Search results for: stage directions

Authors: T. B. Karu Jayasundara

Abstract:

Regions of low gravity and gravity anomalies both influence heavy mineral concentrations on placer deposits. Economically imported heavy minerals are likely to have higher levels of deposition in low gravity regions of placer deposits. This can be found in coastal regions of Southern Asia, particularly in Sri Lanka and Peninsula India and areas located in the lowest gravity region of the world. The area about 70 kilometers of the east coast of Sri Lanka is covered by a high percentage of ilmenite deposits, and the southwest coast of the island consists of Monazite placer deposit. These deposits are one of the largest placer deposits in the world. In India, the heavy mineral industry has a good market. On the other hand, based on the coastal placer deposits recorded, the high gravity region located around Papua New Guinea, has no such heavy mineral deposits. In low gravity regions, with the help of other depositional environmental factors, the grains have more time and space to float in the sea, this helps bring high concentrations of heavy mineral deposits to the coast. The effect of low and high gravity can be demonstrated by using heavy mineral separation devices.  The Wilfley heavy mineral separating table is one of these; it is extensively used in industries and in laboratories for heavy mineral separation. The horizontally oscillating Wilfley table helps to separate heavy and light mineral grains in to deferent fractions, with the use of water. In this experiment, the low and high angle of the Wilfley table are representing low and high gravity respectively. A sample mixture of grain size <0.85 mm of heavy and light mineral grains has been used for this experiment. The high and low angle of the table was 6⁰ and 2⁰ respectively for this experiment. The separated fractions from the table are again separated into heavy and light minerals, with the use of heavy liquid, which consists of a specific gravity of 2.85. The fractions of separated heavy and light minerals have been used for drawing the two-dimensional graphs. The graphs show that the low gravity stage has a high percentage of heavy minerals collected in the upper area of the table than in the high gravity stage. The results of the experiment can be used for the comparison of regional low gravity and high gravity levels of heavy minerals. If there are any heavy mineral deposits in the high gravity regions, these deposits will take place far away from the coast, within the continental shelf.

Keywords: Anomaly, gravity, influence, mineral.

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Authors: Chen Zhang, Bernhard Schwarz-Röhr, Alexander Härting

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To acquire accurate ship motions at the center of gravity, a single low-cost inertial sensor is utilized and applied on board to measure ship oscillating motions. As observations, the three axes accelerations and three axes rotational rates provided by the sensor are used. The mathematical model of processing the observation data includes determination of the distance vector between the sensor and the center of gravity in x, y, and z directions. After setting up the transfer matrix from sensor’s own coordinate system to the ship’s body frame, an extended Kalman filter is applied to deal with nonlinearities between the ship motion in the body frame and the observation information in the sensor’s frame. As a side effect, the method eliminates sensor noise and other unwanted errors. Results are not only roll and pitch, but also linear motions, in particular heave and surge at the center of gravity. For testing, we resort to measurements recorded on a small vessel in a well-defined sea state. With response amplitude operators computed numerically by a commercial software (Seaway), motion characteristics are estimated. These agree well with the measurements after processing with the suggested method.

Keywords: Extended Kalman filter, nonlinear estimation, sea trial, ship motion estimation.

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Authors: Olga V. Krivobokova

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A major goal of any enterprise is to create a ratings system of customer satisfaction, goods and services. It is obvious that the company cannot change what is not measured. In order to get a clearer picture of the preferences of the major consumer groups, this stage should be based on extensive research, including a variety of interviews and surveys. It is necessary to know the key benefits, which determine customer satisfaction in the market segment, of the properties of certain goods and services. It is important to estimate the terms of these preferences from the viewpoint of the client. This article discusses the importance of customer satisfaction, and ways of assessing it.

Keywords: Costs, customer, evaluation, organization, producer, quality management, satisfaction.

