were examined for loss of P16 by immunohistochemical technique using a specific antibody reacting against P16. In total, P16 loss was seen in 33% of all lymphoma cases. P16 loss was identified in 47.7% of HL cases. In contrast, only 16% of NHL showed loss of P16. Loss of P16 was seen in 67% of HL patients with 50 years of age or older, whereas P16 loss was found in only 42% of HL patients with less than 50 years of age. P16 loss in HL is somewhat higher in male (55%) than in female (30%). In subtypes of HL, P16 loss was found exclusively in all cases of lymphocyte depletion, lymphocyte predominance and unclassified cases, whereas P16 loss was seen in 39% of mixed cellularity and 29% of nodular sclerosis cases. In low grade NHL patients, P16 loss was seen in approximately one-third of cases, whereas no or very rare of P16 loss was found in intermediate and high grade cases. P16 loss did not show any correlation with age or gender of NHL patients. In conclusion, the high rate of P16 loss seen in our study suggests that loss of P16 expression plays a critical role in the pathogenesis of lymphoma, particularly with HL.

Keywords: B-cells, immunostaining, P16 protein, Reed-Sternberg cells, tumors.

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Authors: Shidvash Vakilipour, Masoud Mohammadi, Rouzbeh Riazi, Scott Ormiston, Kimia Amiri, Sahar Barati

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An essential component of a finite volume method (FVM) is the advection scheme that estimates values on the cell faces based on the calculated values on the nodes or cell centers. The most widely used advection schemes are upwind schemes. These schemes have been developed in FVM on different kinds of structured and unstructured grids. In this research, the physical influence scheme (PIS) is developed for a cell-centered FVM that uses an implicit coupled solver. Results are compared with the exponential differencing scheme (EDS) and the skew upwind differencing scheme (SUDS). Accuracy of these schemes is evaluated for a lid-driven cavity flow at Re = 1000, 3200, and 5000 and a backward-facing step flow at Re = 800. Simulations show considerable differences between the results of EDS scheme with benchmarks, especially for the lid-driven cavity flow at high Reynolds numbers. These differences occur due to false diffusion. Comparing SUDS and PIS schemes shows relatively close results for the backward-facing step flow and different results in lid-driven cavity flow. The poor results of SUDS in the lid-driven cavity flow can be related to its lack of sensitivity to the pressure difference between cell face and upwind points, which is critical for the prediction of such vortex dominant flows.

Keywords: Cell-centered finite volume method, physical influence scheme, exponential differencing scheme, skew upwind differencing scheme, false diffusion.

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Authors: Savvas Varitis, Panagiotis Kavouras, George Vourlias, Eleni Pavlidou, Theodoros Karakostas, Philomela Komninou

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A chromium-loaded ash originating from incineration of tannery sludge under anoxic conditions was mixed with low grade soda-lime glass powder coming from commercial glass bottles. The relative weight proportions of ash over glass powder tested were 30/70, 40/60 and 50/50. The solid mixtures, formed in green state compacts, were sintered at the temperature range of 800o C up to 1200o C. The resulting products were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDXS) and micro-indentation. The above methods were employed to characterize the various phases, microstructure and hardness of the produced materials. Thermal treatment at 800o C and 1000o C produced opaque ceramic products composed of a variety of chromium-containing and chromium-free crystalline phases. Thermal treatment at 1200o C gave rise to composite products, where only chromium-containing crystalline phases were detected. Hardness results suggest that specific products are serious candidates for structural applications.

Keywords: Chromium-rich tannery residues, glass-ceramic materials, mechanical properties, microstructure

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Authors: Christopher Spiewak, M. R. Islam, Mohammad Arifur Rahaman, Mohammad H. Rahman, Roger Smith, Maarouf Saad

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For those who have lost the ability to move their hand, going through repetitious motions with the assistance of a therapist is the main method of recovery. We have been developed a robotic assistive device to rehabilitate the hand motions in place of the traditional therapy. The developed assistive device (RAD-HR) is comprised of four degrees of freedom enabling basic movements, hand function, and assists in supporting the hand during rehabilitation. We used a nonlinear computed torque control technique to control the RAD-HR. The accuracy of the controller was evaluated in simulations (MATLAB/Simulink environment). To see the robustness of the controller external disturbance as modelling uncertainty (±10% of joint torques) were added in each joints.

