Search results for: Shear field test method

Authors: Kifah Tout, Nisrine Sinno, Mohamad Mikati

Abstract:

Many studies have focused on the nonlinear analysis of electroencephalography (EEG) mainly for the characterization of epileptic brain states. It is assumed that at least two states of the epileptic brain are possible: the interictal state characterized by a normal apparently random, steady-state EEG ongoing activity; and the ictal state that is characterized by paroxysmal occurrence of synchronous oscillations and is generally called in neurology, a seizure. The spatial and temporal dynamics of the epileptogenic process is still not clear completely especially the most challenging aspects of epileptology which is the anticipation of the seizure. Despite all the efforts we still don-t know how and when and why the seizure occurs. However actual studies bring strong evidence that the interictal-ictal state transition is not an abrupt phenomena. Findings also indicate that it is possible to detect a preseizure phase. Our approach is to use the neural network tool to detect interictal states and to predict from those states the upcoming seizure ( ictal state). Analysis of the EEG signal based on neural networks is used for the classification of EEG as either seizure or non-seizure. By applying prediction methods it will be possible to predict the upcoming seizure from non-seizure EEG. We will study the patients admitted to the epilepsy monitoring unit for the purpose of recording their seizures. Preictal, ictal, and post ictal EEG recordings are available on such patients for analysis The system will be induced by taking a body of samples then validate it using another. Distinct from the two first ones a third body of samples is taken to test the network for the achievement of optimum prediction. Several methods will be tried 'Backpropagation ANN' and 'RBF'.

Keywords: Artificial neural network (ANN), automatic prediction, epileptic seizures analysis, genetic algorithm.

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Authors: D. Fodorean, D.C. Popa, F. Jurca, M. Ruba

Abstract:

the paper presents the optimization results for several electrical machines dedicated for powered electric wheel-chairs. The optimization, using the Hook-Jeeves algorithm, was employed based on a design approach which takes into consideration the road conditions. Also, through numerical simulations (based on finite element method), the analytical approach was validated. The optimization approach gave satisfactory results and the best suited variant was chosen for the motorization of the wheel-chair.

Keywords: electrical machines, numerical validation, optimization, electric wheel chair.

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Authors: Sam S. Hashemi

Abstract:

The breakage of bonding between sand particles and their dislodgment from the borehole wall are among the main factors resulting in a borehole failure in poorly cemented granular formations. The grain debonding usually precedes the borehole failure and it can be considered as a sign that the onset of the borehole collapse is imminent. Detecting the bonding breakage point and introducing an appropriate failure criterion will play an important role in borehole stability analysis. To study the influence of different factors on the initiation of sand bonding breakage at the borehole wall, a series of laboratory tests was designed and conducted on poorly cemented sand samples. The total absorbed strain energy per volume of material up to the point of the observed particle debonding was computed. The results indicated that the particle bonding breakage point at the borehole wall was reached both before and after the peak strength of the thick-walled hollow cylinder specimens depending on the stress path and cement content. Three different cement contents and two borehole sizes were investigated to study the influence of the bonding strength and scale on the particle dislodgment. Test results showed that the stress path has a significant influence on the onset of the sand bonding breakage. It was shown that for various stress paths, there is a near linear relationship between the absorbed energy and the normal effective mean stress.

Keywords: Borehole stability, experimental studies, total strain energy, poorly cemented sands, particle bonding breakage.

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Authors: Rihab Gam, Anis Sakly, Faouzi M'sahli

Abstract:

A new strategy of control is formulated for chaos synchronization of non-identical chaotic systems with different orders using the Borne and Gentina practical criterion associated with the Benrejeb canonical arrow form matrix, to drift the stability property of dynamic complex systems. The designed controller ensures that the state variables of controlled chaotic slave systems globally synchronize with the state variables of the master systems, respectively. Numerical simulations are performed to illustrate the efficiency of the proposed method.

Keywords: Synchronization, Non-identical chaotic systems, Different orders, Arrow form matrix.

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Authors: Abhishek Soni, Bhagat Singh

Abstract:

In this study, scanned data of a damaged femur diaphysis are used to generate three dimensional model of the bone. Further, customized implant of Hydroxyapatite-Polyetheretherketone (HA-PEEK) material for this damaged bone is prepared using CAD modeling. Damaged bone and implant have been assembled to prepare the intact bone. This assembled model has been analyzed to evaluate the stresses and deformation developed during the static loading. It has been observed that these stresses and deformation are very less thus imply that the proposed method of preparing implant is appropriate.

