Search results for: sequential stimulation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 259

Search results for: sequential stimulation

229 Efficient Detection Using Sequential Probability Ratio Test in Mobile Cognitive Radio Systems

Authors: Yeon-Jea Cho, Sang-Uk Park, Won-Chul Choi, Dong-Jo Park

Abstract:

This paper proposes a smart design strategy for a sequential detector to reliably detect the primary user-s signal, especially in fast fading environments. We study the computation of the log-likelihood ratio for coping with a fast changing received signal and noise sample variances, which are considered random variables. First, we analyze the detectability of the conventional generalized log-likelihood ratio (GLLR) scheme when considering fast changing statistics of unknown parameters caused by fast fading effects. Secondly, we propose an efficient sensing algorithm for performing the sequential probability ratio test in a robust and efficient manner when the channel statistics are unknown. Finally, the proposed scheme is compared to the conventional method with simulation results with respect to the average number of samples required to reach a detection decision.

Keywords: Cognitive radio, fast fading, sequential detection, spectrum sensing.

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228 Release of Elements in Bottom Ash and Fly Ash from Incineration of Peat- and Wood-Residues using a Sequential Extraction Procedure

Authors: Risto Poykio, Kati Manskinen, Olli Dahl, Mikko Mäkelä, Hannu Nurmesniemi

Abstract:

When the results of the total element concentrations using USEPA method 3051A are compared to the sequential extraction analyses (i.e. the sum of fractions BCR1, BCR2 and BRC3), it can be calculated that the recovery values of elements varied between 56.8-% and 69.4-% in the bottom ash, and between 11.3-% and 70.9-% in the fly ash. This indicates that most of the elements in the ashes do not occur as readily soluble forms.

Keywords: Ash, BCR, leaching, solubility, waste

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227 A Sequential Approach to Random-Effects Meta-Analysis

Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

Abstract:

The objective of meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence base for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research significantly changed over time and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable only to fixed effect model (FEM) of meta-analysis. For random-effects model (REM), the analysis incorporates the heterogeneity variance, τ 2 and its estimation create complications. In this paper we study the use of a truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring in REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of applications.

Keywords: Meta-analysis, random-effects model, sequential testing, temporal changes in effect sizes.

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226 Cephalometric Changes of Patient with Class II Division 1 [Malocclusion] Post Orthodontic Treatment with Growth Stimulation: A Case Report

Authors: Pricillia Priska Sianita

Abstract:

An aesthetic facial profile is one of the goals in Orthodontics treatment. However, this is not easily achieved, especially in patients with Class II Division 1 malocclusion who have the clinical characteristics of convex profile and significant skeletal discrepancy due to mandibular growth deficiency. Malocclusion with skeletal problems require proper treatment timing for growth stimulation, and it must be done in early age and in need of good cooperation from the patient. If this is not done and the patient has passed the growth period, the ideal treatment is orthognathic surgery which is more complicated and more painful. The growth stimulation of skeletal malocclusion requires a careful cephalometric evaluation ranging from diagnosis to determine the parts that require stimulation to post-treatment evaluation to see the success achieved through changes in the measurement of the skeletal parameters shown in the cephalometric analysis. This case report aims to describe skeletal changes cephalometrically that were achieved through orthodontic treatment in growing period. Material and method: Lateral Cephalograms, pre-treatment, and post-treatment of cases of Class II Division 1 malocclusion is selected from a collection of cephalometric radiographic in a private clinic. The Cephalogram is then traced and measured for the skeletal parameters. The result is noted as skeletal condition data of pre-treatment and post-treatment. Furthermore, superimposition is done to see the changes achieved. The results show that growth stimulation through orthodontic treatment can solve the skeletal problem of Class II Division 1 malocclusion and the skeletal changes that occur can be verified through cephalometric analysis. The skeletal changes have an impact on the improvement of patient's facial profile. To sum up, the treatment timing on a skeletal malocclusion is very important to obtain satisfactory results for the improvement of the aesthetic facial profile, and skeletal changes can be verified through cephalometric evaluation of pre- and post-treatment.

