Search results for: Industrial ores classification
Commenced in January 2007
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Edition: International
Paper Count: 2146

Search results for: Industrial ores classification

676 Effects of Irradiation to Morphological, Physicochemical and Biocompatibility Properties of Carrageenan

Authors: Jhalique Jane R. Fojas, Rizalinda L. De Leon, Lucille V. Abad

Abstract:

The characterization of κ-carrageenan could provide a better understanding of its functions in biological, medical and industrial applications. Chemical and physical analyses of carrageenan from seaweeds, Euchema cottonii L., were done to offer information on its properties and the effects of Co-60 γ-irradiation on its thermochemical characteristics. The structural and morphological characteristics of κ-carrageenan were determined using scanning electron microscopy (SEM) while the composition, molecular weight and thermal properties were determined using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), gel permeation chromatography (GPC), thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC). Further chemical analysis was done using hydrogen-1 nuclear magnetic resonance (1H NMR) and functional characteristics in terms of biocompatibility were evaluated using cytotoxicity test.

Keywords: Biocompatibility, carrageenan, DSC, FTIR, GPC, irradiation, NMR, physicochemical, SEM, TGA.

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675 A Preliminary Literature Review of Digital Transformation Case Studies

Authors: Vesna Bosilj Vukšić, Lucija Ivančić, Dalia Suša Vugec

Abstract:

While struggling to succeed in today’s complex market environment and provide better customer experience and services, enterprises encompass digital transformation as a means for reaching competitiveness and foster value creation. A digital transformation process consists of information technology implementation projects, as well as organizational factors such as top management support, digital transformation strategy, and organizational changes. However, to the best of our knowledge, there is little evidence about digital transformation endeavors in organizations and how they perceive it – is it only about digital technologies adoption or a true organizational shift is needed? In order to address this issue and as the first step in our research project, a literature review is conducted. The analysis included case study papers from Scopus and Web of Science databases. The following attributes are considered for classification and analysis of papers: time component; country of case origin; case industry and; digital transformation concept comprehension, i.e. focus. Research showed that organizations – public, as well as private ones, are aware of change necessity and employ digital transformation projects. Also, the changes concerning digital transformation affect both manufacturing and service-based industries. Furthermore, we discovered that organizations understand that besides technologies implementation, organizational changes must also be adopted. However, with only 29 relevant papers identified, research positioned digital transformation as an unexplored and emerging phenomenon in information systems research. The scarcity of evidence-based papers calls for further examination of this topic on cases from practice.

Keywords: Digital strategy, digital technologies, digital transformation, literature review.

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674 Computer Countenanced Diagnosis of Skin Nodule Detection and Histogram Augmentation: Extracting System for Skin Cancer

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

Abstract:

Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: Computer-aided system, detection, image segmentation, morphology.

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673 Applications of Support Vector Machines on Smart Phone Systems for Emotional Speech Recognition

Authors: Wernhuar Tarng, Yuan-Yuan Chen, Chien-Lung Li, Kun-Rong Hsie, Mingteh Chen

Abstract:

An emotional speech recognition system for the applications on smart phones was proposed in this study to combine with 3G mobile communications and social networks to provide users and their groups with more interaction and care. This study developed a mechanism using the support vector machines (SVM) to recognize the emotions of speech such as happiness, anger, sadness and normal. The mechanism uses a hierarchical classifier to adjust the weights of acoustic features and divides various parameters into the categories of energy and frequency for training. In this study, 28 commonly used acoustic features including pitch and volume were proposed for training. In addition, a time-frequency parameter obtained by continuous wavelet transforms was also used to identify the accent and intonation in a sentence during the recognition process. The Berlin Database of Emotional Speech was used by dividing the speech into male and female data sets for training. According to the experimental results, the accuracies of male and female test sets were increased by 4.6% and 5.2% respectively after using the time-frequency parameter for classifying happy and angry emotions. For the classification of all emotions, the average accuracy, including male and female data, was 63.5% for the test set and 90.9% for the whole data set.

Keywords: Smart phones, emotional speech recognition, socialnetworks, support vector machines, time-frequency parameter, Mel-scale frequency cepstral coefficients (MFCC).