Keywords: Customized implant, deformation, femur diaphysis, stress.

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Authors: Y. N. Phang, E. F. Loh

Abstract:

Zero inflated Strict Arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, maximum likelihood estimation method is used in estimating the parameters for zero inflated strict arcsine model. Bootstrapping is then employed to compute the confidence intervals for the estimated parameters.

Keywords: overdispersed count data, maximum likelihood estimation, simulated annealing, BCa confidence intervals.

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Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

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This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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Authors: Simon Brown, Noorzaid Muhamad, David C Simcock

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The kinetic properties of enzymes are often reported using the apparent KM and Vmax appropriate to the standard Michaelis-Menten enzyme. However, this model is inappropriate to enzymes that have more than one substrate or where the rate expression does not apply for other reasons. Consequently, it is desirable to have a means of estimating the appropriate kinetic parameters from the apparent values of KM and Vmax reported for each substrate. We provide a means of estimating the range within which the parameters should lie and apply the method to data for glutamate dehydrogenase from the nematode parasite of sheep Teladorsagia circumcincta.

Keywords: enzyme kinetics, glutamate dehydrogenase, intervalanalysis, parameter estimation.

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Authors: Muhammad E. Rahman, Trevor Orr

Abstract:

This paper presents the use of three-dimensional finite elements coupled with infinite elements to investigate the ground vibrations at the surface in terms of the peak particle velocity (PPV) due to construction of the first bore of the Dublin Port Tunnel. This situation is analysed using a commercially available general-purpose finite element package ABAQUS. A series of parametric studies is carried out to examine the sensitivity of the predicted vibrations to variations in the various input parameters required by finite element method, including the stiffness and the damping of ground. The results of this study show that stiffness has a more significant effect on the PPV rather than the damping of the ground.

Keywords: Finite Elements, PPV, Tunnelling, Vibration

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications.

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Authors: N. H. Othman, N. Udin, M. Ishak, L. H. Shah

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This study focuses on the effect of pin taper tool ratio on friction stir welding of magnesium alloy AZ31. Two pieces of AZ31 alloy with thickness of 6 mm were friction stir welded by using the conventional milling machine. The shoulder diameter used in this experiment is fixed at 18 mm. The taper pin ratio used are varied at 6:6, 6:5, 6:4, 6:3, 6:2 and 6:1. The rotational speeds that were used in this study were 500 rpm, 1000 rpm and 1500 rpm, respectively. The welding speeds used are 150 mm/min, 200 mm/min and 250 mm/min. Microstructure observation of welded area was studied by using optical microscope. Equiaxed grains were observed at the TMAZ and stir zone indicating fully plastic deformation. Tool pin diameter ratio 6/1 causes low heat input to the material because of small contact surface between tool surface and stirred materials compared to other tool pin diameter ratio. The grain size of stir zone increased with increasing of ratio of rotational speed to transverse speed due to higher heat input. It is observed that worm hole is produced when excessive heat input is applied. To evaluate the mechanical properties of this specimen, tensile test was used in this study. Welded specimens using taper pin ratio 6:1 shows higher tensile strength compared to other taper pin ratio up to 204 MPa. Moreover, specimens using taper pin ratio 6:1 showed better tensile strength with 500 rpm of rotational speed and 150mm/min welding speed.

Keywords: Friction stir welding, magnesium AZ31, cylindrical taper tool, taper pin ratio.

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Authors: Derya Eren Akyol, Gonca Tuncel, G. Mirac Bayhan

Abstract:

Activity-Based Costing (ABC) which has become an important aspect of manufacturing/service organizations can be defined as a methodology that measures the cost and performance of activities, resources and cost objects. It can be considered as an alternative paradigm to traditional cost-based accounting systems. The objective of this paper is to illustrate an application of ABC method and to compare the results of ABC with traditional costing methods. The results of the application highlight the weak points of traditional costing methods and an S-Curve obtained is used to identify the undercosted and overcosted products of the firm.

Keywords: Activity-based costing, cost drivers, overheads, traditional costing.