Keywords: Cephalometric evaluation, Class II Division 1 malocclusion, growth stimulation, skeletal changes, skeletal problems.

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225 Applying Sequential Pattern Mining to Generate Block for Scheduling Problems

Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

Abstract:

The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: Combinatorial problems, Sequential Pattern Mining, Estimation of Distribution Algorithms, Artificial Chromosomes.

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224 Application and Limitation of Parallel Modelingin Multidimensional Sequential Pattern

Authors: Mahdi Esmaeili, Mansour Tarafdar

Abstract:

The goal of data mining algorithms is to discover useful information embedded in large databases. One of the most important data mining problems is discovery of frequently occurring patterns in sequential data. In a multidimensional sequence each event depends on more than one dimension. The search space is quite large and the serial algorithms are not scalable for very large datasets. To address this, it is necessary to study scalable parallel implementations of sequence mining algorithms. In this paper, we present a model for multidimensional sequence and describe a parallel algorithm based on data parallelism. Simulation experiments show good load balancing and scalable and acceptable speedup over different processors and problem sizes and demonstrate that our approach can works efficiently in a real parallel computing environment.

Keywords: Sequential Patterns, Data Mining, ParallelAlgorithm, Multidimensional Sequence Data

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223 The Effect of Electrical Stimulation Intensity on VEGF Expression and Biomechanical Properties during Wound

Authors: M R Asadi, G Torkaman, M Hedayati

Abstract:

We evaluated the effect of sensory (direct current (DC), 600μA) and motor (monophasic current, pulse duration 300μs, 100 Hz, 2.5-3mA) intensities of cathodal electrical stimulation (ES) current to release VEGF and biomechanical properties of wound. 54 male Sprague-dawley rats were randomly assigned into one control and two experimental groups. A full thickness skin incision was made on animals- dorsal region. The experimental groups received ES for 1h/day and every other day. VEGF expression was measured in skin on the 7th day after surgical incision and tensile strength was measured on 21st day. On the 7th day, the values of skin VEGF in the sensory group were significantly greater than those of the other groups (p < 0.05). Sensory and Motor intensity stimulation, can not improve the biomechanical properties of the repaired wounds. It seems the mechanical environment induced by sensory and motor intensity of electrical stimulation, could not simulate the role of normal daily stress and strain to maturation of collagen fibers and their cross links. Further work is needed to determine the relationship between VEGF expression after ES and its effect on tensile strength of healed wound.

Keywords: Biomechanical properties Direct current, Monophasic current, Skin, VEGF

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222 Morphology Study of Inverted Planar Heterojunction Perovskite Solar Cells in Sequential Deposition

Authors: Asmat Nawaz, Ali Koray Erdinc, Burak Gultekin, Muhammad Tayyib, Ceylan Zafer, Kaiying Wang, M. Nadeem Akram

Abstract:

In this study, a sequential deposition process is used for the fabrication of PEDOT: PSS based inverted planar perovskite solar cell. A small amount of additive deionized water (DI-H2O) was added into PbI2 + Dimethyl formamide (DMF) precursor solution in order to increase the solubility of PbI2 in DMF, and finally to manipulate the surface morphology of the perovskite films. A morphology transition from needle like structure to hexagonal plates, and then needle-like again has been observed as the DI-H2O was added continuously (0.0 wt% to 3.0wt%). The latter one leads to full surface coverage of the perovskite, which is essential for high performance solar cell.

Keywords: Charge carrier diffusion lengths, methylamonium lead iodide, precursor composition, perovskite solar cell, sequential deposition.