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Authors: May Fadheel Estephan, Richard Perks

Abstract:

Cancer is a serious health concern that affects millions of people worldwide. Early detection and treatment are essential for improving patient outcomes. However, current methods for cancer detection have limitations, such as low sensitivity and specificity. The aim of this study was to develop an optical sensor for cancer detection using elastic light scattering spectroscopy (ELSS). ELSS is a non-invasive optical technique that can be used to characterize the size and concentration of particles in a solution. An optical probe was fabricated with a 100-μm-diameter core and a 132-μm centre-to-centre separation. The probe was used to measure the ELSS spectra of polystyrene spheres with diameters of 2 μm, 0.8 μm, and 0.413 μm. The spectra were then analysed to determine the size and concentration of the spheres. The results showed that the optical probe was able to differentiate between the three different sizes of polystyrene spheres. The probe was also able to detect the presence of polystyrene spheres in suspension concentrations as low as 0.01%. The results of this study demonstrate the potential of ELSS for cancer detection. ELSS is a non-invasive technique that can be used to characterize the size and concentration of cells in a tissue sample. This information can be used to identify cancer cells and assess the stage of the disease. The data for this study were collected by measuring the ELSS spectra of polystyrene spheres with different diameters. The spectra were collected using a spectrometer and a computer. The ELSS spectra were analysed using a software program to determine the size and concentration of the spheres. The software program used a mathematical algorithm to fit the spectra to a theoretical model. The question addressed by this study was whether ELSS could be used to detect cancer cells. The results of the study showed that ELSS could be used to differentiate between different sizes of cells, suggesting that it could be used to detect cancer cells. The findings of this research show the utility of ELSS in the early identification of cancer. ELSS is a non-invasive method for characterizing the number and size of cells in a tissue sample. To determine cancer cells and determine the disease's stage, this information can be employed. Further research is needed to evaluate the clinical performance of ELSS for cancer detection.

Keywords: Elastic Light Scattering Spectroscopy, Polystyrene spheres in suspension, optical probe, fibre optics.

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Authors: Turgay Temel, John Hallam

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A sequential decision problem, based on the task ofidentifying the species of trees given acoustic echo data collectedfrom them, is considered with well-known stochastic classifiers,including single and mixture Gaussian models. Echoes are processedwith a preprocessing stage based on a model of mammalian cochlearfiltering, using a new discrete low-pass filter characteristic. Stoppingtime performance of the sequential decision process is evaluated andcompared. It is observed that the new low pass filter processingresults in faster sequential decisions.

Keywords: Classification, neuro-spike coding, parametricmodel, Gaussian mixture with EM algorithm, sequential decision.

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Authors: S. Anna Durai, E. Anna Saro

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Image Compression using Artificial Neural Networks is a topic where research is being carried out in various directions towards achieving a generalized and economical network. Feedforward Networks using Back propagation Algorithm adopting the method of steepest descent for error minimization is popular and widely adopted and is directly applied to image compression. Various research works are directed towards achieving quick convergence of the network without loss of quality of the restored image. In general the images used for compression are of different types like dark image, high intensity image etc. When these images are compressed using Back-propagation Network, it takes longer time to converge. The reason for this is, the given image may contain a number of distinct gray levels with narrow difference with their neighborhood pixels. If the gray levels of the pixels in an image and their neighbors are mapped in such a way that the difference in the gray levels of the neighbors with the pixel is minimum, then compression ratio as well as the convergence of the network can be improved. To achieve this, a Cumulative distribution function is estimated for the image and it is used to map the image pixels. When the mapped image pixels are used, the Back-propagation Neural Network yields high compression ratio as well as it converges quickly.

Keywords: Back-propagation Neural Network, Cumulative Distribution Function, Correlation, Convergence.

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Authors: Manal Sultan Alhussein, Xiang Michelle Liu

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Telehealth is an advanced technology using digital information and telecommunication facilities that provide access to health services from a distance. It slows the transmission factor of COVID-19, especially for elderly patients and patients with chronic diseases during the pandemic. Therefore, understanding patient perspectives on telehealth services and the factors impacting their option of telehealth service will shed light on the measures that healthcare providers can take to improve the quality of telehealth services. This study aimed to evaluate perceptions of telehealth services among different patient groups and explore various aspects of telehealth utilization in the United States during the COVID-19 pandemic. An online survey distributed via social media platforms was used to collect research data. In addition to the descriptive statistics, both correlation and regression analyses were conducted to test research hypotheses. The empirical results highlighted that the factors such as accessibility to telehealth services and the type of specialty clinics that the patients required play important roles in the effectiveness of telehealth services they received. However, the results found that patients’ waiting time to receive telehealth services and their annual income did not significantly influence their desire to select receiving healthcare services via telehealth. The limitations of the study and future research directions are discussed.

Keywords: Telehealth, patient satisfaction, pandemic, healthcare, remote patient monitor.