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Authors: A. Fathianpour, M. B. Jelodar, S. Wilkinson

Abstract:

This paper outlines the approaches taken to assess multi-hazard assessments. There is currently confusion in assessing multi-hazard impacts, and so this study aims to determine which of the available options are the most useful. The paper uses an international literature search, and analysis of current multi-hazard assessments and a case study to illustrate the effectiveness of the chosen method. Findings from this study will help those wanting to assess multi-hazards to undertake a straightforward approach. The paper is significant as it helps to interpret the various approaches and concludes with the preferred method. Many people in the world live in hazardous environments and are susceptible to disasters. Unfortunately, when a disaster strikes it is often compounded by additional cascading hazards, thus people would confront more than one hazard simultaneously. Hazards include natural hazards (earthquakes, floods, etc.) or cascading human-made hazards (for example, Natural Hazard Triggering Technological disasters (Natech) such as fire, explosion, toxic release). Multi-hazards have a more destructive impact on urban areas than one hazard alone. In addition, climate change is creating links between different disasters such as causing landslide dams and debris flows leading to more destructive incidents. Much of the prevailing literature deals with only one hazard at a time. However, recently sophisticated multi-hazard assessments have started to appear. Given that multi-hazards occur, it is essential to take multi-hazard risk assessment under consideration. This paper aims to review the multi-hazard assessment methods through articles published to date and categorize the strengths and disadvantages of using these methods in risk assessment. Napier City is selected as a case study to demonstrate the necessity of using multi-hazard risk assessments. In order to assess multi-hazard risk assessments, first, the current multi-hazard risk assessment methods were described. Next, the drawbacks of these multi-hazard risk assessments were outlined. Finally, the improvements to current multi-hazard risk assessments to date were summarised. Generally, the main problem of multi-hazard risk assessment is to make a valid assumption of risk from the interactions of different hazards. Currently, risk assessment studies have started to assess multi-hazard situations, but drawbacks such as uncertainty and lack of data show the necessity for more precise risk assessment. It should be noted that ignoring or partial considering multi-hazards in risk assessment will lead to an overestimate or overlook in resilient and recovery action managements.

Keywords: Cascading hazards, multi-hazard, risk assessment, risk reduction.

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Authors: Parvinder S. Sandhu, Sandeep Khimta, Kiranpreet Kaur

Abstract:

The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.

Keywords: Growing Neural Gas, data clustering, fault prediction.

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Authors: J. K. Shrestha, A. Benta, R. B. Lopes, N. Lopes

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This work provides a practical method for the development of rural road networks in rural areas of developing countries. The proposed methodology enables to determine obligatory points in the rural road network maximizing the number of settlements that have access to basic services within a given maximum distance. The proposed methodology is simple and practical, hence, highly applicable to real-world scenarios, as demonstrated in the definition of the road network for the rural areas of Nepal.

Keywords: Minimum spanning tree, nodal points, rural road network.

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Authors: Satyendra Nath Mandal, J. Pal Choudhury, Dilip De, S. R. Bhadra Chaudhuri

Abstract:

The production of a plant can be measured in terms of seeds. The generation of seeds plays a critical role in our social and daily life. The fruit production which generates seeds, depends on the various parameters of the plant, such as shoot length, leaf number, root length, root number, etc When the plant is growing, some leaves may be lost and some new leaves may appear. It is very difficult to use the number of leaves of the tree to calculate the growth of the plant.. It is also cumbersome to measure the number of roots and length of growth of root in several time instances continuously after certain initial period of time, because roots grow deeper and deeper under ground in course of time. On the contrary, the shoot length of the tree grows in course of time which can be measured in different time instances. So the growth of the plant can be measured using the data of shoot length which are measured at different time instances after plantation. The environmental parameters like temperature, rain fall, humidity and pollution are also play some role in production of yield. The soil, crop and distance management are taken care to produce maximum amount of yields of plant. The data of the growth of shoot length of some mustard plant at the initial stage (7,14,21 & 28 days after plantation) is available from the statistical survey by a group of scientists under the supervision of Prof. Dilip De. In this paper, initial shoot length of Ken( one type of mustard plant) has been used as an initial data. The statistical models, the methods of fuzzy logic and neural network have been tested on this mustard plant and based on error analysis (calculation of average error) that model with minimum error has been selected and can be used for the assessment of shoot length at maturity. Finally, all these methods have been tested with other type of mustard plants and the particular soft computing model with the minimum error of all types has been selected for calculating the predicted data of growth of shoot length. The shoot length at the stage of maturity of all types of mustard plants has been calculated using the statistical method on the predicted data of shoot length.

