Search results for: Multi-objective decision making techniques

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

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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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Authors: Rumman Md Raihanuzzaman, Lee Chang Chuan, Zonghan Xie, Reza Ghomashchi

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Cemented carbides, owing to their excellent mechanical properties, have been of immense interest in the field of hard materials for the past few decades. A number of processing techniques have been developed to obtain high quality carbide tools, with a wide range of grain size depending on the application and requirements. Microwave sintering is one of the heating processes, which has been used to prepare a wide range of materials including ceramics. A deep understanding of microwave sintering and its contribution towards control of grain growth and on deformation of the resulting carbide materials requires further studies and attention. In addition, the effect of binder materials and their behavior during microwave sintering is another area that requires clear understanding. This review aims to focus on microwave sintering, providing information of how the process works and what type of materials it is best suited for. In addition, a closer look at some microwave sintered Tungsten Carbide-Cobalt samples will be taken and discussed, highlighting some of the key issues and challenges faced in this research area.

Keywords: Cemented carbides, consolidation, microwave sintering, mechanical properties.

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Authors: S. Sendhilkumar, N. Mohanasundaram, M. Senthilkumar, S. N. Sivanandam

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The operational life of rotating machines has to be extended using a predictive condition maintenance tool. Among various condition monitoring techniques, vibration analysis is most widely used technique in industry. Signals are extracted for evaluating the condition of machine; further diagnostics is carried out with detected signals to extend the life of machine. With help of detected signals, further interpretations are done to predict the occurrence of defects. To study the problem of defects, a test rig with various possibilities of defects is constructed and experiments are performed considering the unbalanced condition. Further, this paper presents an approach for fault diagnosis of unbalance condition using Elman neural network and frequency-domain vibration analysis. Amplitudes with variation in acceleration are fed to Elman neural network to classify fault or no-fault condition. The Elman network is trained, validated and tested with experimental readings. Results illustrate the effectiveness of Elman network in rotor-bearing system.

Keywords: Elman neural network, fault detection, rotating machines, unbalance, vibration analysis.

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Authors: Othman Belgassim, Krzysztof Jemielniak

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The analysis of Acoustic Emission (AE) signal generated from metal cutting processes has often approached statistically. This is due to the stochastic nature of the emission signal as a result of factors effecting the signal from its generation through transmission and sensing. Different techniques are applied in this manner, each of which is suitable for certain processes. In metal cutting where the emission generated by the deformation process is rather continuous, an appropriate method for analysing the AE signal based on the root mean square (RMS) of the signal is often used and is suitable for use with the conventional signal processing systems. The aim of this paper is to set a strategy in tool failure detection in turning processes via the statistic analysis of the AE generated from the cutting zone. The strategy is based on the investigation of the distribution moments of the AE signal at predetermined sampling. The skews and kurtosis of these distributions are the key elements in the detection. A normal (Gaussian) distribution has first been suggested then this was eliminated due to insufficiency. The so called Beta distribution was then considered, this has been used with an assumed β density function and has given promising results with regard to chipping and tool breakage detection.

Keywords: AE signal, skew, kurtosis, tool failure

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Authors: Mandla T. Nene, Edgar.Jembere, Matthew O. Adigun, Themba Shezi, Siyabonga S. Cebekhulu

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The drastic increase in the usage of SMS technology has led service providers to seek for a solution that enable users of mobile devices to access services through SMSs. This has resulted in the proposal of solutions towards SMS-based service invocation in service oriented environments. However, the dynamic nature of service-oriented environments coupled with sudden load peaks generated by service request, poses performance challenges to infrastructures for supporting SMS-based service invocation. To address this problem we adopt load balancing techniques. A load balancing model with adaptive load balancing and load monitoring mechanisms as its key constructs is proposed. The load balancing model then led to realization of Least Loaded Load Balancing Framework (LLLBF). Evaluation of LLLBF benchmarked with round robin (RR) scheme on the queuing approach showed LLLBF outperformed RR in terms of response time and throughput. However, LLLBF achieved better result in the cost of high processing power.

Keywords: SMS (Short Message Service), LLLBF (Least Loaded Load Balancing Framework), Service Oriented Computing (SOC).