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672 Determining G-γ Degradation Curve in Cohesive Soils by Dilatometer and in situ Seismic Tests

Authors: Ivandic Kreso, Spiranec Miljenko, Kavur Boris, Strelec Stjepan

Abstract:

This article discusses the possibility of using dilatometer tests (DMT) together with in situ seismic tests (MASW) in order to get the shape of G-g degradation curve in cohesive soils (clay, silty clay, silt, clayey silt and sandy silt). MASW test provides the small soil stiffness (Go from vs) at very small strains and DMT provides the stiffness of the soil at ‘work strains’ (MDMT). At different test locations, dilatometer shear stiffness of the soil has been determined by the theory of elasticity. Dilatometer shear stiffness has been compared with the theoretical G-g degradation curve in order to determine the typical range of shear deformation for different types of cohesive soil. The analysis also includes factors that influence the shape of the degradation curve (G-g) and dilatometer modulus (MDMT), such as the overconsolidation ratio (OCR), plasticity index (IP) and the vertical effective stress in the soil (svo'). Parametric study in this article defines the range of shear strain gDMT and GDMT/Go relation depending on the classification of a cohesive soil (clay, silty clay, clayey silt, silt and sandy silt), function of density (loose, medium dense and dense) and the stiffness of the soil (soft, medium hard and hard). The article illustrates the potential of using MASW and DMT to obtain G-g degradation curve in cohesive soils.

Keywords: Dilatometer testing, MASW testing, shear wave, soil stiffness, stiffness reduction, shear strain.

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671 Dynamic Threshold Adjustment Approach For Neural Networks

Authors: Hamza A. Ali, Waleed A. J. Rasheed

Abstract:

The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.

Keywords: Classification, Recognition, Neural Networks, Pattern Recognition, Generalization.

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670 The Gasification of Acetone via Partial Oxidation in Supercritical Water

Authors: Shyh-Ming Chern, Kai-Ting Hsieh

Abstract:

Organic solvents find various applications in many industrial sectors and laboratories as dilution solvents, dispersion solvents, cleaners and even lubricants. Millions of tons of spent organic solvents (SOS) are generated each year worldwide, prompting the need for more efficient, cleaner and safer methods for the treatment and resource recovery of SOS. As a result, acetone, selected as a model compound for SOS, was gasified in supercritical water to assess the feasibility of resource recovery of SOS by means of supercritical water processes. Experiments were conducted with an autoclave reactor. Gaseous product is mainly consists of H2, CO, CO2 and CH4. The effects of three major operating parameters, the reaction temperature, from 673 to 773K, the dosage of oxidizing agent, from 0.3 to 0.5 stoichiometric oxygen, and the concentration of acetone in the feed, 0.1 and 0.2M, on the product gas composition, yield and heating value were evaluated with the water density fixed at about 0.188g/ml.

Keywords: Acetone, gasification, SCW, supercritical water.

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669 Ecotoxicological Studies of Soil Using Analytical and Biological Methods: A Review

Authors: V. Chahal, A. Nagpal, Y. B. Pakade, J. K. Katnoria

Abstract:

Soil is a complex physical and biological system that provides support, water, nutrients and oxygen to the plants. Apart from these, it acts as a connecting link between inorganic, organic and living components of the ecosystem. In recent years, presence of xenobiotics, alterations in the natural soil environment, application of pesticides/inorganic fertilizers, percolation of contaminated surface water as well as leachates from landfills to subsurface strata and direct discharge of industrial wastes to the land have resulted in soil pollution which in turn has posed severe threats to human health especially in terms of causing carcinogenicity by direct DNA damage. The present review is an attempt to summarize literature on sources of soil pollution, characterization of pollutants and their consequences in different living systems.

Keywords: Soil Pollution, Contaminants, Heavy metals, Pesticides, Bioassays.

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668 DC Link Floating for Grid Connected PV Converters

Authors: Attila Balogh, Eszter Varga, István Varjasi

Abstract:

Nowadays there are several grid connected converter in the grid system. These grid connected converters are generally the converters of renewable energy sources, industrial four quadrant drives and other converters with DC link. These converters are connected to the grid through a three phase bridge. The standards prescribe the maximal harmonic emission which could be easily limited with high switching frequency. The increased switching losses can be reduced to the half with the utilization of the wellknown Flat-top modulation. The suggested control method is the expansion of the Flat-top modulation with which the losses could be also reduced to the half compared to the Flat-top modulation. Comparing to traditional control these requirements can be simultaneously satisfied much better with the DLF (DC Link Floating) method.

