Search results for: Fuzzy analytic network process

Authors: Mahboobeh Abdoos, Karim Faez, Masoud Sabaei

Abstract:

Position based routing protocols are the kinds of routing protocols, which they use of nodes location information, instead of links information to routing. In position based routing protocols, it supposed that the packet source node has position information of itself and it's neighbors and packet destination node. Greedy is a very important position based routing protocol. In one of it's kinds, named MFR (Most Forward Within Radius), source node or packet forwarder node, sends packet to one of it's neighbors with most forward progress towards destination node (closest neighbor to destination). Using distance deciding metric in Greedy to forward packet to a neighbor node, is not suitable for all conditions. If closest neighbor to destination node, has high speed, in comparison with source node or intermediate packet forwarder node speed or has very low remained battery power, then packet loss probability is increased. Proposed strategy uses combination of metrics distancevelocity similarity-power, to deciding about giving the packet to which neighbor. Simulation results show that the proposed strategy has lower lost packets average than Greedy, so it has more reliability.

Keywords: Mobile Ad Hoc Network, Position Based, Reliability, Routing.

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Authors: Arijit Roy

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Occurrence of popcorn in IC packages while assembling them onto the PCB is a well known moisture sensitive reliability issues, especially for surface mount packages. Commonly reflow soldering simulation process is conducted to assess the impact of assembling IC package onto PCB. A strain gauge-based instrumentation is developed to investigate the popcorn effect in surface mount packages during reflow soldering process. The instrument is capable of providing real-time quantitative information of the occurrence popcorn phenomenon in IC packages. It is found that the popcorn occur temperatures between 218 to 241°C depending on moisture soak condition, but not at the peak temperature of the reflow process. The presence of popcorn and delamination are further confirmed by scanning acoustic tomography as a failure analysis.

Keywords: Instrumentation, Popcorn, Real-time, Solder Reflow, Strain Gauge.

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: ATR, HRRP, motion compensation, SFW, TMP.

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Authors: Yao-Tang Chang, Chuen-Ching Wang, Shu-Han Hu

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In order to implement flexibility as well as survivable capacities over passive optical network (PON), a new automatic random fault-recovery mechanism with array-waveguide-grating based (AWG-based) optical switch (OSW) is presented. Firstly, wavelength-division-multiplexing and optical code-division multiple-access (WDM/OCDMA) scheme are configured to meet the various geographical locations requirement between optical network unit (ONU) and optical line terminal (OLT). The AWG-base optical switch is designed and viewed as central star-mesh topology to prohibit/decrease the duplicated redundant elements such as fiber and transceiver as well. Hence, by simple monitoring and routing switch algorithm, random fault-recovery capacity is achieved over bi-directional (up/downstream) WDM/OCDMA scheme. When error of distribution fiber (DF) takes place or bit-error-rate (BER) is higher than 10-9 requirement, the primary/slave AWG-based OSW are adjusted and controlled dynamically to restore the affected ONU groups via the other working DFs immediately.

Keywords: Random fault recovery mechanism, Array-waveguide-grating based optical switch (AWG- based OSW), wavelength-division-multiplexing and optical code-divisionmultiple-access (WDM/ OCDMA)

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Authors: Umber Iqbal, Shaleeza Sohail, Muhammad Younas Javed

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True integration of multimedia services over wired or wireless networks increase the productivity and effectiveness in today-s networks. IP Multimedia Subsystems are Next Generation Network architecture to provide the multimedia services over fixed or mobile networks. This paper proposes an extended SIP-based QoS Management architecture for IMS services over underlying IP access networks. To guarantee the end-to-end QoS for IMS services in interconnection backbone, SIP based proxy Modules are introduced to support the QoS provisioning and to reduce the handoff disruption time over IP access networks. In our approach these SIP Modules implement the combination of Diffserv and MPLS QoS mechanisms to assure the guaranteed QoS for real-time multimedia services. To guarantee QoS over access networks, SIP Modules make QoS resource reservations in advance to provide best QoS to IMS users over heterogeneous networks. To obtain more reliable multimedia services, our approach allows the use of SCTP protocol over SIP instead of UDP due to its multi-streaming feature. This architecture enables QoS provisioning for IMS roaming users to differentiate IMS network from other common IP networks for transmission of realtime multimedia services. To validate our approach simulation models are developed on short scale basis. The results show that our approach yields comparable performance for efficient delivery of IMS services over heterogeneous IP access networks.

Keywords: SIP-Based QoS Management Architecture, IPMultimedia Subsystems, IP Access Networks

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Authors: Tomohiro Hachino, Hitoshi Takata, Shigeru Nakayama, Ichiro Iimura, Seiji Fukushima, Yasutaka Igarashi

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This paper presents a nonparametric identification of continuous-time nonlinear systems by using a Gaussian process (GP) model. The GP prior model is trained by artificial bee colony algorithm. The nonlinear function of the objective system is estimated as the predictive mean function of the GP, and the confidence measure of the estimated nonlinear function is given by the predictive covariance of the GP. The proposed identification method is applied to modeling of a simplified electric power system. Simulation results are shown to demonstrate the effectiveness of the proposed method.