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Authors: Amoljit S. Gill, Sanjeev Kumar

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In this study, Electrical Discharge Machining (EDM) is used to modify the surface of high carbon steel En31 with the help of tool electrode (Copper-Chromium-Nickel) manufactured by powder metallurgy (PM) process. The effect of EDM on surface roughness during surface alloying is studied. Taguchi’s Design of experiment (DOE) and L18 orthogonal array is used to find the best level of input parameters in order to achieve high surface finish. Six input parameters are considered and their percentage contribution towards surface roughness is investigated by analysis of variances (ANOVA). Experimental results show that an hard alloyed surface (1.21% carbon, 2.14% chromium and 1.38% nickel) with surface roughness of 3.19µm can be generated using EDM with PM tool. Additionally, techniques like Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS) are used to analyze the machined surface and EDMed layer composition, respectively. The increase in machined surface micro-hardness (101%) may be related to the formation of carbides containing chromium.

Keywords: Electrical Discharge Machining, Surface Roughness, Powder metallurgy compact tools, Taguchi DOE technique.

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Authors: Francisca Grimón, Marylin Giugni, Josep Monguet F., Joaquín Fernández, Luis León G.

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In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.

Keywords: Blended Learning, System Adaptive, Model, Clustering Algorithms.

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Authors: Chit Su Htwe, Win Htay

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The iris recognition technology is the most accurate, fast and less invasive one compared to other biometric techniques using for example fingerprints, face, retina, hand geometry, voice or signature patterns. The system developed in this study has the potential to play a key role in areas of high-risk security and can enable organizations with means allowing only to the authorized personnel a fast and secure way to gain access to such areas. The paper aim is to perform the iris region detection and iris inner and outer boundaries localization. The system was implemented on windows platform using Visual C# programming language. It is easy and efficient tool for image processing to get great performance accuracy. In particular, the system includes two main parts. The first is to preprocess the iris images by using Canny edge detection methods, segments the iris region from the rest of the image and determine the location of the iris boundaries by applying Hough transform. The proposed system tested on 756 iris images from 60 eyes of CASIA iris database images.

Keywords: Canny, C#, hough transform, image preprocessing.

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

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

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

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Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: Bridge Management Systems (BMS), cost optimization condition assessment, fund allocation, Markov chain.

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Authors: Federico Pérez González, Iñaki Goirizelaia Ordorika, Pedro Iriondo Bengoa

Abstract:

In this work a new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuous-tone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different importance levels from which the bit stream will be generated. The subcomponents of each importance level are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several improvement levels.

Keywords: Image compression, wavelet transform, highly scalable, reversible transform, embedded, subcomponents.

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Authors: A. Abou El-Azm Aly, F. Nicolleau, T. M. Michelitsch, A. F. Nowakowski

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In this study, the dispersion of heavy particles line in an isotropic and incompressible three-dimensional turbulent flow has been studied using the Kinematic Simulation techniques to find out the evolution of the line fractal dimension. The fractal dimension of the line is found in the case of different particle gravity (in practice, different values of particle drift velocity) in the presence of small particle inertia with a comparison with that obtained in the diffusion case of material line at the same Reynolds number. It can be concluded for the dispersion of heavy particles line in turbulent flow that the particle gravity affect the fractal dimension of the line for different particle gravity velocities in the range 0.2 < W < 2. With the increase of the particle drift velocity, the fractal dimension of the line decreases which may be explained as the particles pass many scales in their journey in the direction of the gravity and the particles trajectories do not affect by these scales at high particle drift velocities.

Keywords: Heavy particles, two-phase flow, Kinematic Simulation, Fractal dimension.

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Authors: T. C. Manjunath, B. Bandyopadhyay

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This paper deals with the design of a periodic output feedback controller for a flexible beam structure modeled with Timoshenko beam theory, Finite Element Method, State space methods and embedded piezoelectrics concept. The first 3 modes are considered in modeling the beam. The main objective of this work is to control the vibrations of the beam when subjected to an external force. Shear piezoelectric sensors and actuators are embedded into the top and bottom layers of a flexible aluminum beam structure, thus making it intelligent and self-adaptive. The composite beam is divided into 5 finite elements and the control actuator is placed at finite element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. 4 state space SISO models are thus developed. Periodic Output Feedback (POF) Controllers are designed for the 4 SISO models of the same plant to control the flexural vibrations. The effect of placing the sensor at different locations on the beam is observed and the performance of the controller is evaluated for vibration control. Conclusions are finally drawn.