Keywords: Fuzzy time series, neural network, forecasting error, average error.

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Authors: K. Kalaikumar, E. Baburaj

Abstract:

One of the problems to be addressed in wireless sensor networks is the issues related to cross layer communication. Cross layer architecture shares the information across the layer, ensuring Quality of Services (QoS). With this shared information, MAC protocol adapts effective functionality maintenance such as route selection on changeable sensor network environment. However, time slot assignment and neighbour route selection time duration for cross layer have not been carried out. The time varying physical layer communication over cross layer causes high traffic load in the sensor network. Though, the traffic load was reduced using cross layer optimization procedure, the computational cost is high. To improve communication efficacy in the sensor network, a self-determined time slot based Cross-Layered Neighbour Route Discovery (C-LNRD) method is presented in this paper. In the presented work, the initial process is to discover the route in the sensor network using Dynamic Source Routing based Medium Access Control (MAC) sub layers. This process considers MAC layer operation with dynamic route neighbour table discovery. Then, the discovered route path for packet communication employs Broad Route Distributed Time Slot Assignment method on Cross-Layered Sensor Network system. Broad Route means time slotting on varying length of the route paths. During packet communication in this sensor network, transmission of packets is adjusted over the different time with varying ranges for controlling the traffic rate. Finally, Rayleigh fading model is developed in C-LNRD to identify the performance of the sensor network communication structure. The main task of Rayleigh Fading is to measure the power level of each communication under MAC sub layer. The minimized power level helps to easily reduce the computational cost of packet communication in the sensor network. Experiments are conducted on factors such as power factor, on packet communication, neighbour route discovery time, and information (i.e., packet) propagation speed.

Keywords: Medium access control, neighbour route discovery, wireless sensor network, Rayleigh fading, distributed time slot assignment

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Authors: Lv Yuhua

Abstract:

In this paper, by establishing a new comparison result, we investigate the existence of positive solutions for initial value problems of nonlinear systems of second order integro-differential equations in Banach space.We improve and generalize some results  (see[5,6]), and the results is new even in finite dimensional spaces.

Keywords: Systems of integro-differential equations, monotone iterative method, comparison result, cone.

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Authors: S. Joshi, D. Pant

Abstract:

Absorption and fluorescence spectra of quinine sulphate (QSD) have been recorded at room temperature in wide range of solvents of different polarities. The ground-state dipole moment of QSD was obtained from quantum mechanical calculations and the excited state dipole moment of QSD was estimated from Bakhshiev-s and Kawski-Chamma-Viallet-s equations by means of solvatochromic shift method. Higher value of dipole moment is observed for excited state as compared to the corresponding ground state value and this is attributed to the more polar excited state of QSD.

Keywords: Dipole moment, Quinine sulphate dication, Solvatochromic shift

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Authors: Hazem M. El-Bakry

Abstract:

Neural processors have shown good results for detecting a certain character in a given input matrix. In this paper, a new idead to speed up the operation of neural processors for character detection is presented. Such processors are designed based on cross correlation in the frequency domain between the input matrix and the weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the searching process. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single faster neural processor. Furthermore, faster character detection is obtained by using parallel processing techniques to test the resulting sub-images at the same time using the same number of faster neural networks. In contrast to using only faster neural processors, the speed up ratio is increased with the size of the input image when using faster neural processors and image decomposition. Moreover, the problem of local subimage normalization in the frequency domain is solved. The effect of image normalization on the speed up ratio of character detection is discussed. Simulation results show that local subimage normalization through weight normalization is faster than subimage normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.

Keywords: Fast Character Detection, Neural Processors, Cross Correlation, Image Normalization, Parallel Processing.

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Authors: Muhammad Irfan Marwat, Sadaqat Jan, Syed Zafar Ali Shah

Abstract:

Software Architecture plays a key role in software development but absence of formal description of Software Architecture causes different impede in software development. To cope with these difficulties, ontology has been used as artifact. This paper proposes ontology for Software Architectural design based on IEEE model for architecture description and Kruchten 4+1 model for viewpoints classification. For categorization of style and views, ISO/IEC 42010 has been used. Corpus method has been used to evaluate ontology. The main aim of the proposed ontology is to classify and locate Software Architectural design information.

