Search results for: Generalized matrix approach

Authors: Arash Taheri

Abstract:

In this paper, Lagrangian coherent structure (LCS) concept is applied to wake flows generated in the up/down-stream of a swimming nematode C. elegans in an intermediate Re number range, i.e., 250-1200. It materializes Lagrangian hidden structures depicting flow transport barriers. To pursue the goals, nematode swimming in a quiescent fluid flow environment is numerically simulated by a two-way fluid-structure interaction (FSI) approach with the aid of immersed boundary method (IBM). In this regard, incompressible Navier-Stokes equations, fully-coupled with Lagrangian deformation equations for the immersed body, are solved using IB2d code. For all simulations, nematode’s body is modeled with a parametrized spring-fiber built-in case available in the computational code. Reverse von-Kármán vortex street formation and vortex shedding characteristics are studied and discussed in details via LCS approach, including grid resolution, integration time and Reynolds number effects. Results unveil presence of different flow regions with distinct fluid particle fates in the swimming animal’s wake and formation of so-called ‘mushroom-shaped’ structures in attracting LCS identities.

Keywords: Lagrangian coherent structure, nematode swimming, fluid-structure interaction, immersed boundary method, bionics.

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Authors: G. Büyüközkan , O. Feyzioglu, Z. Vardaloglu

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Collaborative planning, forecasting and replenishment (CPFR) coordinates the various supply chain management activities including production and purchase planning, demand forecasting and inventory replenishment between supply chain trading partners. This study proposes a systematic way of analyzing CPFR supporting factors using fuzzy cognitive map (FCM) approach. FCMs have proven particularly useful for solving problems in which a number of decision variables and uncontrollable variables are causally interrelated. Hence the FCMs of CPFR are created to show the relationships between the factors that influence on effective implementation of CPFR in the supply chain.

Keywords: Collaborative planning, forecasting and replenishment, fuzzy cognitive map, information sharing, decision synchronization, incentive alignment.

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Authors: M. K. Moazzam, A. Salmanpour, M. Nirouei

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In this paper we have numerically analyzed terahertzrange wavelength conversion using nondegenerate four wave mixing (NDFWM) in a SOA integrated DFB laser (experiments reported both in MIT electronics and Fujitsu research laboratories). For analyzing semiconductor optical amplifier (SOA), we use finitedifference beam propagation method (FDBPM) based on modified nonlinear SchrÖdinger equation and for distributed feedback (DFB) laser we use coupled wave approach. We investigated wavelength conversion up to 4THz probe-pump detuning with conversion efficiency -5dB in 1THz probe-pump detuning for a SOA integrated quantum-well

Keywords: distributed feedback laser, nondegenerate fourwave mixing, semiconductor optical amplifier, wavelengthconversion

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Authors: Evangelos G. Karvelas, Christos Liosis, Andreas Theodorakakos, Theodoros E. Karakasidis

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In the present work, a numerical method for the estimation of the appropriate gradient magnetic fields for optimum driving of the particles into the desired area inside the human body is presented. The proposed method combines Computational Fluid Dynamics (CFD), Discrete Element Method (DEM) and Covariance Matrix Adaptation (CMA) evolution strategy for the magnetic navigation of nanoparticles. It is based on an iteration procedure that intents to eliminate the deviation of the nanoparticles from a desired path. Hence, the gradient magnetic field is constantly adjusted in a suitable way so that the particles’ follow as close as possible to a desired trajectory. Using the proposed method, it is obvious that the diameter of particles is crucial parameter for an efficient navigation. In addition, increase of particles' diameter decreases their deviation from the desired path. Moreover, the navigation method can navigate nanoparticles into the desired areas with efficiency approximately 99%.

Keywords: CFD, CMA evolution strategy, DEM, magnetic navigation, spherical particles.