Keywords: Smart structure, Timoshenko beam theory, Periodic output feedback control, Finite Element Method, State space model, SISO, Embedded sensors and actuators, Vibration control.

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Authors: S. Krustev, V. Angelova, P. Zaprjanova

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Selenium (Se) is an essential micro-nutrient for human and animals but it is highly toxic. Its organic compounds play an important role in biochemistry and nutrition of the cells. Concentration levels of this element in the different regions of the world vary considerably. This study aimed to compare the availability and levels of the Se in some rural areas of the Balkan Peninsula and relationship with the concentrations of other trace elements. For this purpose soil samples and wheat grains from different regions of Bulgaria, Serbia, Nord Macedonia, Romania, and Greece situated far from large industrial centers have been analyzed. The main methods for their determination were the atomic spectral techniques – atomic absorption and plasma atomic emission. As a result of this study, data on microelements levels from the main grain-producing regions of the Balkan Peninsula were determined and systematized. The presented results confirm the low levels of Se in this region: 0.222– 0.962 mg.kg^-1 in soils and 0.001 - 0.005 mg.kg^-1 in wheat grains and require measures to offset the effect of this deficiency.

Keywords: Agricultural soils, Balkan Peninsula, rural areas, selenium.

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Authors: Rachel Bardy Prado, Vinícius de Melo Benites, José Carlos Polidoro, Carlos Eduardo Gonçalves, Alexey Naumov

Abstract:

Most agricultural crops cultivated in Brazil are highly nutrient demanding. Brazilian soils are generally acidic with low base saturation and available nutrients. Demand for fertilizer application has increased because the national agricultural sector expansion. To improve productivity without environmental impact, there is the need for the utilization of novel procedures and techniques to optimize fertilizer application. This includes the digital soil mapping and GIS application applied to mapping in different scales. This paper is based on research, realized during 2005 to 2010 by Brazilian Corporation for Agricultural Research (EMBRAPA) and its partners. The purpose was to map soil fertility in national and regional scales. A soil profile data set in national scale (1:5,000,000) was constructed from the soil archives of Embrapa Soils, Rio de Janeiro and in the regional scale (1:250,000) from COMIGO Cooperative soil data set, Rio Verde, Brazil. The mapping was doing using ArcGIS 9.1 tools from ESRI.

Keywords: agricultural sustainability, fertilizer optimization, GIS, soil attributes.

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Authors: Jing Yu Pan, Dahai Liu

Abstract:

Airlines in the US have taken protective measures to battle the COVID-19 pandemic, with a mask mandate being the most important one, especially in the aircraft cabin. As the airline industry is recovering from the pandemic, mask-wearing will eventually become a personal choice during a flight. Nevertheless, COVID-19 will continue to create uncertainty for a long time into the future, making it necessary to understand the attitude and voluntary use of masks by air travelers on airplanes even after masks are no longer mandatory. This study aimed to understand the relationship between demographic characteristics and mask-wearing intention in the US. For age, gender, income, educational, and ethnicity groups, this study examined three factors – subjective norms, risk avoidance, and information seeking and their influence on the mask-wearing intention onboard airplanes during COVID-19, and whether or not attitude toward masks was an important mediator. The results show that all demographic factors except gender could help to explain the group variations in factor impact and the mediating effect in mask-wearing intentions. In particular, Asian travelers had mask-wearing intentions that were not affected by attitude either directly or indirectly. These findings provide useful implications to enhance the health safety of air travelers, especially in the US where opposing views toward mask-wearing still widely exist.

Keywords: COVID-19, passenger demographics, aircraft cabin, mask-wearing intention, attitude as mediator.

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Authors: S. Wechmongkhonkon, N.Poomtong, S. Areerachakul

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Water quality is a subject of ongoing concern. Deterioration of water quality has initiated serious management efforts in many countries. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (TColiform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of canals in Dusit district in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 96.52% in classifying the water quality of Dusit district canal in Bangkok Subsequently, this encouraging result could be applied with plan and management source of water quality.