Keywords: Biorobotics, rehabilitation, nonlinear control, robotic assistive device, exoskeleton.

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Authors: Kazuo Komatsu, Hitoshi Takata

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In this paper we consider a nonlinear control design for nonlinear systems by using two-stage formal linearization and twotype LQ controls. The ordinary LQ control is designed on almost linear region around the steady state point. On the other region, another control is derived as follows. This derivation is based on coordinate transformation twice with respect to linearization functions which are defined by polynomials. The linearized systems can be made up by using Taylor expansion considered up to the higher order. To the resulting formal linear system, the LQ control theory is applied to obtain another LQ control. Finally these two-type LQ controls are smoothly united to form a single nonlinear control. Numerical experiments indicate that this control show remarkable performances for a nonlinear system.

Keywords: Formal Linearization, LQ Control, Nonlinear Control, Taylor Expansion, Zero Function.

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: Economic production quantity, random cost, supply chain management, vendor-managed inventory.

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Authors: Chetan R. Patel, G. J. Joshi

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Present study is carried out on six lane divided urban arterial road in Patna and Pune city of India. Both the road having distinct differences in terms of the vehicle composition and the road side parking. Arterial road in Patan city has 33% of non-motorized mode, whereas Pune arterial road dominated by 65% of Two wheeler. Also road side parking is observed in Patna city. The field studies using videography techniques are carried out for traffic data collection. Data are extracted for one minute duration for vehicle composition, speed variation and flow rate on selected arterial road of the two cities. Speed flow relationship is developed and capacity is determine. Equivalency factor in terms of dynamic car unit is determine to represent the vehicle is single unit. The variation in the capacity due to side friction, presence of non motorized traffic and effective utilization of lane width is compared at concluding remarks.

Keywords: Arterial Road, Capacity, Dynamic Equivalency Factor, Effect of Non motorized mode, Side friction.

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Authors: M. Sedighizadeh, A. Rezazadeh

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In this paper a PID control strategy using neural network adaptive RASP1 wavelet for WECS-s control is proposed. It is based on single layer feedforward neural networks with hidden nodes of adaptive RASP1 wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. This particular neuro PID controller assumes a certain model structure to approximately identify the system dynamics of the unknown plant (WECS-s) and generate the control signal. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution.

Keywords: Adaptive PID Control, RASP1 Wavelets, WindEnergy Conversion Systems.

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Authors: Negar Khezri, Golnaz Yaghoubnezhadzanganeh, Amirreza Attarzadeh

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Type 2 Diabetes (T2DM) and Alzheimer's disease (AD) are two main health problems influencing millions of people in the world. Neuron loss and synaptic impairment that interfere with cognition and memory cause for the behavioral indications of AD. While it is now accepted that insulin has central neuromodulatory purpose, it was contemplated for many years that brain is insusceptible to insulin, involving its function in memory and learning, which are impaired in AD. The common characteristics of both AD and T2D are impaired insulin signaling, oxidative stress, the excitation of inflammatory pathways and unqualified glucose metabolism. This review summarizes how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches. Here we summarize how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches.

Keywords: Alzheimer’s disease, diabetes, insulin resistance, neurodegenerative.

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

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In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: Segmentation, color-texture, neural networks, fractal, watershed.

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Authors: Teerapun Saeheaw, Nivit Charoenchai, Wichai Chattinnawat

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This paper proposes a meta-heuristic called Ant Colony Optimization to solve multi-objective production problems. The multi-objective function is to minimize lead time and work in process. The problem is related to the decision variables, i.e.; distance and process time. According to decision criteria, the mathematical model is formulated. In order to solve the model an ant colony optimization approach has been developed. The proposed algorithm is parameterized by the number of ant colonies and the number of pheromone trails. One example is given to illustrate the effectiveness of the proposed model. The proposed formulations; Max-Min Ant system are then used to solve the problem and the results evaluate the performance and efficiency of the proposed algorithm using simulation.