Keywords: DC link floating, high efficiency, PV converter, control method.

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667 Modeling and Simulation of Ship Structures Using Finite Element Method

Authors: Javid Iqbal, Zhu Shifan

Abstract:

The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: Dynamic analysis, finite element methods, ship structure, vibration analysis.

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666 Applying Case-Based Reasoning in Supporting Strategy Decisions

Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

Abstract:

Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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665 A Supervisory Scheme for Step-Wise Safe Switching Controllers

Authors: Fotis N. Koumboulis, Maria P. Tzamtzi

Abstract:

A supervisory scheme is proposed that implements Stepwise Safe Switching Logic. The functionality of the supervisory scheme is organized in the following eight functional units: Step- Wise Safe Switching unit, Common controllers design unit, Experimentation unit, Simulation unit, Identification unit, Trajectory cruise unit, Operating points unit and Expert system unit. The supervisory scheme orchestrates both the off-line preparative actions, as well as the on-line actions that implement the Stepwise Safe Switching Logic. The proposed scheme is a generic tool, that may be easily applied for a variety of industrial control processes and may be implemented as an automation software system, with the use of a high level programming environment, like Matlab.

Keywords: Supervisory systems, safe switching, nonlinear systems.

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664 Formant Tracking Linear Prediction Model using HMMs for Noisy Speech Processing

Authors: Zaineb Ben Messaoud, Dorra Gargouri, Saida Zribi, Ahmed Ben Hamida

Abstract:

This paper presents a formant-tracking linear prediction (FTLP) model for speech processing in noise. The main focus of this work is the detection of formant trajectory based on Hidden Markov Models (HMM), for improved formant estimation in noise. The approach proposed in this paper provides a systematic framework for modelling and utilization of a time- sequence of peaks which satisfies continuity constraints on parameter; the within peaks are modelled by the LP parameters. The formant tracking LP model estimation is composed of three stages: (1) a pre-cleaning multi-band spectral subtraction stage to reduce the effect of residue noise on formants (2) estimation stage where an initial estimate of the LP model of speech for each frame is obtained (3) a formant classification using probability models of formants and Viterbi-decoders. The evaluation results for the estimation of the formant tracking LP model tested in Gaussian white noise background, demonstrate that the proposed combination of the initial noise reduction stage with formant tracking and LPC variable order analysis, results in a significant reduction in errors and distortions. The performance was evaluated with noisy natual vowels extracted from international french and English vocabulary speech signals at SNR value of 10dB. In each case, the estimated formants are compared to reference formants.

Keywords: Formants Estimation, HMM, Multi Band Spectral Subtraction, Variable order LPC coding, White Gauusien Noise.

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663 The Experimental and Numerical Analysis of a Lightpipe using a Simulation Software

Authors: M. Paroncini, F. Corvaro, G. Nardini, S. Pistolesi

Abstract:

A lightpipe is an about 99 percent specular reflective mirror pipe or duct that is used for the transmission of the daylight from the outside into a building. The lightpipes are usually used in the daylighting buildings, in the residential, industrial and commercial sectors. This paper is about the performances of a lightpipe installed in a laboratory (3 m x 2.6 m x 3 m) without windows. The aim is to analyse the luminous intensity distribution for several sky/sun conditions. The lightpipe was monitored during the year 2006. The lightpipe is 1 m long and the diameter of the top collector and of the internal diffuser device is 0.25 m. In the laboratory there are seven illuminance sensors: one external is located on the roof of the laboratory and six internal sensors are connected to a data acquisition system. The internal sensors are positioned under the internal diffusive device at an height of 0.85 m from the floor to simulate a working plane. The numerical data are obtained through a simulation software. This paper shows the comparison between the experimental and numerical results concerning the behavior of the lightpipe.

Keywords: Daylighting, Desktop Radiance, Lightpipe.