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Authors: Han-yuh Liu, Chia-yen Wu

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Truly successful bloggers, navigating the public to know them, often use their blogs as a way to better communicate with customers. Integrating with marketing tools, storytelling can be regarded as one of the most effective ways that businesses can follow to gain competitive edge. Even though the literature on marketing contains much discussion of traditional vehicles, the issue of business blogs applying storytelling has, as yet, received little attention. In the exploration stage, this paper identifies four storytelling disciplines and then presents a road map to business blogging. This paper also provides a two-path framework for blog storytelling and initiates an issue for further study.

Keywords: Storytelling, business blog, blog content, blog position, blog navigation.

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Authors: Tamara Anderson, Neela Badrie

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Consumers are demanding novel beverages that are healthier, convenient and have appealing consumer acceptance. The objectives of this study were to investigate the effects of adding grape polyphenols and the influence of presenting health claims on the sensory acceptability of wines. Fresh red sorrel calyces were fermented into wines. The total soluble solids of the pectinase-treated sorrel puree were from 4°Brix to 23.8°Brix. Polyphenol in the form of grape pomace extract was added to sorrel wines (w/v) in specified levels to give 0. 25. 50 and 75 ppm. A focus group comprising of 12 panelists was use to select the level of polyphenol to be added to sorrel wines for sensory preference The sensory attributed of the wines which were evaluated were colour, clarity, aroma, flavor, mouth-feel, sweetness, astringency and overall preference. The sorrel wine which was most preferred from focus group evaluation was presented for hedonic rating. In the first stage of hedonic testing, the sorrel wine was served chilled at 7°C for 24 h prior to sensory evaluation. Each panelist was provided with a questionnaire and was asked to rate the wines on colour, aroma, flavor, mouth-feel, sweetness, astringency and overall acceptability using a 9-point hedonic scale. In the second stage of hedonic testing, the panelist were instructed to read a health abstract on the health benefits of polyphenolic compounds and again to rate sorrel wine with added 25 ppm polyphenol. Paired t-test was used for the analysis of the influence of presenting health information on polyphenols on hedonic scoring of sorrel wines. Focus groups found that the addition of polyphenol addition had no significant effect on sensory color and aroma but affected clarity and flavor. A 25 ppm wine was liked moderately in overall acceptability. The presentation of information on the health benefit of polyphenols in sorrel wines to panelists had no significant influence on the sensory acceptance of wine. More than half of panelists would drink this wine now and then. This wine had color L 19.86±0.68, chroma 2.10±0.12, hue° 16.90 ±3.10 and alcohol content of 13.0%. The sorrel wine was liked moderately in overall acceptability with the added polyphenols.

Keywords: Sorrel wines, Roselle Hibiscus sabdariffa L, novel wine, polyphenols, health benefits, physicochemical properties.

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Authors: Kadyraliyeva Altynay Mustafayevna, Zholdubayeva Azhar Kuanyshbekovna, Alimzhanova Aliya Sharabekovna, Zhiyenbekova Ainur Abdurakhmanovna, Asanov Seylbek Sadikovich

Abstract:

The article analyses historical aspects of the formation of the Kazakh nation in the conditions of the multicultural society. The authors underline cultural integration as a significant stage of the cultural advancement of the Kazakh nation. The transition to the modern-style houses, the adoption and development of the secular education gave a rise to the development of the society and culture on the whole.

Keywords: Assimilation, culture genesis, cultural integration, multiculturalism

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Authors: Bassma Aldahlan, Zongming Fei

Abstract:

Recently, there is a great interest in smart parking application. Theses applications are enhanced by a vehicular ad-hoc network, which helps drivers find and reserve satiable packing spaces for a period of time ahead of time. Named Data Networking (NDN) is a future Internet architecture that benefits vehicular ad-hoc networks because of its clean-slate design and pure communication model. In this paper, we proposed an NDN-based frame-work for smart parking that involved a fog computing architecture. The proposed application had two main directions: First, we allowed drivers to query the number of parking spaces in a particular parking lot. Second, we introduced a technique that enabled drivers to make intelligent reservations before their arrival time. We also introduced a “push-based” model supporting the NDN-based framework for smart parking applications. To evaluate the proposed solution’s performance, we analyzed the function for finding parking lots with available parking spaces and the function for reserving a parking space. Our system showed high performance results in terms of response time and push overhead. The proposed reservation application performed better than the baseline approach.

Keywords: Cloud Computing, Vehicular Named Data Networking, Smart Parking Applications, Fog Computing.