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Authors: Tristan O'Neill, Trina Myers, Jarrod Trevathan

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The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: E. Feizi Ashtiani, S. Jamshidi, M.H Niksokhan, A. Feizi Ashtiani

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Waste load allocation (WLA) policies may use multiobjective optimization methods to find the most appropriate and sustainable solutions. These usually intend to simultaneously minimize two criteria, total abatement costs (TC) and environmental violations (EV). If other criteria, such as inequity, need for minimization as well, it requires introducing more binary optimizations through different scenarios. In order to reduce the calculation steps, this study presents value index as an innovative decision making approach. Since the value index contains both the environmental violation and treatment costs, it can be maximized simultaneously with the equity index. It implies that the definition of different scenarios for environmental violations is no longer required. Furthermore, the solution is not necessarily the point with minimized total costs or environmental violations. This idea is testified for Haraz River, in north of Iran. Here, the dissolved oxygen (DO) level of river is simulated by Streeter-Phelps equation in MATLAB software. The WLA is determined for fish farms using multi-objective particle swarm optimization (MOPSO) in two scenarios. At first, the trade-off curves of TC-EV and TC-Inequity are plotted separately as the conventional approach. In the second, the Value-Equity curve is derived. The comparative results show that the solutions are in a similar range of inequity with lower total costs. This is due to the freedom of environmental violation attained in value index. As a result, the conventional approach can well be replaced by the value index particularly for problems optimizing these objectives. This reduces the process to achieve the best solutions and may find better classification for scenario definition. It is also concluded that decision makers are better to focus on value index and weighting its contents to find the most sustainable alternatives based on their requirements.

Keywords: Waste load allocation (WLA), Value index, Multi objective particle swarm optimization (MOPSO), Haraz River, Equity.

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Authors: Nishant Singh, Christian Huyck, Vaibhav Gandhi, Alexander Jones

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A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors, and outputs to effectors. The robot performs a simple pick-and-place task. This work is a proof of concept study for a longer term approach. It is hoped that further work will lead to more effective and flexible robots. As another benefit, it is hoped that further work will also lead to a better understanding of human and other animal neural processing, particularly for physical motion. This is a multidisciplinary approach combining cognitive neuroscience, robotics, and psychology.

Keywords: Robot, neuron, cell assembly, spiking neuron, force sensitive resistor.

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Authors: Eric Jiang

Abstract:

As a popular rank-reduced vector space approach, Latent Semantic Indexing (LSI) has been used in information retrieval and other applications. In this paper, an LSI-based content vector model for text classification is presented, which constructs multiple augmented category LSI spaces and classifies text by their content. The model integrates the class discriminative information from the training data and is equipped with several pertinent feature selection and text classification algorithms. The proposed classifier has been applied to email classification and its experiments on a benchmark spam testing corpus (PU1) have shown that the approach represents a competitive alternative to other email classifiers based on the well-known SVM and naïve Bayes algorithms.

Keywords: Feature Selection, Latent Semantic Indexing, Text Classification, Vector Space Model.

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Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara

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Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.

Keywords: Gaussian mixture discriminant analysis, spectral mixture model, World View-2, land parcels.

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Authors: Chiharu Okuma, Naoki Yamamoto, Jun Murakami

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As a method of expanding a higher-order tensor data to tensor products of vectors we have proposed the Third-order Orthogonal Tensor Product Expansion (3OTPE) that did similar expansion as Higher-Order Singular Value Decomposition (HOSVD). In this paper we provide a computation algorithm to improve our previous method, in which SVD is applied to the matrix that constituted by the contraction of original tensor data and one of the expansion vector obtained. The residual of the improved method is smaller than the previous method, truncating the expanding tensor products to the same number of terms. Moreover, the residual is smaller than HOSVD when applying to color image data. It is able to be confirmed that the computing time of improved method is the same as the previous method and considerably better than HOSVD.

Keywords: Singular value decomposition (SVD), higher-orderSVD (HOSVD), outer product expansion, power method.