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662 A Communication Signal Recognition Algorithm Based on Holder Coefficient Characteristics

Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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661 Design and Optimization of Coplanar Waveguide-Fed Sensing Antennas for ISM Band Applications

Authors: Vivek Bharti, Inderpreet Kaur, Saurabh Verma, Renu Gangwar, Hari Kumar Singh

Abstract:

This work presents a dual-band Coplanar Waveguide (CPW) fed rectangular patch antenna designed for applications in Industrial, Scientific, and Medical (ISM) Band sensing. Fabricated on a cost-effective FR-4 substrate with specific dimensions, the antenna incorporates a rectangular slot and a copper patch, optimized through simulation to achieve desired characteristics, particularly focusing on the reflection coefficient. A unique feature is introduced through the integration of copper cells forming a Partially Reflecting Surface (PRS) to feed the antenna. Dual-band functionality is achieved, covering frequencies of 1.28 GHz-1.3 GHz and 4.9 GHz-5.2 GHz, catering to diverse communication needs within these frequency ranges. The addition of a superstrate enhances the antenna’s gain, resulting in 4.5 dBi at 1.28 GHz-1.3 GHz and 6.5 dBi at 4.9 GHz-5.2 GHz, with an efficiency of 58%.

Keywords: ISM, Coplanar waveguide fed, superstrate, circularly polarized.

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660 Solar Tracking System Using a Refrigerant as Working Medium for Solar Energy Conversion

Authors: S. Sendhil Kumar, S. N. Vijayan

Abstract:

Utilization of solar energy can be found in various domestic and industrial applications. The performance of any solar collector is largely affected by various parameters such as glazing, absorber plate, top covers, and heating pipes. Technology improvements have brought us another method for conversion of solar energy to direct electricity using solar photovoltaic system. Utilization and extraction of solar energy is the biggest problem in these conversion methods. This paper aims to overcome these problems and take the advantages of available energy from solar by maximizing the utilization through solar tracking system using a refrigerant as a working medium. The use of this tracking system can help increase the efficiency of conversion devices by maximum utilization of solar energy. The dual axis tracking system gives maximum energy output compared to single axis tracking system.

Keywords: Refrigerant, solar collector, solar energy, solar panel, solar tracking.

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659 Forest Risk and Vulnerability Assessment: A Case Study from East Bokaro Coal Mining Area in India

Authors: Sujata Upgupta, Prasoon Kumar Singh

Abstract:

The expansion of large scale coal mining into forest areas is a potential hazard for the local biodiversity and wildlife. The objective of this study is to provide a picture of the threat that coal mining poses to the forests of the East Bokaro landscape. The vulnerable forest areas at risk have been assessed and the priority areas for conservation have been presented. The forested areas at risk in the current scenario have been assessed and compared with the past conditions using classification and buffer based overlay approach. Forest vulnerability has been assessed using an analytical framework based on systematic indicators and composite vulnerability index values. The results indicate that more than 4 km2 of forests have been lost from 1973 to 2016. Large patches of forests have been diverted for coal mining projects. Forests in the northern part of the coal field within 1-3 km radius around the coal mines are at immediate risk. The original contiguous forests have been converted into fragmented and degraded forest patches. Most of the collieries are located within or very close to the forests thus threatening the biodiversity and hydrology of the surrounding regions. Based on the vulnerability values estimated, it was concluded that more than 90% of the forested grids in East Bokaro are highly vulnerable to mining. The forests in the sub-districts of Bermo and Chandrapura have been identified as the most vulnerable to coal mining activities. This case study would add to the capacity of the forest managers and mine managers to address the risk and vulnerability of forests at a small landscape level in order to achieve sustainable development.

Keywords: Coal mining, forest, indicators, vulnerability.

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658 Virtual Mechanical Engineering Education – A Case Study

Authors: S. H. R. Lo

Abstract:

Virtual engineering technology has undergone rapid progress in recent years and is being adopted increasingly by manufacturing companies of many engineering disciplines. There is an increasing demand from industry for qualified virtual engineers. The qualified virtual engineers should have the ability of applying engineering principles and mechanical design methods within the commercial software package environment. It is a challenge to the engineering education in universities which traditionally tends to lack the integration of knowledge and skills required for solving real world problems. In this paper, a case study shows some recent development of a MSc Mechanical Engineering course at Department of Engineering and Technology in MMU, and in particular, two units Simulation of Mechanical Systems(SMS) and Computer Aided Fatigue Analysis(CAFA) that emphasize virtual engineering education and promote integration of knowledge acquisition, skill training and industrial application.