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Authors: Galeano R. Katherine, Rincon L. David, Luengas. Lely, Guevara. Juan Carlos

Abstract:

The following paper shows an interactive tool which main purpose is to teach how to play a flute. It consists of three stages the first one is the instruction and teaching process through a software application, the second is the practice part when the user starts to play the flute (hardware specially designed for this application) this flute is capable of capturing how is being played the flute and the final stage is the one in which the data captured are sent to the software and the user is evaluated in order to give him / she a correction or an acceptance

Keywords: acoustoelectric devices, computer applications, learning systems, music, technological innovation, virtual reality

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Authors: Diego Ordonez, Carlos Dafonte, Minia Manteiga, Bernardino Arcayy

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This work presents a neural network model for the clustering analysis of data based on Self Organizing Maps (SOM). The model evolves during the training stage towards a hierarchical structure according to the input requirements. The hierarchical structure symbolizes a specialization tool that provides refinements of the classification process. The structure behaves like a single map with different resolutions depending on the region to analyze. The benefits and performance of the algorithm are discussed in application to the Iris dataset, a classical example for pattern recognition.

Keywords: Neural networks, Self-organizing feature maps, Hierarchicalsystems, Pattern clustering methods.

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

Abstract:

2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: Artificial Intelligence, machine learning, deep learning, convolutional neural networks.

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Authors: A. M. Tahsini, S. A. Hosseini

Abstract:

In the present study, the surface temperature history of the adaptor part in a two-stage supersonic launch vehicle is accurately predicted. The full Navier-Stokes equations are used to estimate the aerodynamic heat flux and the one-dimensional heat conduction in solid phase is used to compute the temperature history. The instantaneous surface temperature is used to improve the applied heat flux, to improve the accuracy of the results.

Keywords: Aerodynamic heating, Heat conduction, Numerical simulation, Supersonic flight, Launch vehicle.

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Authors: Zeljko Panian

Abstract:

Web intelligence, if made personal, can fuel the process of building communications around the interests and preferences of each individual customer or prospect, by providing specific behavioral insights about each individual. To become fully efficient, Web intelligence must reach a stage of a high-level maturity, passing throughout a process that involves five steps: (1) Web site analysis; (2) Web site and advertising optimization; (3) Segment targeting; (4) Interactive marketing (online only); and (5) Interactive marketing (online and offline). Discussing these steps in detail, the paper uncovers the real gold mine that is personal-level Web intelligence.

Keywords: Web intelligence, web analytics, informationtechnology (IT), interactive marketing.

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Authors: Asha Hasnimy Mohd Hashim, Lee Ai Choo

Abstract:

We investigated the effects of modified preprogrammed training mode Chase Trainer from Balance Trainer (BT3, HurLab, Tampere, Finland) on athlete who experienced unilateral Patellofemoral Pain Syndrome (PFPS). Twenty-seven athletes with mean age= 14.23 ±1.31 years, height = 164.89 ± 7.85 cm, weight = 56.94 ± 9.28 kg were randomly assigned to two groups: experiment (EG; n = 14) and injured (IG; n = 13). EG performed a series of Chase Trainer program which required them to shift their body weight at different directions, speeds and angle of leaning twice a week for duration of 8 weeks. The static postural control and perceived pain level measures were taken at baseline, after 6 weeks and 8 weeks of training. There was no significant difference in any of tested variables between EG and IG before and after 6-week the intervention period. However, after 8-week of training, the postural control (eyes open) and perceived pain level of EG improved compared to IG (p<0.05). The postural control with eyes closed of EG improved (p<0.05) but the values were not significantly different compared to IG after training. The results suggest that using Chase Trainer exercise program it is possible to improve individual postural control and decreased perceived pain level in athlete with unilateral Patellofemoral Pain Syndrome (PFPS).

Keywords: Patellofemoral Pain Syndrome, perceived pain level, postural control.

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Authors: Rohit Suryawanshi

Abstract:

In this study, the commercial Computational Fluid Dynamics (CFD), ANSYS-Fluent, has been used to optimize the marine propeller with the design of experiment (DOE) method. At the initial stage, different propeller parameters ware selected for the three different levels. The four characteristics factors are: no. of the blade, camber value, pitch delta & chord at the hub. Then, CAD modelling is performed by considering the selected factor and level. In this investigation, a total of 9 test models are simulated with the Reynolds-Averaged Navier-Stokes (RANS) equations. The standard, realizable

Keywords: Marine propeller, Computational Fluid Dynamics, optimization, DOE, propeller thrust.