Keywords: Ant colony optimization, multi-objective problems.

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Authors: Sang-Rak Kim, Jea-Yong Park, Won-Goo Lee, Jin-Shik Yu, Seog-Young Han

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This paper presents a Reliability-Based Topology Optimization (RBTO) based on Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of the uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.

Keywords: Evolutionary Structural Optimization, PerformanceMeasure Approach, Reliability-Based Topology Optimization, Reliability Index Approach.

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Authors: Clio G. Vossou, Ioannis N. Koukoulis, Christopher G. Provatidis

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The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.

Keywords: Defect identification, genetic algorithms, optimization.

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Authors: Toshihiko Matsuka, James E. Corter

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Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.

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Authors: M. Hanif, M. Salik

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In the present research work we present the optical emission studies of the Indium (In) – Tin (Sn) plasma produced by the first (1064 nm) harmonic of an Nd: YAG nanosecond pulsed laser. The experimentally observed line profiles of neutral Indium (In I) and Tin (SnI) are used to extract the electron temperature (Te) using the Boltzmann plot method. Whereas, the electron number density (Ne) has been determined from the Stark broadening line profile method. The Te is calculated by varying the distance from the target surface along the line of propagation of plasma plume and also by varying the laser irradiance. Beside we have studied the variation of Ne as a function of laser irradiance as well as its variation with distance from the target surface.

Keywords: Indium – Tin plasma, laser ablation, optical emission spectroscopy, electron temperature, and electron number density.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

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In many applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. Here we consider partially monotone problems, where the target variable depends monotonically on some of the predictor variables but not all. We propose an approach to build partially monotone models based on the convolution of monotone neural networks and kernel functions. The results from simulations and a real case study on house pricing show that our approach has significantly better performance than partially monotone linear models. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: Mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Homa Torabizadeh

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This study proposes a basic molecular formula for all proteins. A total of 10,739 proteins belonging to 9 different protein groups classified on the basis of their functions were selected randomly. They included enzymes, storage proteins, hormones, signalling proteins, structural proteins, transport proteins, immunoglobulins or antibodies, motor proteins and receptor proteins. After obtaining the protein molecular formula using the ProtParam tool, the H/C, N/C, O/C, and S/C ratios were determined for each randomly selected sample. In this case, H, N, O, and S coefficients were specified per carbon atom. Surprisingly, the results demonstrated that H, N, O, and S coefficients for all 10,739 proteins are similar and highly correlated. This study demonstrates that despite differences in the structure and function, all known proteins have a similar basic molecular formula CnH1.58 ± 0.015nN0.28 ± 0.005nO0.30 ± 0.007nS0.01 ± 0.002n. The total correlation between all coefficients was found to be 0.9999.

Keywords: Protein molecular formula, Basic unit formula, Protparam tool.

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Authors: Samir Abdelhamid, Noureddine Bouguechal

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We report in this paper the procedure of a system of automatic speech recognition based on techniques of the dynamic programming. The technique of temporal retiming is a technique used to synchronize between two forms to compare. We will see how this technique is adapted to the field of the automatic speech recognition. We will expose, in a first place, the theory of the function of retiming which is used to compare and to adjust an unknown form with a whole of forms of reference constituting the vocabulary of the application. Then we will give, in the second place, the various algorithms necessary to their implementation on machine. The algorithms which we will present were tested on part of the corpus of words in Arab language Arabdic-10 [4] and gave whole satisfaction. These algorithms are effective insofar as we apply them to the small ones or average vocabularies.

Keywords: Continuous speech recognition, temporal retiming, phonetic decoding, algorithms, vocal signal, dynamic programming.