Keywords: Computational modelling and simulation, mechanical engineering education.

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657 The Effects of TiO2 Nanoparticles on Tumor Cell Colonies: Fractal Dimension and Morphological Properties

Authors: T. Sungkaworn, W. Triampo, P. Nalakarn, D. Triampo, I. M. Tang, Y. Lenbury, P. Picha

Abstract:

Semiconductor nanomaterials like TiO2 nanoparticles (TiO2-NPs) approximately less than 100 nm in diameter have become a new generation of advanced materials due to their novel and interesting optical, dielectric, and photo-catalytic properties. With the increasing use of NPs in commerce, to date few studies have investigated the toxicological and environmental effects of NPs. Motivated by the importance of TiO2-NPs that may contribute to the cancer research field especially from the treatment prospective together with the fractal analysis technique, we have investigated the effect of TiO2-NPs on colony morphology in the dark condition using fractal dimension as a key morphological characterization parameter. The aim of this work is mainly to investigate the cytotoxic effects of TiO2-NPs in the dark on the growth of human cervical carcinoma (HeLa) cell colonies from morphological aspect. The in vitro studies were carried out together with the image processing technique and fractal analysis. It was found that, these colonies were abnormal in shape and size. Moreover, the size of the control colonies appeared to be larger than those of the treated group. The mean Df +/- SEM of the colonies in untreated cultures was 1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs was 1.287±0.045. It was found that the circularity of the control group (0.401±0.071) is higher than that of the treated group (0.103±0.042). The same tendency was found in the diameter parameters which are 1161.30±219.56 μm and 852.28±206.50 μm for the control and treated group respectively. Possible explanation of the results was discussed, though more works need to be done in terms of the for mechanism aspects. Finally, our results indicate that fractal dimension can serve as a useful feature, by itself or in conjunction with other shape features, in the classification of cancer colonies.

Keywords: Tumor growth, Cell colonies, TiO2, Nanoparticles, Fractal, Morphology, Aggregation.

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656 Diagnosis of Intermittent High Vibration Peaks in Industrial Gas Turbine Using Advanced Vibrations Analysis

Authors: Abubakar Rashid, Muhammad Saad, Faheem Ahmed

Abstract:

This paper provides a comprehensive study pertaining to diagnosis of intermittent high vibrations on an industrial gas turbine using detailed vibrations analysis, followed by its rectification. Engro Polymer & Chemicals Limited, a Chlor-Vinyl complex located in Pakistan has a captive combined cycle power plant having two 28 MW gas turbines (make Hitachi) & one 15 MW steam turbine. In 2018, the organization faced an issue of high vibrations on one of the gas turbines. These high vibration peaks appeared intermittently on both compressor’s drive end (DE) & turbine’s non-drive end (NDE) bearing. The amplitude of high vibration peaks was between 150-170% on the DE bearing & 200-300% on the NDE bearing from baseline values. In one of these episodes, the gas turbine got tripped on “High Vibrations Trip” logic actuated at 155µm. Limited instrumentation is available on the machine, which is monitored with GE Bently Nevada 3300 system having two proximity probes installed at Turbine NDE, Compressor DE &at Generator DE & NDE bearings. Machine’s transient ramp-up & steady state data was collected using ADRE SXP & DSPI 408. Since only 01 key phasor is installed at Turbine high speed shaft, a derived drive key phasor was configured in ADRE to obtain low speed shaft rpm required for data analysis. By analyzing the Bode plots, Shaft center line plot, Polar plot & orbit plots; rubbing was evident on Turbine’s NDE along with increased bearing clearance of Turbine’s NDE radial bearing. The subject bearing was then inspected & heavy deposition of carbonized coke was found on the labyrinth seals of bearing housing with clear rubbing marks on shaft & housing covering at 20-25 degrees on the inner radius of labyrinth seals. The collected coke sample was tested in laboratory & found to be the residue of lube oil in the bearing housing. After detailed inspection & cleaning of shaft journal area & bearing housing, new radial bearing was installed. Before assembling the bearing housing, cleaning of bearing cooling & sealing air lines was also carried out as inadequate flow of cooling & sealing air can accelerate coke formation in bearing housing. The machine was then taken back online & data was collected again using ADRE SXP & DSPI 408 for health analysis. The vibrations were found in acceptable zone as per ISO standard 7919-3 while all other parameters were also within vendor defined range. As a learning from subject case, revised operating & maintenance regime has also been proposed to enhance machine’s reliability.