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Authors: Abdallah Ghoul, Bachir Ouamri, Ismail Khalil Bousserhane

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In this paper, we have developed a sliding mode controller for PUMA 600 manipulator robot, to control the remote robot a teleoperation system was developed. This system includes two sites, local and remote. The sliding mode controller is installed at the remote site. The client asks for a position through an interface and receives the real positions after running of the task by the remote robot. Both sites are interconnected via the Internet. In order to verify the effectiveness of the sliding mode controller, that is compared with a classic PID controller. The developed approach is tested on a virtual robot. The results confirmed the high performance of this approach.

Keywords: Internet, manipulator robot, PID controller, remote control, sliding mode, teleoperation.

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Authors: R. Bremananth, A. Chitra

Abstract:

Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

Keywords: Autocorrelators, biometrics cryptography, irispatterns, wavelets.

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Authors: Alireza Rezaei, Fatemeh Baharifard, Kourosh Parand

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In this paper we improve the quasilinearization method by barycentric Lagrange interpolation because of its numerical stability and computation speed to achieve a stable semi analytical solution. Then we applied the improved method for solving the Fin problem which is a nonlinear equation that occurs in the heat transferring. In the quasilinearization approach the nonlinear differential equation is treated by approximating the nonlinear terms by a sequence of linear expressions. The modified QLM is iterative but not perturbative and gives stable semi analytical solutions to nonlinear problems without depending on the existence of a smallness parameter. Comparison with some numerical solutions shows that the present solution is applicable.

Keywords: Quasilinearization method, Barycentric lagrange interpolation, nonlinear ODE, fin problem, heat transfer.

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Authors: Bremananth R, Nithya B, Saipriya R

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The proposed system identifies the species of the wood using the textural features present in its barks. Each species of a wood has its own unique patterns in its bark, which enabled the proposed system to identify it accurately. Automatic wood recognition system has not yet been well established mainly due to lack of research in this area and the difficulty in obtaining the wood database. In our work, a wood recognition system has been designed based on pre-processing techniques, feature extraction and by correlating the features of those wood species for their classification. Texture classification is a problem that has been studied and tested using different methods due to its valuable usage in various pattern recognition problems, such as wood recognition, rock classification. The most popular technique used for the textural classification is Gray-level Co-occurrence Matrices (GLCM). The features from the enhanced images are thus extracted using the GLCM is correlated, which determines the classification between the various wood species. The result thus obtained shows a high rate of recognition accuracy proving that the techniques used in suitable to be implemented for commercial purposes.

Keywords: Correlation, Grey Level Co-Occurrence Matrix, ProbabilityDensity Function, Wood Recognition.

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Authors: Adnan Abdul-Aziz Gutub, Manal Mohammad Fattani

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This paper presents a new steganography approach suitable for Arabic texts. It can be classified under steganography feature coding methods. The approach hides secret information bits within the letters benefiting from their inherited points. To note the specific letters holding secret bits, the scheme considers the two features, the existence of the points in the letters and the redundant Arabic extension character. We use the pointed letters with extension to hold the secret bit 'one' and the un-pointed letters with extension to hold 'zero'. This steganography technique is found attractive to other languages having similar texts to Arabic such as Persian and Urdu.

Keywords: Arabic text, Cryptography, Feature coding, Information security, Text steganography, Text watermarking.

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Authors: Amira Abbes Kheriji, Faouzi Bouani, Mekki Ksouri, Mohamed Ben Ahmed

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Model Predictive Control (MPC) is increasingly being proposed for real time applications and embedded systems. However comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprises as well as a transformer of organizations and markets. Recently, advances in microelectronics and software allow such technique to be implemented in embedded systems. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In fact in this paper, we propose an efficient framework for implementation of Generalized Predictive Control (GPC) in the performed STM32 microcontroller. The STM32 keil starter kit based on a JTAG interface and the STM32 board was used to implement the proposed GPC firmware. Besides the GPC, the PID anti windup algorithm was also implemented using Keil development tools designed for ARM processor-based microcontroller devices and working with C/Cµ langage. A performances comparison study was done between both firmwares. This performances study show good execution speed and low computational burden. These results encourage to develop simple predictive algorithms to be programmed in industrial standard hardware. The main features of the proposed framework are illustrated through two examples and compared with the anti windup PID controller.