Keywords: Software Architecture Ontology, Semantic based Software Architecture, Software Architecture, Ontology, Software Engineering.

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Authors: A. M. Tahsini

Abstract:

Supersonic hydrogen-air cylindrical mixing layer is numerically analyzed to investigate the effect of inlet swirl on ignition time delay in scramjets. Combustion is treated using detail chemical kinetics. One-equation turbulence model of Spalart and Allmaras is chosen to study the problem and advection upstream splitting method is used as computational scheme. The results show that swirling both fuel and oxidizer streams may drastically decrease the ignition distance in supersonic combustion, unlike using the swirl just in fuel stream which has no helpful effect.

Keywords: Ignition delay, Supersonic combustion, Swirl, Numerical simulation, Turbulence.

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Authors: Pathravut Klinklom, Apanee Luengnaruemitchai, Samai Jai-In

Abstract:

In this research, CaO-ZnO catalysts (with various Ca:Zn atomic ratios of 1:5, 1:3, 1:1, and 3:1) prepared by incipientwetness impregnation (IWI) and co-precipitation (CP) methods were used as a catalyst in the transesterification of palm oil with methanol for biodiesel production. The catalysts were characterized by several techniques, including BET method, CO2-TPD, and Hemmett Indicator. The effects of precursor concentration, and calcination temperature on the catalytic performance were studied under reaction conditions of a 15:1 methanol to oil molar ratio, 6 wt% catalyst, reaction temperature of 60°C, and reaction time of 8 h. At Ca:Zn atomic ratio of 1:3 gave the highest FAME value owing to a basic properties and surface area of the prepared catalyst.

Keywords: CaO, ZnO, Biodiesel, Impregnation, Coprecipitation.

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Authors: Cornelia-Eugenia Munteanu

Abstract:

The goal of this paper is to present the diagnostic contribution that the screening instrument, Mini-Mental State Examination-2: Expanded Version (MMSE-2:EV), brings in detecting the cognitive impairment or in monitoring the progress of degenerative disorders. The diagnostic signification is underlined by the interpretation of the MMSE-2:EV scores, resulted from the test application to patients with mild and major neurocognitive disorders. The cases were selected from current practice, in order to cover vast and significant neurocognitive pathology: mild cognitive impairment, Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s disease, conversion of the mild cognitive impairment into Alzheimer’s disease. The MMSE-2:EV version was used: it was applied one month after the initial assessment, three months after the first reevaluation and then every six months, alternating the blue and red forms. Correlated with age and educational level, the raw scores were converted in T scores and then, with the mean and the standard deviation, the z scores were calculated. The differences of raw scores between the evaluations were analyzed from the point of view of statistic signification, in order to establish the progression in time of the disease. The results indicated that the psycho-diagnostic approach for the evaluation of the cognitive impairment with MMSE-2:EV is safe and the application interval is optimal. In clinical settings with a large flux of patients, the application of the MMSE-2:EV is a safe and fast psychodiagnostic solution. The clinicians can draw objective decisions and for the patients: it does not take too much time and energy, it does not bother them and it doesn’t force them to travel frequently.

Keywords: MMSE-2, dementia, cognitive impairment, neuropsychology.

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Authors: Jindřiška Šedová, Miloš Šeda

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This paper summarizes and compares approaches to solving the knapsack problem and its known application in capital budgeting. The first approach uses deterministic methods and can be applied to small-size tasks with a single constraint. We can also apply commercial software systems such as the GAMS modelling system. However, because of NP-completeness of the problem, more complex problem instances must be solved by means of heuristic techniques to achieve an approximation of the exact solution in a reasonable amount of time. We show the problem representation and parameter settings for a genetic algorithm framework.

Keywords: Capital budgeting, knapsack problem, GAMS, heuristic method, genetic algorithm.

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Authors: S. Seyedtabaii, L. Seyedtabaii

Abstract:

Artifact free photoplethysmographic (PPG) signals are necessary for non-invasive estimation of oxygen saturation (SpO2) in arterial blood. Movement of a patient corrupts the PPGs with motion artifacts, resulting in large errors in the computation of Sp02. This paper presents a study on using Kalman Filter in an innovative way by modeling both the Artillery Blood Pressure (ABP) and the unwanted signal, additive motion artifact, to reduce motion artifacts from corrupted PPG signals. Simulation results show acceptable performance regarding LMS and variable step LMS, thus establishing the efficacy of the proposed method.