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221 Effect of FES Cycling Training on Spasticity in Spinal Cord Injured Subjects

Authors: Werner Reichenfelser, Harald Hackl, Josef Hufgard, Karin Gstaltner, Margit Gfoehler

Abstract:

Training with Functional Electrical Stimulation (FES) has both physiological and psychological benefits for spinal cord injured subjects. Commonly used methods for quantification of spasticity have shown controversial reliability. In this study we propose a method for quick determination of spasticity in spinal cord injured subjects on a cycling and measurement system. 23 patients did training sessions on an instrumented mobile FES cycle three times a week over two months as part of their clinical rehabilitation program. Spasticity (MAS) and the legs resistance to the pedaling motion were assessed before and after the FES training and measurements were done on the subjects ability to pedal with our without motor assistance. Measurements with test persons with incomplete spastic paraplegia have shown that spasticity is decreased after a 30 min cycling training with functional electrical stimulation (FES).

Keywords: Spasticity, paraplegia, spinal cord injury, functional electrical stimulation.

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220 A Robotic Rehabilitation Arm Driven by Somatosensory Brain-Computer Interface

Authors: Jiewei Li, Hongyan Cui, Chunqi Chang, Yong Hu

Abstract:

It was expected to benefit patient with hemiparesis after stroke by extensive arm rehabilitation, to partially regain forearm and hand function. This paper propose a robotic rehabilitation arm in assisting the hemiparetic patient to learn new ways of using and moving their weak arms. In this study, the robotic arm was driven by a somatosensory stimulated brain computer interface (BCI), which is a new modality BCI. The use of somatosensory stimulation is not only an input for BCI, but also a electrical stimulation for treatment of hemiparesis to strengthen the arm and improve its range of motion. A trial of this robotic rehabilitation arm was performed in a stroke patient with pure motor hemiparesis. The initial trial showed a promising result from the patient with great motivation and function improvement. It suggests that robotic rehabilitation arm driven by somatosensory BCI can enhance the rehabilitation performance and progress for hemiparetic patients after stroke.

Keywords: Robotic rehabilitation arm, brain computer interface (BCI), hemiparesis, stroke, somatosensory stimulation.

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219 Alternative Acidizing Fluids and Their Impact on the Southern Algerian Shale Formations

Authors: Rezki Akkal, Mohamed Khodja, Slimane Azzi

Abstract:

Acidification is a technique used in oil reservoirs to improve annual production, reduce the skin and increase the pressure of an oil well while eliminating the formation damage that occurs during the drilling process, completion and, amongst others, to create new channels allowing the easy circulation of oil around a producing well. This is achieved by injecting an acidizing fluid at a relatively low pressure to prevent fracturing formation. The treatment fluid used depends on the type and nature of the reservoir rock traversed as well as its petrophysical properties. In order to understand the interaction mechanisms between the treatment fluids used for the reservoir rock acidizing, several candidate wells for stimulation were selected in the large Hassi Messaoud deposit in southern Algeria. The stimulation of these wells is completed using different fluids composed mainly of HCl acid with other additives such as corrosion inhibitors, clay stabilizers and iron controllers. These treatment fluids are injected over two phases, namely with clean tube (7.5% HCl) and matrix aidizing with HCl (15%). The stimulation results obtained are variable according to the type of rock traversed and its mineralogical composition. These results show that there has been an increase in production flow and head pressure respectively from 1.99 m3 / h to 3.56 m3 / h and from 13 Kgf / cm2 to 20 kgf / cm2 in the sands formation having good petrophysical properties of (porosity = 16%) and low amount of clay (Vsh = 6%).

Keywords: Acidizing, Hassi-Messaoud reservoir, tube clean, matrix stimulation.

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218 Revised PLWAP Tree with Non-frequent Items for Mining Sequential Pattern

Authors: R. Vishnu Priya, A. Vadivel

Abstract:

Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.

Keywords: Sequential pattern mining, weblog, frequent and non-frequent items, incremental and interactive mining.