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Authors: Bilgehan Gültekin, Tuba Gültekin

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It is quite essential to form dialogue mechanisms and dialogue channels to solve intercultural communication issues. Therefore, every country should develop a intercultural education project which aims to resolve international communication issues. For proper mediation training, the first step is to reach an agreement on the actors to run the project. The strongest mediation mechanisms in the world should be analyzed and initiated within the educational policies. A communication-based mediation model should be developed for international mediation training. Mediators can use their convincing communication skills as a part of this model. At the first, fundamental stages of the mediation training should be specified within the scope of the model. Another important topic at this point is common sence and peace leaders to act as an ombudsman in this process. Especially for solving some social issues and conflicts, common sense leaders acting as an ombudsman would lead to effective communication. In mediation training that is run by universities and non-governmental organizations, another phase is to focus on conducting the meetings. In intercultural mediation training, one of the most critical topics is to conduct the meeting traffic and performing a shuttle diplomacy. Meeting traffic is where the mediator organizes meetings with the parties with initiative powers, in order to contribute to the solution of the issue, and schedule these meetings. In this notice titled “ Intercultural mediation training and the training process of common sense leaders by the leadership of universities communication and artistic campaigns" , communication models and strategies about this topic will be constructed and an intercultural art activities and perspectives will be presented.

Keywords: Intercultural communication, mediation education, common sense leaders, artistic sensitivity

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Authors: Ashish Kumar Nayak, Dhamodharan K., Ajay S. Kalamdhad

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The present study is aimed at alteration of sewage sludge into stable compost product using vermicomposting of sewage sludge mixed with cattle manure and saw dust in five different proportions based on C/N ratios (C/N 15 (R1), 20 (R2), 25 (R3) and 30 (R4); and control (R5)) by employing an epigeic earthworm Eisenia fetida. Higher reductions in C/N ratio, CO₂ evolution and OUR were observed in R4 demonstrated the compost stability. In addition, R4 proved to be best combination for the growth of the earthworms. In order to observe the optimal degradation, kinetics for degradation of organic matter in vermicomposting were quantitatively evaluated. An approach model was developed by assuming that composting process is carried out in a homogeneous way and the kinetics for decomposition reaction is represented by a Monod-type equation. The results exhibit comparable variations in the kinetic constants K_m and K₃ under varying parameters during vermicomposting process. Results suggested that higher R² value in R4, enhanced suitability towards Lineweaver-Burke plot. R4 yields higher degradability coefficient (K) reveals that the occurrence of optimal nutrient balance, which not only enhanced the affinity of enzymes towards substrate but also improved its degradation process. Therefore, it can be proved that R4 provided to be the best feed combination for vermicomposting process as compared to other reactors.

Keywords: Vermicomposting, Eisenia fetida, Sewage sludge, C/N ratio, Stability, Enzyme kinetics concept.

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Authors: Aktan Ozsoy, Ali Fırat Cabalar, Eyyub Karakan

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Climate change is one of the biggest issues facing communities. Increasing population, growing economies, rapid industrialization are the main factors triggering it. On the other hand, the millions of tons of waste have generated by the period of rapid global growth not only harm to the environment but also lead to the use of valuable lands around the world as landfill sites. Moreover, it is rapidly consuming our resources and this forces the human population and wildlife to share increasingly shrinking space. In this direction, it is vital to reuse waste materials with a sustainability philosophy. This study was carried out to contribute to the combat against climate change, conserve our natural resources and the environment. An oedometer (consolidation) test was performed on two waste materials combined in certain proportions to evaluate their sustainable usage. Crushed brick dust (BD) was mixed with rock powder (RP) in 0%, 5%, 10%, 20%, 30%, 40%, and 50% (dry weight of soil). The results obtained revealed the importance of the gradation of the material used in the consolidation test. It was found that there was a negligible difference between the initial and final void ratio of mixtures with BD added.

Keywords: Waste material, oedometer test, environmental geotechnics, sustainability, crushed brick dust, rock powder.

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