Keywords: artificial neural network, classification, surface water quality

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Authors: E. Moroydor Derun, A. S. Kipcak, A. Kaplan, S. Piskin

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Magnesium wastes are produced by many industrial activities. This waste problem is becoming a future problem for the world. Magnesium borates have many advantages such as; high corrosion resistance, heat resistance, high coefficient of elasticity and can also be used in the production of material against radiation. Addition, magnesium borates have great potential in sectors including ceramic and detergents industry and superconducting materials. In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC. Several mole ratios of waste magnesium to H3BO3 are selected as; 1:2, 1:4, 1:6, 1:8, 1:10. Reaction time was determined as 1 hour. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques are applied to products. As a result the forms of mcallisterite “Mg2(B6O7(OH)6)2.9(H2O)”, admontite “MgO(B2O3)3.7(H2O)” and magnesium boron hydrate (MgO(B2O3)3.6(H2O)” are obtained. 

Keywords: Hydrothermal synthesis, magnesium borates, waste magnesium.

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Authors: Mazhar B. Tayel, Eslam I. AlSaba

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Heart is the most important part in the body of living organisms. It affects and is affected by any factor in the body. Therefore, it is a good detector for all conditions in the body. Heart signal is a non-stationary signal; thus, it is utmost important to study the variability of heart signal. The Heart Rate Variability (HRV) has attracted considerable attention in psychology, medicine and has become important dependent measure in psychophysiology and behavioral medicine. The standards of measurements, physiological interpretation and clinical use for HRV that are most often used were described in many researcher papers, however, remain complex issues are fraught with pitfalls. This paper presents one of the nonlinear techniques to analyze HRV. It discusses many points like, what Poincaré plot is and how Poincaré plot works; also, Poincaré plot's merits especially in HRV. Besides, it discusses the limitation of Poincaré cause of standard deviation SD1, SD2 and how to overcome this limitation by using complex correlation measure (CCM). The CCM is most sensitive to changes in temporal structure of the Poincaré plot as compared toSD1 and SD2.

Keywords: Heart rate variability, chaotic system, Poincaré, variance, standard deviation, complex correlation measure.

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Authors: Silvia Tamayo-Moreno, Diana Pérez-Marín

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In this paper, the possibility of children studying by using an interactive learning technology called Pedagogic Conversational Agent is presented. The main benefit is that the agent is able to adapt the dialogue to each student and to provide automatic feedback. Moreover, according to Math teachers, in many cases students are unable to solve the problems even knowing the procedure to solve them, because they do not understand what they have to do. The hypothesis is that if students are helped to understand what they have to solve, they will be able to do it. Taken that into account, we have started the development of Dr. Roland, an agent to help students understand Math problems following a User-Centered Design methodology. The use of this methodology is proposed, for the first time, to design pedagogic agents to teach any subject from Secondary down to Pre-Primary education. The reason behind proposing a methodology is that while working on this project, we noticed the lack of literature to design and evaluate agents. To cover this gap, we describe how User-Centered Design can be applied, and which usability techniques can be applied to evaluate the agent.

Keywords: Pedagogic conversational agent, human-computer interaction, user-centered design, natural language interface.

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Authors: Ahmed A. D. Sarhan, M. Sayuti, M. Hamdi

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Nowadays, the demand for high product quality focuses extensive attention to the quality of machined surface. The (CNC) milling machine facilities provides a wide variety of parameters set-up, making the machining process on the glass excellent in manufacturing complicated special products compared to other machining processes. However, the application of grinding process on the CNC milling machine could be an ideal solution to improve the product quality, but adopting the right machining parameters is required. In glass milling operation, several machining parameters are considered to be significant in affecting surface roughness. These parameters include the lubrication pressure, spindle speed, feed rate and depth of cut. In this research work, a fuzzy logic model is offered to predict the surface roughness of a machined surface in glass milling operation using CBN grinding tool. Four membership functions are allocated to be connected with each input of the model. The predicted results achieved via fuzzy logic model are compared to the experimental result. The result demonstrated settlement between the fuzzy model and experimental results with the 93.103% accuracy.