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217 A New Brazilian Friction-Resistant Low Alloy High Strength Steel – A Life Testing Approach

Authors: D. I. De Souza, G. P. Azevedo, R. Rocha

Abstract:

In this paper we will develop a sequential life test approach applied to a modified low alloy-high strength steel part used in highway overpasses in Brazil.We will consider two possible underlying sampling distributions: the Normal and theInverse Weibull models. The minimum life will be considered equal to zero. We will use the two underlying models to analyze a fatigue life test situation, comparing the results obtained from both.Since a major chemical component of this low alloy-high strength steel part has been changed, there is little information available about the possible values that the parameters of the corresponding Normal and Inverse Weibull underlying sampling distributions could have. To estimate the shape and the scale parameters of these two sampling models we will use a maximum likelihood approach for censored failure data. We will also develop a truncation mechanism for the Inverse Weibull and Normal models. We will provide rules to truncate a sequential life testing situation making one of the two possible decisions at the moment of truncation; that is, accept or reject the null hypothesis H0. An example will develop the proposed truncated sequential life testing approach for the Inverse Weibull and Normal models.

Keywords: Sequential life testing, normal and inverse Weibull models, maximum likelihood approach, truncation mechanism.

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216 Mining Sequential Patterns Using I-PrefixSpan

Authors: Dhany Saputra, Dayang R. A. Rambli, Oi Mean Foong

Abstract:

In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use sufficient data structure for Seq-Tree framework and separator database to reduce the execution time and memory usage. Thus, with I-PrefixSpan there is no in-memory database stored after index set is constructed. The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.

Keywords: ArrayList, ArrayIntList, minimum support, sequence database, sequential patterns.

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215 Spiral Cuff for Fiber-Diameter Selective VNS

Authors: P. Pečlin, J. Rozman

Abstract:

In this paper we present the modeling, design, and experimental testing of a nerve cuff multi-electrode system for diameter-selective vagus nerve stimulation. The multi-electrode system contained ninety-nine platinum electrodes embedded within a self-curling spiral silicone sheet. The electrodes were organized in a matrix having nine parallel groups, each containing eleven electrodes. Preliminary testing of the nerve cuff was performed in an isolated segment of a swinish left cervical vagus nerve. For selective vagus nerve stimulation, precisely defined current quasitrapezoidal, asymmetric and biphasic stimulating pulses were applied to preselected locations along the left vagus segment via appointed group of three electrodes within the cuff. Selective stimulation was obtained by anodal block. However, these pulses may not be safe for a long-term application because of a frequently used high imbalance between the cathodic and anodic part of the stimulating pulse. Preliminary results show that the cuff was capable of exciting A and B-fibres, and, that for a certain range of parameters used in stimulating pulses, the contribution of A-fibres to the CAP was slightly reduced and the contribution of B-fibres was slightly larger. Results also showed that measured CAPs are not greatly influenced by the imbalance between a charge Qc injected in cathodic and Qa in anodic phase of quasitrapezoidal, asymmetric and biphasic pulses.

Keywords: Vagus nerve stimulation, multi-electrode nerve cuff.

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214 Time-Derivative Estimation of Noisy Movie Data using Adaptive Control Theory

Authors: Soon-Hyun Park, Takami Matsuo

Abstract:

This paper presents an adaptive differentiator of sequential data based on the adaptive control theory. The algorithm is applied to detect moving objects by estimating a temporal gradient of sequential data at a specified pixel. We adopt two nonlinear intensity functions to reduce the influence of noises. The derivatives of the nonlinear intensity functions are estimated by an adaptive observer with σ-modification update law.

Keywords: Adaptive estimation, parameter adjustmentlaw, motion detection, temporal gradient, differential filter.

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213 Bayesian Online Learning of Corresponding Points of Objects with Sequential Monte Carlo

Authors: Miika Toivanen, Jouko Lampinen

Abstract:

This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.

Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.