Keywords: Artificial bee colony algorithm, Gaussian process model, identification, nonlinear system, electric power system.

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Afef Badri

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Metaphorical creativity does not constitute a static property of discourse. It is an interactive dynamic process created online. There has been a lack of research concerning online produced metaphorical creativity. This paper intends to account for metaphorical creativity in online talk-in-interaction as a dynamic process that emerges as discourse unfolds. It brings together insights from the emergentist approach to the study of metaphor in verbal interactions and insights from conceptual blending approach as a model for analysing online metaphorical constructions to propose a model for studying metaphorical creativity in interactive talk. The model is based on three focal points. First, metaphorical creativity is a dynamic emergent and open-to-change process that evolves in real time as interlocutors constantly blend and re-blend previous metaphorical contributions. Second, it is not a product of isolated individual minds but a joint achievement that is co-constructed and co-elaborated by interlocutors. The third and most important point is that the emergent process of metaphorical creativity is tightly shaped by contextual variables surrounding talk-in-interaction. It is grounded in the framework of interpretation of interlocutors. It is constrained by preceding contributions in a way that creates textual cohesion of the verbal exchange and it is also a goal-oriented process predefined by the communicative intention of each participant in a way that reveals the ideological coherence/incoherence of the entire conversation.

Keywords: Communicative intention, conceptual blending, contextual variables, the emergentist approach, ideological coherence, metaphorical creativity, textual cohesion

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Authors: Pradeep M., N. S. Mahesh, Raja Hussain

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Resistance spot welding (RSW) has been used widely to join sheet metals. It has been a challenge to get required weld quality in spot welding of dissimilar thickness materials. Weld parameters are not generally available in standards for thickness beyond 4mm. This paper presents the welding process design and parameter optimization of RSW used in joining of low carbon steel sheet of thickness 0.8 mm and metal strips of cross section 10 x 5mm for electrical motor applications. Taguchi quality design was adopted for weld current and time optimization using L9 orthogonal array. Optimum process parameters (current- 3.5kA and time- 10 cycles) were obtained from the Taguchi analysis and shear test results. Confirmation experiment result revealed that the weld quality was within acceptable interval. Further, numerical simulation of RSW process was carried out with selected weld parameters to quantify the temperature at faying surface and check for formation of appropriate nugget. The nugget geometry measured after peel test and predicted from numerical validation method were similar and in accordance with the standards.

Keywords: Resistance spot welding, dissimilar thickness, weld parameters, Taguchi method, numerical modeling.

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Authors: Ali Samadi Afshar, Sayed Reaza Hashemi

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In the gas refineries of Iran-s South Pars Gas Complex, Sulfrex demercaptanization process is used to remove volatile and corrosive mercaptans from liquefied petroleum gases by caustic solution. This process consists of two steps. Removing low molecular weight mercaptans and regeneration exhaust caustic. Some parameters such as LPG feed temperature, caustic concentration and feed-s mercaptan in extraction step and sodium mercaptide content in caustic, catalyst concentration, caustic temperature, air injection rate in regeneration step are effective factors. In this paper was focused on temperature factor that play key role in mercaptans extraction and caustic regeneration. The experimental results demonstrated by optimization of temperature, sodium mercaptide content in caustic because of good oxidation minimized and sulfur impurities in product reduced.

Keywords: Caustic regeneration, demercaptanization, LPG sweetening, mercaptan extraction, temperature.

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Authors: Aboamama Atahar Ahmed, Muhammad Shafie Abd Latiff, Kamalrulnizam Abu Bakar, Zainul AhmadRajion

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Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.

Keywords: Visualization, Grid computing, Medical datasets, visualization techniques, thin clients, Globus toolkit, VTK.

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Authors: Rosziati Ibrahim, Siow Yen Yen

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System development life cycle (SDLC) is a process uses during the development of any system. SDLC consists of four main phases: analysis, design, implement and testing. During analysis phase, context diagram and data flow diagrams are used to produce the process model of a system. A consistency of the context diagram to lower-level data flow diagrams is very important in smoothing up developing process of a system. However, manual consistency check from context diagram to lower-level data flow diagrams by using a checklist is time-consuming process. At the same time, the limitation of human ability to validate the errors is one of the factors that influence the correctness and balancing of the diagrams. This paper presents a tool that automates the consistency check between Data Flow Diagrams (DFDs) based on the rules of DFDs. The tool serves two purposes: as an editor to draw the diagrams and as a checker to check the correctness of the diagrams drawn. The consistency check from context diagram to lower-level data flow diagrams is embedded inside the tool to overcome the manual checking problem.