Keywords: Embedded systems, Model Predictive Control, microcontroller, Keil tool.

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Authors: Abilio Avila, Orestis Terzidis

Abstract:

A fundamental principle of Grounded Theory (GT) is to prevent the formation of preconceived theories. This implies the need to start a research study with an open mind and to avoid being absorbed by the existing literature. However, to start a new study without an understanding of the research domain and its context can be extremely challenging. This paper presents a research approach that simultaneously supports a researcher to identify and to focus on critical areas of a research project and prevent the formation of prejudiced concepts by the current body of literature. This approach comprises of four stages: Selection of secondary case studies, analysis of secondary case studies, development of an initial conceptual framework, development of an initial interview guide. The analysis of secondary case studies as a starting point for a research project allows a researcher to create a first understanding of a research area based on real-world cases without being influenced by the existing body of theory. It enables a researcher to develop through a structured course of actions a firm guide that establishes a solid starting point for further investigations. Thus, the described approach may have significant implications for GT researchers who aim to start a study within a given research area.

Keywords: Grounded theory, qualitative research, secondary case studies, secondary data analysis, interview guide.

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Authors: Krisada Sungkhamanee

Abstract:

The objectives of this research are to search the management pattern of Nakhon Pathom lodging entrepreneurs for sufficient economy ways, to know the threat that affects this sector and design fit arrangement model to sustain their business with Nakhon Pathom style. What will happen if they do not use this approach? Will they have a financial crisis? The data and information are collected by informal discussions with 12 managers and 400 questionnaires. A mixed method of both qualitative research and quantitative research are used. Bent Flyvbjerg’s phronesis is utilized for this analysis. Our research will prove that sufficient economy can help small business firms to solve their problems. We think that the results of our research will be a financial model to solve many problems of the entrepreneurs and this way will can be a model for other provinces of Thailand.

Keywords: Nakhon Pathom Province, Lodging Business, Sufficient Economy.

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Authors: F. A. M. Elfaki, Amar Abobakar, M. Azram, M. Usman

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This paper discusses regression analysis of partly interval-censored failure time data, which is occur in many fields including demographical, epidemiological, financial, medical and sociological studies. For the problem, we focus on the situation where the survival time of interest can be described by the additive hazards model in the present of partly interval-censored. A major advantage of the approach is its simplicity and it can be easily implemented by using R software. Simulation studies are conducted which indicate that the approach performs well for practical situations and comparable to the existing methods. The methodology is applied to a set of partly interval-censored failure time data arising from anti D in Rhesus D negative studies.

Keywords: Anti D in Rhesus D negative, Cox’s model, EM algorithm.

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Authors: A. I. Alateyah, H. N. Dhakal, Z. Y. Zhang

Abstract:

The study of the effect of the processing parameters on the level of intercalation between the layered silicate and polymer of two different methodology took place. X-ray diffraction, Scanning Electron Microscopy, Energy Dispersive X-ray Spectrometry, and Transmission Electron Microscopy were utilized in order to examine the intercalation level of nanocomposites of both methodologies. It was found that drying the clay prior to mixing with the polymer, mixing time and speed, degassing time, and the curing method had major changes to the level of distribution of the nanocomposites structure. In methodology 1, the presence of aggregation layers was observed at only 2.5 wt.% clay loading whereas in methodology 2 the presence of aggregation layers was found at higher clay loading (i.e. 5 wt.%).

Keywords: Vinyl ester, nanocomposites, layered silicate, characterisations, aggregation layers, intercalation, exfoliation.