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212 A Combined Approach of a Sequential Life Testing and an Accelerated Life Testing Applied to a Low-Alloy High Strength Steel Component

Authors: D. I. De Souza, D. R. Fonseca, G. P. Azevedo

Abstract:

Sometimes the amount of time available for testing could be considerably less than the expected lifetime of the component. To overcome such a problem, there is the accelerated life-testing alternative aimed at forcing components to fail by testing them at much higher-than-intended application conditions. These models are known as acceleration models. One possible way to translate test results obtained under accelerated conditions to normal using conditions could be through the application of the “Maxwell Distribution Law.” In this paper we will apply a combined approach of a sequential life testing and an accelerated life testing to a low alloy high-strength steel component used in the construction of overpasses in Brazil. The underlying sampling distribution will be three-parameter Inverse Weibull model. To estimate the three parameters of the Inverse Weibull model we will use a maximum likelihood approach for censored failure data. We will be assuming a linear acceleration condition. To evaluate the accuracy (significance) of the parameter values obtained under normal conditions for the underlying Inverse Weibull model we will apply to the expected normal failure times a sequential life testing using a truncation mechanism. An example will illustrate the application of this procedure.

Keywords: Sequential Life Testing, Accelerated Life Testing, Underlying Three-Parameter Weibull Model, Maximum Likelihood Approach, Hypothesis Testing.

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211 Propane Dehydrogenation with Better Stability by a Modified Pt-Based Catalyst

Authors: N. Hataivichian, K. Suriye, S. Kunjara Na Ayudhya, P. Praserthdam, S. Phatanasri

Abstract:

The effect of transition metal doping on Pt/Al2O3 catalyst used in propane dehydrogenation reaction at 500°C was studied. The preparation methods investigated were sequential impregnation (Pt followed by the 2nd metal or the 2nd metal followed by Pt) and co-impregnation. The metal contents of these catalysts were fixed as the weight ratio of Pt per the 2nd metal of around 0.075. These catalysts were characterized by N2-physisorption, TPR, COchemisorption and NH3-TPD. It was found that the impregnated 2nd metal had an effect upon reducibility of Pt due to its interaction with transition metal-containing structure. This was in agreement with the CO-chemisorption result that the presence of Pt metal, which is a result from Pt species reduction, was decreased. The total acidity of bimetallic catalysts is decreased but the strong acidity is slightly increased. It was found that the stability of bimetallic catalysts prepared by co-impregnation and sequential impregnation where the 2nd metal was impregnated before Pt were better than that of monometallic catalyst (undoped Pt one) due to the forming of Pt sites located on the transition metal-oxide modified surface. Among all preparation methods, the sequential impregnation method- having Pt impregnated before the 2nd metal gave the worst stability because this catalyst lacked the modified Pt sites and some fraction of Pt sites was covered by the 2nd metal.

Keywords: Alumina, dehydrogenation, platinum, transition metal.

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210 An Adequate Choice of Initial Sample Size for Selection Approach

Authors: Mohammad H. Almomani, Rosmanjawati Abdul Rahman

Abstract:

In this paper, we consider the effect of the initial sample size on the performance of a sequential approach that used in selecting a good enough simulated system, when the number of alternatives is very large. We implement a sequential approach on M=M=1 queuing system under some parameter settings, with a different choice of the initial sample sizes to explore the impacts on the performance of this approach. The results show that the choice of the initial sample size does affect the performance of our selection approach.

Keywords: Ranking and Selection, Ordinal Optimization, Optimal Computing Budget Allocation, Subset Selection, Indifference-Zone, Initial Sample Size.