Keywords: ADRE, bearing, gas turbine, GE Bently Nevada, Hitachi, vibration.

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655 Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach

Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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654 SWOT Analysis of Cassava Sector in Cameroon

Authors: Elise Stephanie Mvodo Meyo, Dapeng Liang

Abstract:

Cassava is one of the top five crops in Cameroon. Its evolution has remained constant since the independence period and the production has more than tripled. It is a crop with multiple industrial capacities but the sector-s business opportunities are underexploited. Using Strengths, Weaknesses, Opportunities and Threats analysis method, this paper examines the cassava actual state. It appraises the sector-s strengths (S), considers suitable measures to strengthen weaknesses (W), evaluates strategies to fully benefit from the sector numerous business opportunities (O) and explore means to convert threats (T) into opportunities. Data were collected from the ministry of agriculture and rural development and different actors. The results show that cassava sector embodies many business opportunities and stands as a raw material provider for many industries but ultimately requires challenges to be tackled appropriately.

Keywords: Business opportunities, cassava sector, rural development, SWOT analysis.

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653 New Echocardiographic Morphofunctional Diastolic Index (MFDI) in Differentiation of Normal Left Ventricular Filling from Pseudonormal and Restrictive

Authors: N. Nelasov, D. Safonov, M. Babaev, E. Mirzojan, O. Eroshenko, M. Morgunov, A. Erofeeva

Abstract:

We have shown previously that reflected high intensity motion signals (RIMS) can be used for detection of left ventricular (LV) diastolic dysfunction (DD). It is also well known, that left atrial (LA) dimension can be used as a marker of DD. In this study we decided to analyze the diagnostic role of new echocardiographic morphofunctional diastolic index (MFDI) in differentiation of normal filling of LV from pseudonormal and restrictive. MFDI includes LA dimension and velocity of early diastolic component ea of RIMS (MFDI = LA/ea).  

343 healthy subjects and patients with various cardiac pathology underwent dopplerechocardiographic exam. According to the criteria of "Don" classification scheme 155 subjects had signs of normal LV filling (N) and 55 - of pseudonormal and restrictive filling (PN + R). LA dimension was performed in standard manner. RIMS were registered by conventional pulsed wave Doppler from apical 4-chamber view, when the sample volume was positioned between the tips of mitral leaflets. The velocity of early diastolic component of RIMS was measured. After calculation of MFDI mean values of this index in two groups (N and PN + R) were compared. The cutoff value of MFDI for differentiation of patients with N and PN + R was determined.

Mean value of MFDI in subjects with normal filling was 1.38+0.33 and in patients with pseudonormal and restrictive filling 2.43+0.43; p<0.0001. The cutoff value of MFDI > 2.0 separated subjects with normal LV filling from subjects with pseudonormal and restrictive filling with sensitivity 89.1% and specificity 97.4%.

Keywords: Dopplerechocardiography, diastolic dysfunction, left atrium, reflected high intensity motion signals.

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652 A New Microstrip Diplexer Using Coupled Stepped Impedance Resonators

Authors: A. Chinig, J. Zbitou, A. Errkik, L. Elabdellaoui, A. Tajmouati, A. Tribak, M. Latrach

Abstract:

This paper presents a new structure of microstrip band pass filter (BPF) based on coupled stepped impedance resonators. Each filter consists of two coupled stepped impedance resonators connected to microstrip feed lines. The coupled junction is utilized to connect the two BPFs to the antenna. This two band pass filters are designed and simulated to operate for the digital communication system (DCS) and Industrial Scientific and Medical (ISM) bands at 1.8 GHz and 2.45 GHz respectively. The proposed circuit presents good performances with an insertion loss lower than 2.3 dB and isolation between the two channels greater than 21 dB. The prototype of the optimized diplexer have been investigated numerically by using ADS Agilent and verified with CST microwave software.