Keywords: CNC-machine, Glass milling, Grinding, Surface roughness, Cutting force, Fuzzy logic model.

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Authors: Atheel Hassan Alwash, Ahmad Zuhairi Abdullah, Norli Ismail

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Characteristics and sonocatalytic activity of zeolite Y catalysts loaded with TiO2 using impregnation and ion exchange methods for the degradation of amaranth dye were investigated. The Ion-exchange method was used to encapsulate the TiO2 into the internal pores of the zeolite while the incorporation of TiO2 mostly on the external surface of zeolite was carried out using the impregnation method. Different characterization techniques were used to elucidate the physicochemical properties of the produced catalysts. The framework of zeolite Y remained virtually unchanged after the encapsulation of TiO2 while the crystallinity of zeolite decreased significantly after the incorporation of 15 wt% of TiO2. The sonocatalytic activity was enhanced by TiO2 incorporation with maximum degradation efficiencies of 50% and 68% for the encapsulated titanium and titanium loaded onto the zeolite, respectively after 120min of reaction. Catalysts characteristics and sonocatalytic behaviors were significantly affected by the preparation method and the location of TiO2 introduced with zeolite structure. Behaviors in the sonocatalytic process were successfully correlated with the characteristics of the catalysts used.

Keywords: Sonocatalytic degradation, TiO2 loaded, ionexchange, impregnation, amaranth dye, process behavior.

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Authors: Moiz S. Vohra, Nagalingam Arun Prasanth, Wei L. Tan, S. H. Yeo

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The understanding of generation and collapse of acoustic cavitation bubbles are prerequisites for application of cavitation erosion. Microbubbles generated due to rapid fluctuation of pressure induced by propagation of ultrasonic wave lead to formation of high velocity microjets and or shock waves upon collapse. Due to vast application of ultrasonic, it is important to characterize and understand cavitation collapse pressure under the radiating surface at different conditions. A comparative investigation is carried out to determine impact load and dynamic pressure distribution exerted upon bubble collapse using thin film pressure sensors. Measurements were recorded at different input conditions such as amplitude, stand-off distance, insertion depth of the horn inside the liquid and pulse on-off time of acoustic vibrations. Impact force of 2.97 N is recorded at amplitude of 108 μm and stand-off distance of 1 mm from the sensor film, whereas impulsive force as low as 0.4 N is recorded at amplitude of 12 μm and stand-off distance of 5 mm from the sensor film. The results drawn from the investigation indicated that variety of impact loads can be achieved by controlling generation and collapse of bubbles, making it suitable to use for numerous application.

Keywords: Ultrasonic cavitation, bubble collapse, pressure mapping sensor, impact load.

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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: Ren Jian-min, Wu Si-wei, Jin Wei

Abstract:

CTMA-bentonite and BTEA-Bentonite prepared by Na-bentonite cation exchanged with cetyltrimethylammonium(CTMA) and benzyltriethylammonium (BTEA). Products were characterized by XRD and IR techniques.The d001 spacing value of CTMA-bentonite and BTEA-bentonite are 7.54Å and 3.50Å larger than that of Na-bentonite at 100% cation exchange capacity, respectively. The IR spectrum showed that the intensities of OH stretching and bending vibrations of the two organoclays decreased greatly comparing to untreated Na-bentonite. Batch experiments were carried out at 303 K, 318 K and 333 K to obtain the sorption isotherms of Crystal violet onto the two organoclays. The results show that the sorption isothermal data could be well described by Freundlich model. The dynamical data for the two organoclays fit well with pseudo-second-order kinetic model. The adsorption capacity of CTMA-bentonite was found higher than that of BTEA-Bentonite. Thermodynamic parameters such as changes in the free energy (ΔG°), the enthalpy (ΔH°) and the entropy (ΔS°) were also evaluated. The overall adsorption process of Crystal violet onto the two organoclays were spontaneous, endothermic physisorption. The CTMA-bentonite and BTEA-Bentonite could be employed as low-cost alternatives to activated carbon in wastewater treatment for the removal of color which comes from textile dyes.