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209 Combined Effect of Heat Stimulation and Delayed Addition of Superplasticizer with Slag on Fresh and Hardened Property of Mortar

Authors: Faraidoon Rahmanzai, Mizuki Takigawa, Yu Bomura, Shigeyuki Date

Abstract:

To obtain the high quality and essential workability of mortar, different types of superplasticizers are used. The superplasticizers are the chemical admixture used in the mix to improve the fluidity of mortar. Many factors influenced the superplasticizer to disperse the cement particle in the mortar. Nature and amount of replaced cement by slag, mixing procedure, delayed addition time, and heat stimulation technique of superplasticizer cause the varied effect on the fluidity of the cementitious material. In this experiment, the superplasticizers were heated for 1 hour under 60 °C in a thermostatic chamber. Furthermore, the effect of delayed addition time of heat stimulated superplasticizers (SP) was also analyzed. This method was applied to two types of polycarboxylic acid based ether SP (precast type superplasticizer (SP2) and ready-mix type superplasticizer (SP1)) in combination with a partial replacement of normal Portland cement with blast furnace slag (BFS) with 30% w/c ratio. On the other hands, the fluidity, air content, fresh density, and compressive strength for 7 and 28 days were studied. The results indicate that the addition time and heat stimulation technique improved the flow and air content, decreased the density, and slightly decreased the compressive strength of mortar. Moreover, the slag improved the flow of mortar by increasing the amount of slag, and the effect of external temperature of SP on the flow of mortar was decreased. In comparison, the flow of mortar was improved on 5-minute delay for both kinds of SP, but SP1 has improved the flow in all conditions. Most importantly, the transition points in both types of SP appear to be the same, at about 5±1 min.  In addition, the optimum addition time of SP to mortar should be in this period.

Keywords: Combined effect, delayed addition, heat stimulation, flow of mortar.

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208 A Constructivist Approach and Tool for Autonomous Agent Bottom-up Sequential Learning

Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

Abstract:

During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: Cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation.

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207 Close Loop Controlled Current Nerve Locator

Authors: H. A. Alzomor, B. K. Ouda, A. M. Eldeib

Abstract:

Successful regional anesthesia depends upon precise location of the peripheral nerve or nerve plexus. Locating peripheral nerves is preferred to be done using nerve stimulation. In order to generate a nerve impulse by electrical means, a minimum threshold stimulus of current “rheobase” must be applied to the nerve. The technique depends on stimulating muscular twitching at a close distance to the nerve without actually touching it. Success rate of this operation depends on the accuracy of current intensity pulses used for stimulation .In this paper, we will discuss a circuit and algorithm for closed loop control for the current, theoretical analysis and test results is discussed and results is compared to previous techniques.

Keywords: Close Loop Control, Constant Current, Nerve Locator.

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206 A Heuristic for the Integrated Production and Distribution Scheduling Problem

Authors: Christian Meinecke, Bernd Scholz-Reiter

Abstract:

The integrated problem of production and distribution scheduling is relevant in many industrial applications. Thus, many heuristics to solve this integrated problem have been developed in the last decade. Most of these heuristics use a sequential working principal or a single decomposition and integration approach to separate and solve subproblems. A heuristic using a multi step decomposition and integration approach is presented in this paper and evaluated in a case study. The result show significant improved results compared with sequential scheduling heuristics.

Keywords: Production and outbound distribution, integrated planning, heuristic, decomposition and integration.

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205 Non-Destructive Testing of Carbon Fiber Reinforced Plastic by Infrared Thermography Methods

Authors: W. Swiderski

Abstract:

Composite materials are one answer to the growing demand for materials with better parameters of construction and exploitation. Composite materials also permit conscious shaping of desirable properties to increase the extent of reach in the case of metals, ceramics or polymers. In recent years, composite materials have been used widely in aerospace, energy, transportation, medicine, etc. Fiber-reinforced composites including carbon fiber, glass fiber and aramid fiber have become a major structural material. The typical defect during manufacture and operation is delamination damage of layered composites. When delamination damage of the composites spreads, it may lead to a composite fracture. One of the many methods used in non-destructive testing of composites is active infrared thermography. In active thermography, it is necessary to deliver energy to the examined sample in order to obtain significant temperature differences indicating the presence of subsurface anomalies. To detect possible defects in composite materials, different methods of thermal stimulation can be applied to the tested material, these include heating lamps, lasers, eddy currents, microwaves or ultrasounds. The use of a suitable source of thermal stimulation on the test material can have a decisive influence on the detection or failure to detect defects. Samples of multilayer structure carbon composites were prepared with deliberately introduced defects for comparative purposes. Very thin defects of different sizes and shapes made of Teflon or copper having a thickness of 0.1 mm were screened. Non-destructive testing was carried out using the following sources of thermal stimulation, heating lamp, flash lamp, ultrasound and eddy currents. The results are reported in the paper.