Keywords: Band Pass Filter, coupled junction, coupled stepped impedance resonators, diplexer, insertion loss, isolation.

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651 Design and Analysis of an Electro Thermally Symmetrical Actuated Microgripper

Authors: Sh. Foroughi, V. Karamzadeh, M. Packirisamy

Abstract:

This paper presents design and analysis of an electrothermally symmetrical actuated microgripper applicable for performing micro assembly or biological cell manipulation. Integration of micro-optics with microdevice leads to achieve extremely precise control over the operation of the device. Geometry, material, actuation, control, accuracy in measurement and temperature distribution are important factors which have to be taken into account for designing the efficient microgripper device. In this work, analyses of four different geometries are performed by means of COMSOL Multiphysics 5.2 with implementing Finite Element Methods. Then, temperature distribution along the fingertip, displacement of gripper site as well as optical efficiency vs. displacement and electrical potential are illustrated. Results show in addition to the industrial application of this device, the usage of that as a cell manipulator is possible.

Keywords: Electro thermal actuator, MEMS, Microgripper, MOEMS.

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650 Ethnocentrism: The Hidden Adversary of Effective Global Leadership

Authors: Ruxandra A. Vodă

Abstract:

With the industrial revolution, global leaders must more rapidly become knowledgeable of and develop essential cross-cultural competencies to be effective. Ethnocentrism represents a hidden barrier of effective leadership and must be acknowledged and addressed proactively by global leaders. The article examines the impact of ethnocentrism in four critical areas (leadership strategy, cross-cultural competencies, intercultural communication, and adaptation to international contexts) and argues that by developing cross-cultural competencies, leaders might naturally reduce ethnocentrism levels. This paper will also offer few examples to support international managers in understanding how ethnocentrism can affect performance.

Keywords: Adaptation to intercultural contexts, cross-cultural competencies, effective leadership, ethnocentrism, global leader, intercultural communication, leadership strategy, the GLOBE Project.

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649 An Overview of Evaluations Using Augmented Reality for Assembly Training Tasks

Authors: S. Werrlich, E. Eichstetter, K. Nitsche, G. Notni

Abstract:

Augmented Reality (AR) is a strong growing research topic in different training domains such as medicine, sports, military, education and industrial use cases like assembly and maintenance tasks. AR claims to improve the efficiency and skill-transfer of training tasks. This paper gives a comprehensive overview of evaluations using AR for assembly and maintenance training tasks published between 1992 and 2017. We search in a structured way in four different online databases and get 862 results. We select 17 relevant articles focusing on evaluating AR-based training applications for assembly and maintenance tasks. This paper also indicates design guidelines which are necessary for creating a successful application for an AR-based training. We also present five scientific limitations in the field of AR-based training for assembly tasks. Finally, we show our approach to solve current research problems using Design Science Research (DSR).

Keywords: Assembly, augmented reality, survey, training.

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648 Air Flows along Perforated Metal Plates with the Heat Transfer

Authors: K. Fraňa, S. Simon

Abstract:

The objective of the paper is a numerical study of heat transfer between perforated metal plates and the surrounding air flows. Different perforation structures can nowadays be found in various industrial products. Besides improving the mechanical properties, the perforations can intensify the heat transfer as well. The heat transfer coefficient depends on a wide range of parameters such as type of perforation, size, shape, flow properties of the surrounding air etc. The paper was focused on three different perforation structures which have been investigated from the point of the view of the production in the previous studies. To determine the heat coefficients and the Nusselt numbers, the numerical simulation approach was adopted. The calculations were performed using the OpenFOAM software. The three-dimensional, unstable, turbulent and incompressible air flow around the perforated surface metal plate was considered.

Keywords: Perforations, convective heat transfers, turbulent flows, numerical simulations.

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647 An Investigation into the Application of Artificial Neural Networks to the Prediction of Injuries in Sport

Authors: J. McCullagh, T. Whitfort

Abstract:

Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.

Keywords: Artificial Neural Networks, data, injuries, sport

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