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Authors: Jung-Ho Moon, Myung-Gon Yoon, Tae Kwon Ha

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High temperature deformation behavior of cast 310S stainless steel has been investigated in this study by performing tensile and compression tests at temperatures from 900 to 1200^oC. Rectangular ingots of which the dimensions were 350×350×100 in millimeter were cast using vacuum induction melting. Phase equilibrium was calculated using the FactSage®, thermodynamic software and database. Thermal expansion coefficient was also measured on the ingot in the temperature range from room temperature to 1200^oC. Tensile strength of cast 310S stainless steel was 9 MPa at 1200^oC, which is a little higher than that of a wrought 310S. With temperature decreased, tensile strength increased rapidly and reached up to 72 MPa at 900^oC. Elongation also increased with temperature decreased. Microstructure observation revealed that s phase was precipitated along the grain boundary and within the matrix over 1200^oC, which is detrimental to high temperature elongation.

Keywords: Stainless steel, STS 310S, high temperature deformation, microstructure, mechanical properties.

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

Abstract:

A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme Gradient Boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impairment, multiclass classification, ADNI, support vector machine, random forest.

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Authors: S. Balaji, N. Revathi

Abstract:

Connected dominating set (CDS) problem in unit disk graph has signi£cant impact on an ef£cient design of routing protocols in wireless sensor networks, where the searching space for a route is reduced to nodes in the set. A set is dominating if all the nodes in the system are either in the set or neighbors of nodes in the set. In this paper, a simple and ef£cient heuristic method is proposed for £nding a minimum connected dominating set (MCDS) in ad hoc wireless networks based on the new parameter support of vertices. With this parameter the proposed heuristic approach effectively £nds the MCDS of a graph. Extensive computational experiments show that the proposed approach outperforms the recently proposed heuristics found in the literature for the MCD

Keywords: ad hoc wireless networks, dominating sets, unit disk graphs, heuristic.

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Authors: Yulia Irnidayanti, Win Darmanto, Agus Abadi

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research goal was to determine the expression levels cDNA of brain embrio at gestation days 10 (GD-10). The Electroforesis DNA results showed that GAPDH, Fibronectin1, Ncam1, Tenascin, Vimentin, Neurofilament heavy, Neurofilament medium and Neurofilament low were 447 bp, 462 bp, 293 bp. 416 bp, 327 bp, 301 bp, 398 bp and 289 bp. Result of real-time RT-PCR on brain Embryo at gestation days 10 showed that the expression of copy gen Fibronectin 36 copies, Ncam 21,708 copies; Tenascin 24,505 copies; Vimentin 538,554 copies; Neurofilament heavy 2,419 copies; Neurofilament medium 92,928 copies; Neurofilament low 125,809 copies. Vimentin expressed gene copies is very high compared with other gene copies. This condition are caused by Vimentin, that contribute to proliferate of brain development. The vimentin role to cell proliferation of brain.

Keywords: GAPDH, Fibronectin, Ncam, Tenascin, vimentin, Neurofilamen heavy, Neurofilament medium, Neurofilamen low.

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Authors: K. Sasikala, R. S. D Wahidabanu

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Various fairness models and criteria proposed by academia and industries for wired networks can be applied for ad hoc wireless network. The end-to-end fairness in an ad hoc wireless network is a challenging task compared to wired networks, which has not been addressed effectively. Most of the traffic in an ad hoc network are transport layer flows and thus the fairness of transport layer flows has attracted the interest of the researchers. The factors such as MAC protocol, routing protocol, the length of a route, buffer size, active queue management algorithm and the congestion control algorithms affects the fairness of transport layer flows. In this paper, we have considered the rate of data transmission, the queue management and packet scheduling technique. The ad hoc network is dynamic in nature due to various parameters such as transmission of control packets, multihop nature of forwarding packets, changes in source and destination nodes, changes in the routing path influences determining throughput and fairness among the concurrent flows. In addition, the effect of interaction between the protocol in the data link and transport layers has also plays a role in determining the rate of the data transmission. We maintain queue for each flow and the delay information of each flow is maintained accordingly. The pre-processing of flow is done up to the network layer only. The source and destination address information is used for separating the flow and the transport layer information is not used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and the transport layer information is used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on not mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and MC-MLAS and the performance of the proposed approach is encouraging.