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Authors: Ahyoung Jeon, Geunchul Park, Jung-Hoon Ro, Gye-rok Geon

Abstract:

Falls are the primary cause of accidents in people over the age of 65, and frequently lead to serious injuries. Since the early detection of falls is an important step to alert and protect the aging population, a variety of research on detecting falls was carried out including the use of accelerators, gyroscopes and tilt sensors. In exiting studies, falls were detected using an accelerometer with errors. In this study, the proposed method for detecting falls was to use two accelerometers to reject wrong falls detection. As falls are accompanied by the acceleration of gravity and rotational motion, the falls in this study were detected by using the z-axial acceleration differences between two sites. The falls were detected by calculating the difference between the analyses of accelerometers placed on two different positions on the chest of the subject. The parameters of the maximum difference of accelerations (diff_Z) and the integration of accelerations in a defined region (Sum_diff_Z) were used to form the fall detection algorithm. The falls and the activities of daily living (ADL) could be distinguished by using the proposed parameters without errors in spite of the impact and the change in the positions of the accelerometers. By comparing each of the axial accelerations, the directions of falls and the condition of the subject afterwards could be determined.In this study, by using two accelerometers without errors attached to two sites to detect falls, the usefulness of the proposed fall detection algorithm parameters, diff_Z and Sum_diff_Z, were confirmed.

Keywords: Tri-axial accelerometer, fall detection.

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Authors: Zhizhong Jiang, Craig Comstock

Abstract:

The past decade has seen enormous growth in the amount of software produced. However, given the ever increasing complexity of the software being developed and the concomitant rise in the typical project size, managers are becoming increasingly aware of the importance of issues that influence the productivity levels of the project teams involved. By analyzing the latest release of ISBSG data repository, we report on the factors found to significantly influence the productivity among which average team size and language type are the two most essential ones. Building on this we present an original model for evaluating the potential productivity during the project planning stage.

Keywords: ISBSG, Linear Model, Productivity, SoftwareEngineering.

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Authors: Sanpachai Huvanandana

Abstract:

A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

Keywords: Human verification, object recognition, videounderstanding, segmentation.

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Authors: Daniel J. O. Ferreira, Juan H. Sosa-Arnao, Bruno C. Moreira, Leonardo P. Rangel, Song W. Park

Abstract:

The comprehensive CFD models have been used to represent and study the heterogeneous combustion of biomass. In the present work, the operation of a global flue gas circuit in the sugarcane bagasse combustion, from wind boxes below primary air grate supply, passing by bagasse insertion in swirl burners and boiler furnace, to boiler bank outlet is simulated. It uses five different meshes representing each part of this system located in sequence: wind boxes and grate, boiler furnace, swirl burners, superheaters and boiler bank. The model considers turbulence using standard k-ε, combustion using EDM, radiation heat transfer using DTM with 16 ray directions and bagasse particle tracking represented by Schiller- Naumann model. The results showed good agreement with expected behavior found in literature and equipment design. The more detailed results view in separated parts of flue gas system allows observing some flow behaviors that cannot be represented by usual simplifications like bagasse supply under homogeneous axial and rotational vectors and others that can be represented using new considerations like the representation of 26 thousand grate orifices by 144 rectangular inlets.

Keywords: Comprehensive CFD model, sugar-cane bagasse combustion, sugar-cane bagasse grate boiler.

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Authors: Verónica Diaz Quezada

Abstract:

This research examines the teaching models used by secondary math teachers when teaching logarithmic, quadratic and exponential functions. For this, descriptive case studies have been carried out on 5 secondary teachers. These teachers have been chosen from 3 scientific-humanistic and technical schools, in Chile. Data have been obtained through non-participant class observation and the application of a questionnaire and a rubric to teachers. According to the results, the didactic model that prevails is the one that starts with an interactive strategy, moves to a more content-based structure, and ends with a reinforcement stage. Nonetheless, there is always influence from teachers, their methods, and the group of students.

Keywords: Teaching models, math teachers, functions, secondary education.

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Authors: Adrienne Kline, Jaydip Desai

Abstract:

Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: Brain-machine interface, EEGLAB, emotiv EEG neuroheadset, openViBE, simulink.