Keywords: Non-destructive testing, IR thermography, composite material, thermal stimulation.

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204 Action Potential of Lateral Geniculate Neurons at Low Threshold Currents: Simulation Study

Authors: Faris Tarlochan, Siva Mahesh Tangutooru

Abstract:

Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 μm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral geniculate nucleus, visual cortex, finite element, glaucoma, neuroprostheses.

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203 Lead in The Soil-Plant System Following Aged Contamination from Ceramic Wastes

Authors: F. Pedron, M. Grifoni, G. Petruzzelli, M. Barbafieri, I. Rosellini, B. Pezzarossa

Abstract:

Lead contamination of agricultural land mainly vegetated with perennial ryegrass (Lolium perenne) has been investigated. The metal derived from the discharge of sludge from a ceramic industry in the past had used lead paints. The results showed very high values of lead concentration in many soil samples. In order to assess the lead soil contamination, a sequential extraction with H2O, KNO3, EDTA was performed, and the chemical forms of lead in the soil were evaluated. More than 70% of lead was in a potentially bioavailable form. Analysis of Lolium perenne showed elevated lead concentration. A Freundlich-like model was used to describe the transferability of the metal from the soil to the plant.

Keywords: Bioavailability, Freundlich-like equation, sequential extraction, soil lead contamination.

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202 An Edit-Distance Algorithm to Detect Correlated Attacks in Distributed Systems

Authors: Sule Simsek

Abstract:

Intrusion detection systems (IDS)are crucial components of the security mechanisms of today-s computer systems. Existing research on intrusion detection has focused on sequential intrusions. However, intrusions can also be formed by concurrent interactions of multiple processes. Some of the intrusions caused by these interactions cannot be detected using sequential intrusion detection methods. Therefore, there is a need for a mechanism that views the distributed system as a whole. L-BIDS (Lattice-Based Intrusion Detection System) is proposed to address this problem. In the L-BIDS framework, a library of intrusions and distributed traces are represented as lattices. Then these lattices are compared in order to detect intrusions in the distributed traces.

Keywords: Attack graph, distributed, edit-distance, misuse detection.

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201 Volatility of Cu, Ni, Cr, Co, Pb, and As in Fluidised-Bed Combustion Chamber in Relation to Their Modes of Occurrence in Coal

Authors: L. Bartoňová, Z. Klika

Abstract:

Modes of occurrence of Pb, As, Cr, Co, Cu, and Ni in bituminous coal and lignite were determined by means of sequential extraction using NH4OAc, HCl, HF and HNO3 extraction solutions. Elemental affinities obtained were then evaluated in relation to volatility of these elements during the combustion of these coals in two circulating fluidised-bed power stations. It was found out that higher percentage of the elements bound in silicates brought about lower volatility, while higher elemental proportion with monosulphides association (or bound as exchangeable ion) resulted in higher volatility. The only exception was the behavior of arsenic, whose volatility depended on amount of limestone added during the combustion process (as desulphurisation additive) rather than to its association in coal.

Keywords: Coal combustion, sequential extraction, trace elements, volatility.

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200 Sequential Partitioning Brainbow Image Segmentation Using Bayesian

Authors: Yayun Hsu, Henry Horng-Shing Lu

Abstract:

This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate crosstalk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds, since biological information is inherently included inside the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: Brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning.

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