Keywords: Characterization, Adsorption, Crystal violet, Bentonite, BTEA, CTMA

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Authors: N. Janjamraj, A. Oonsivilai

Abstract:

This paper present the harmonic elimination of hybrid multilevel inverters (HMI) which could be increase the number of output voltage level. Total Harmonic Distortion (THD) is one of the most important requirements concerning performance indices. Because of many numbers output levels of HMI, it had numerous unknown variables of eliminate undesired individual harmonic and THD nonlinear equations set. Optimized harmonic stepped waveform (OHSW) is solving switching angles conventional method, but most complicated for solving as added level. The artificial intelligent techniques are deliberation to solve this problem. This paper presents the Particle Swarm Optimization (PSO) technique for solving switching angles to get minimum THD and eliminate undesired individual harmonics of 15-levels hybrid multilevel inverters. Consequently it had many variables and could eliminate numerous harmonics. Both advantages including high level of inverter and Particle Swarm Optimization (PSO) are used as powerful tools for harmonics elimination.

Keywords: Multilevel Inverters, Particle Swarms Optimization, Harmonic Elimination.

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Authors: Waldemiro Francisco Sorte Junior

Abstract:

The Japanese integrative approach to social systems can be observed in supply chain management as well as in the relationship between public and private sectors. Both the Lean Production System and the Developmental State Model are characterized by efforts towards the achievement of mutual goals, resulting in initiatives for capacity building which emphasize the system level. In Brazil, although organizations undertake efforts to build capabilities at the individual and organizational levels, the system level is being neglected. Fieldwork data confirmed the findings of other studies in terms of the lack of integration in supply chain management in the Brazilian automobile industry. Moreover, due to the absence of an active role of the Brazilian state in its relationship with the private sector, automakers are not fully exploiting the opportunities in the domestic and regional markets. For promoting a higher level of economic growth as well as to increase the degree of spill-over of technologies and techniques, a more integrative approach is needed.

Keywords: Integration, Lean Production System, DevelopmentalState Model, Brazilian automobile industry.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: Ramya Dorai, M. Rajaram

Abstract:

A Mobile Adhoc Network (MANET) is a collection of mobile nodes that communicate with each other with wireless links and without pre-existing communication infrastructure. Routing is an important issue which impacts network performance. As MANETs lack central administration and prior organization, their security concerns are different from those of conventional networks. Wireless links make MANETs susceptible to attacks. This study proposes a new trust mechanism to mitigate wormhole attack in MANETs. Different optimization techniques find available optimal path from source to destination. This study extends trust and reputation to an improved link quality and channel utilization based Adhoc Ondemand Multipath Distance Vector (AOMDV). Differential Evolution (DE) is used for optimization.

Keywords: Mobile Adhoc Network (MANET), Adhoc Ondemand Multi-Path Distance Vector (AOMDV), Trust and Reputation, Differential Evolution (DE), Link Quality, Channel Utilization.

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Authors: Zhiqiang Xu, Hongfang Ma, Haitao Zhang, Weixin Qian, Weiyong Ying

Abstract:

SSZ-13 materials with different Si/Al ratio were prepared by varying the composition of aluminosilicate precursor solutions upon hydrothermal treatment at 150 °C. The Si/Al ratio of the initial system was systematically changed from 12.5 to infinity in order to study the limits of Al composition in precursor solutions for constructing CHA structure. The intermediates and final products were investigated by complementary techniques such as XRD, HRTEM, FESEM, and chemical analysis. NH₃-TPD was used to study the Brønsted acidity of SSZ-13 samples with different Si/Al ratios. The effect of the Si/Al ratio on the precursor species, ultimate crystal size, morphology and yield was investigated. The results revealed that Al species determine the nucleation rate and the number of nuclei, which is tied to the morphology and yield of SSZ-13. The size of SSZ-13 increased and the yield decreased as the Si/Al ratio was improved. Varying Si/Al ratio of the initial system is a facile, commercially viable method of tailoring SSZ-13 crystal size and morphology. Furthermore, SSZ-13 materials with different Si/Al ratio were tested as catalysts for the methanol to olefins (MTO) reaction at 350 °C. SSZ-13 with the Si/Al ratio of 35 shows the best MTO catalytic performance.

Keywords: Crystallization, MTO, Si/Al ratio, SSZ-13.

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