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Authors: Y. Rosli, A. Husna AH, M. Nurhayati

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This research was carried out to determine the possible effects of low electromagnetic field (EMF) exposure to the developing mice fetuses. Pregnant mice were exposed to EMF exposure at 0mT (sham) and 1.2 mT for six hours per session, carried out on gestation day 3, 6, 9, 12 and 15. Samples from the stillborn offspring were observed for morphological defects. The heart didn-t show progressive cellular damage, the lungs were congested and emphysemics. The bones were in advance stage of hypertrophy. Spectrums of morphological defects were observed over 70% of the surviving offspring. These results indicate that even at lower exposure to low EMF, is enough to induce morphological defects in prenatal mice.

Keywords: bone hypertrophy, EMF, low electromagnetic field.

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Authors: D. Sufi Ahmadi, B. Bagheri

Abstract:

Thermal water hammer is a special type of water hammer which rarely occurs in heat exchangers. In biphasic fluids, if steam bubbles are surrounded by condensate, regarding lower condensate temperature than steam, they will suddenly collapse. As a result, the vacuum caused by an extreme change in volume lead to movement of the condensates in all directions and their collision the force produced by this collision leads to a severe stress in the pipe wall. This phenomenon is a special type of water hammer. According to fluid mechanics, this phenomenon is a particular type of transient flows during which abrupt change of fluid leads to sudden pressure change inside the tube. In this paper, the mechanism of abrupt failure of 80 tubes of 481 tubes of a methanol heat exchanger is discussed. Initially, due to excessive temperature differences between heat transfer fluids and simultaneous failure of 80 tubes, thermal shock was presupposed as the reason of failure. Deeper investigation on cross-section of failed tubes showed that failure was, ductile type of failure, so the first hypothesis was rejected. Further analysis and more accurate experiments revealed that failure of tubes caused by thermal water hammer. Finally, the causes of thermal water hammer and various solutions to avoid such mechanism are discussed.

Keywords: Thermal water hammer, Brittle Failure, Condensate thermal shock

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Authors: Tudor Barbu

Abstract:

We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.

Keywords: Text-independent speaker recognition, mel cepstral analysis, speech feature vector, Hausdorff-based metric, supervised classification.

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Authors: Avelino Mondlane, Karin Hansson, Oliver Popov, Xavier Muianga

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This paper discusses the role and importance of Information and Communication Technologies (ICT) and social Networking (SN) in the process of decision making for Flood Risk and Knowledge Management Strategies. We use Mozambique Red Cross (CVM) as the case study and further more we address scenarios for flood risk management strategies, using earlier warning and social networking and we argue that a sustainable desirable stage of life can be achieved by developing scenario strategic planning based on backcasting.

Keywords: ICT, KM, scenario planning, backcasting and flood risk management.

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Authors: Nga-Viet Nguyen, Georgy Shevlyakov, Vladimir Shin

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To solve the problem of multisensor data fusion under non-Gaussian channel noise. The advanced M-estimates are known to be robust solution while trading off some accuracy. In order to improve the estimation accuracy while still maintaining the equivalent robustness, a two-stage robust fusion algorithm is proposed using preliminary rejection of outliers then an optimal linear fusion. The numerical experiments show that the proposed algorithm is equivalent to the M-estimates in the case of uncorrelated local estimates and significantly outperforms the M-estimates when local estimates are correlated.

Keywords: Data fusion, estimation, robustness, M-estimates.

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Authors: Saeedeh Shafiee Nahrkhalaji

Abstract:

Metacognitive knowledge increases EFL students’ ability to be successful learners. Although this relationship has been investigated by a number of scholars, EFL teachers’ explicit awareness of their cognitive knowledge has not been sufficiently explored. The aim of this study was to examine the role of EFL teachers’ metacognitive knowledge in their pedagogical performance. Furthermore, the role played by years of their academic education and teaching experience was also studied. Fifty female EFL teachers were selected. They completed Metacognitive Awareness Inventory (MAI) that assessed six components of metacognition including procedural knowledge, declarative knowledge, conditional knowledge, planning, evaluating, and management strategies. Near the end of the academic semester, the students of each class filled in ‘the Language Teacher Characteristics Questionnaire’ to evaluate their teachers’ pedagogical performance. Four elements of MAI, declarative knowledge, planning, evaluating, and management strategies were found to be significantly correlated with EFL teachers’ pedagogical success. Significant correlation was also established between metacognitive knowledge and EFL teachers’ years of academic education and teaching experience. The findings obtained from this research have contributing implication for EFL teacher educators. The discussion concludes by setting out directions for future research.

Keywords: Metacognotive Knowledge, Pedagogical Performance, Language Teacher Characteristics Questionnaire, Metacognitive Awareness Inventory.

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