Keywords: Kalman filter, Motion artifact, PPG, Photoplethysmography.

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Authors: Dmitriy Yu. Korulkin, Ravshan M. Nuraliev, Raissa A. Muzychkina

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In this research paper were investigated the main regularities of a radical bromination reaction of decalin. There had been studied the temperature effect, durations of reaction, frequency rate of process, a ratio of initial components, type and number of the initiator on decalin bromination degree. There were specified optimum conditions of synthesis of a perbromodecalin by the method of a decalin bromination. There are developed the technological flowchart of receiving a perbromodecalin and the mass balance of process on the first and the subsequent loadings of components. The results of research of antibacterial and antifungal activity of synthesized bromoderivatives have been represented.

Keywords: Decalin, optimum technology, perbromodecalin, radical bromination.

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Authors: Eva Pajorová, Ladislav Hluchý

Abstract:

Developed tool is one of system tools for easier access to various scientific areas and real time interactive learning between lecturer and for hearing impaired students. There is no demand for the lecturer to know Sign Language (SL). Instead, the new software tools will perform the translation of the regular speech into SL, after which it will be transferred to the student. On the other side, the questions of the student (in SL) will be translated and transferred to the lecturer in text or speech. One of those tools is presented tool. It-s too for developing the correct Speech Visemes as a root of total communication method for hearing impared students.

Keywords: Impared people, sing language, communication methods.

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Authors: V. K. Bansal, M. Kumar, P. P. Bansal, A. Batish

Abstract:

This paper presents the results of an experimental investigation carried out to evaluate the effects of partial replacement of cement and fine aggregate with industrial waste by-products on concrete strength properties. The Grey Taguchi approach has been used to optimize the mix proportions for desired properties. In this research work, a ternary combination of industrial waste by-products has been used. The experiments have been designed using Taguchi's L9 orthogonal array with four factors having three levels each. The cement was partially replaced by ladle furnace slag (LFS), fly ash (FA) and copper slag (CS) at 10%, 25% and 40% level and fine aggregate (sand) was partially replaced with electric arc furnace slag (EAFS), iron slag (IS) and glass powder (GP) at 20%, 30% and 40% level. Three water to binder ratios, fixed at 0.40, 0.44 and 0.48, were used, and the curing age was fixed at 7, 28 and 90 days. Thus, a series of nine experiments was conducted on the specimens for water to binder ratios of 0.40, 0.44 and 0.48 at 7, 28 and 90 days of the water curing regime. It is evident from the investigations that Grey Taguchi approach for optimization helps in identifying the factors affecting the final outcomes, i.e. compressive strength and split tensile strength of concrete. For the materials and a range of parameters used in this research, the present study has established optimum mixes in terms of strength properties. The best possible levels of mix proportions were determined for maximization through compressive and splitting tensile strength. To verify the results, the optimal mix was produced and tested. The mixture results in higher compressive strength and split tensile strength than other mixes. The compressive strength and split tensile strength of optimal mixtures are also compared with the control concrete mixtures. The results show that compressive strength and split tensile strength of concrete made with partial replacement of cement and fine aggregate is more than control concrete at all ages and w/c ratios. Based on the overall observations, it can be recommended that industrial waste by-products in ternary combinations can effectively be utilized as partial replacements of cement and fine aggregates in all concrete applications.

Keywords: Analysis of variance, ANOVA, compressive strength, concrete, grey Taguchi method, industrial by-products, split tensile strength.

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Authors: Ridha Ghayoula, Mbarek Traii, Ali Gharsallah

Abstract:

In this paper, we intend to study the synthesis of the multibeam arrays. The synthesis implementation-s method for this type of arrays permits to approach the appropriated radiance-s diagram. The used approach is based on neural network that are capable to model the multibeam arrays, consider predetermined general criteria-s, and finally it permits to predict the appropriated diagram from the neural model. Our main contribution in this paper is the extension of a synthesis model of these multibeam arrays.

Keywords: Multibeam, modelling, neural networks, synthesis, antennas.

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