Keywords: ATP, End-to-End fairness, FSM, MAC, QoS.

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Authors: W. Kiamouche, M. Benslama

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This paper presents an alternative strategy of queuing handover called Pseudo Last Useful Instant PLUI scheme for Low Earth Orbit Mobile Satellite Systems LEO MSSs. The PLUI scheme uses the same approach as the Last Useful Instant LUI scheme previously proposed in literature, with less complex implementation. Simulation tests were carried out using Dynamic Channel Allocation DCA in order to evaluate the performance of this scheme and also an analytical approach has been presented to allow the performance evaluation of Fixed Channel Allocation FCA, with different handover queuing disciplines. The results show that performances achieved by the proposed strategy are close to those achieved using the LUI scheme.

Keywords: LEO mobile satellite networks, LUI and FIFOschemes, queuing handover.

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Authors: F. Brunke, L. Waalkes, C. Siemers

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Due to reduced stiffness, research on second generation titanium alloys for implant applications, like the metastable β-titanium alloy Ti-15Mo, become more and more important in the recent years. The machinability of these alloys is generally poor leading to problems during implant production and comparably large production costs. Therefore, in the present study, Ti-15Mo was alloyed with 0.8 wt.-% of the rare earth metals lanthanum (Ti-15Mo+0.8La) and neodymium (Ti-15Mo+0.8Nd) to improve its machinability. Their microstructure consisted of a titanium matrix and micrometer-size particles of the rare earth metals and two of their oxides. The particles stabilized the microstructure as grain growth was minimized. As especially the ductility might be affected by the precipitates, the behavior of Ti-15Mo+0.8La and Ti- 15Mo+0.8Nd was investigated during static and dynamic deformation at elevated temperature to develop a processing route. The resulting mechanical properties (static strength and ductility) were similar in all investigated alloys.

Keywords: Ti-15Mo, Titanium alloys, Rare earth metals, Free-machining alloy.

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Authors: Navid Javidtash, Abdolmohamad Davodi, Mojtaba Hakimzadeh, Abdolreza Roozbeh

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Economic dispatch (ED) is considered to be one of the key functions in electric power system operation. This paper presents a new hybrid approach based genetic algorithm (GA) to economic dispatch problems. GA is most commonly used optimizing algorithm predicated on principal of natural evolution. Utilization of chaotic queue with GA generates several neighborhoods of near optimal solutions to keep solution variation. It could avoid the search process from becoming pre-mature. For the objective of chaotic queue generation, utilization of tent equation as opposed to logistic equation results in improvement of iterative speed. The results of the proposed approach were compared in terms of fuel cost, with existing differential evolution and other methods in literature.

Keywords: Economic Dispatch(ED), Optimization, Fuel Cost, Genetic Algorithm (GA).

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

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: Vanessa Matias Leite, Jandira Guenka Palma, Flávio Henrique de Oliveira

Abstract:

This paper presents a model-oriented development approach to software development in the Model-View-Controller (MVC) architectural standard. This approach aims to expose a process of extractions of information from the models, in which through rules and syntax defined in this work, assists in the design of the initial model and its future conversions. The proposed paper presents a syntax based on the natural language, according to the rules agreed in the classic grammar of the Portuguese language, added to the rules of conversions generating models that follow the norms of the Object Management Group (OMG) and the Meta-Object Facility MOF.

Keywords: Model driven architecture, model-view-controller, bnf syntax, model, transformation, UML.

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