Keywords: Data Flow Diagram, Context Diagram, ConsistencyCheck, Syntax and Semantic Rules

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Authors: Abhimanyu Pati, Prabir K. Bandyopadhyay

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The paper intends to highlight the significance of Digital Manufacturing (DM) strategy in support and achievement of business strategy and goals of any manufacturing organization. Towards this end, DM initiatives have been given a process perspective, while not undermining its technological significance, with a view to link its benefits directly with fulfilment of customer needs and expectations in a responsive and cost-effective manner. A digital process model has been proposed to categorize digitally enabled organizational processes with a view to create synergistic groups, which adopt and use digital tools having similar characteristics and functionalities. This will throw future opportunities for researchers and developers to create a unified technology environment for integration and orchestration of processes. Secondly, an effort has been made to apply “what” and “how” features of Quality Function Deployment (QFD) framework to establish the relationship between customers’ needs – both for external and internal customers, and the features of various digital processes, which support for the achievement of these customer expectations. The paper finally concludes that in the present highly competitive environment, business organizations cannot thrive to sustain unless they understand the significance of digital strategy and integrate it with their business strategy with a clearly defined implementation roadmap. A process-oriented approach to DM strategy will help business executives and leaders to appreciate its value propositions and its direct link to organization’s competitiveness.

Keywords: Digital manufacturing, digital process model, quality function deployment, business strategy.

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Authors: Muhammad Marsudi, Hani Shafeek

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The purpose of this paper is to simulate the production process of a metal stamping industry and to evaluate the utilization of the production line by using ARENA simulation software. The process time and the standard time for each process of the production line is obtained from data given by the company management. Other data are collected through direct observation of the line. There are three work stations performing ten different types of processes in order to produce a single product type. Arena simulation model is then developed based on the collected data. Verification and validation are done to the Arena model, and finally the result of Arena simulation can be analyzed. It is found that utilization at each workstation will increase if batch size is increased although throughput rate remains/is kept constant. This study is very useful for the company because the company needs to improve the efficiency and utilization of its production lines.

Keywords: Arena software, case study, production line, utilization.

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Authors: A. Kulprasutidilok

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In order to address the social factors of elderly health care, researcher and community members have turned to more inclusive and participatory approaches to research and interventions. One such approach, community-based participatory research (CBPR) in public health, has received increased attention as the academic and public health communities struggle to address the persistent problems of disparities in the use of health care and health outcomes for several over the past decade. As Thailand becomes an ageing society, health services and proper care systems specifically for the elderly group need to be prepared and well established. The purpose of this assignment was to study the health problems and was to explore the process of community participation in elderly health care. Participants in this study were member of elderly group of Paisanee Ramintra 65 community in Bangkok, Thailand. The results indicated two important components of community participation process in elderly health care: 1) a process to develop community participation in elderly health care, and 2) outcomes resulting from such process. The development of community participation consisted of four processes. As for the outcomes of the community participation development process, they consisted of elderly in the community got jointly and formulated a group, which strengthened the project because of collaborative supervision among themselves. Moreover, inactive health care services have changed to being energetic and focus on health promotion rather than medical achievement and elderly association of community can perform health care activities for chronically illness through the achievement of this development; consequently, they increasingly gained access to physical, cognitive, and social activity.

Keywords: Community-based participatory research, elderly health care, Thailand.

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Authors: Z. Pavlík, H. Benešová, P. Matiašovský, M. Pavlíková

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In this paper, study on carbonation process of several types of advanced plasters on lime basis is presented. The movement of carbonation head was measured by colorimetric method using phenolphtalein. The rate of carbonation was accessed also by gravimetric method. Samples of studied materials were placed into the climatic chamber for simulation of environment with high concentration of CO2. The particular samples were on all lateral sides and on the bottom side provided by epoxy resin in order to arrange 1-D transport of CO2 into the studied samples. The carbonation rates of particular materials pointed to the time dependence of diffusion process of CO2 for all the studied plasters. From the quantitative point of view, the carbonation of advanced modified plasters was much faster than for the reference lime plaster, what is beneficial for the practical application of the tested newly developed materials.

Keywords: Carbonation, colorimetric method, gravimetric method, lime-based plasters, pozzolana admixtures.

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Authors: Jonghyun Park, Soonyoung Park, Sanggyun Kim, Wanhyun Cho, Sunworl Kim

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In general, image-based 3D scenes can now be found in many popular vision systems, computer games and virtual reality tours. So, It is important to segment ROI (region of interest) from input scenes as a preprocessing step for geometric stricture detection in 3D scene. In this paper, we propose a method for segmenting ROI based on tensor voting and Dirichlet process mixture model. In particular, to estimate geometric structure information for 3D scene from a single outdoor image, we apply the tensor voting and Dirichlet process mixture model to a image segmentation. The tensor voting is used based on the fact that homogeneous region in an image are usually close together on a smooth region and therefore the tokens corresponding to centers of these regions have high saliency values. The proposed approach is a novel nonparametric Bayesian segmentation method using Gaussian Dirichlet process mixture model to automatically segment various natural scenes. Finally, our method can label regions of the input image into coarse categories: “ground", “sky", and “vertical" for 3D application. The experimental results show that our method successfully segments coarse regions in many complex natural scene images for 3D.

Keywords: Region segmentation, tensor voting, image-based 3D, geometric structure, Gaussian Dirichlet process mixture model

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Authors: Homayoon Zarshenas, Mahdi Bamdad, Hadi Grailu, Akbar A. Shakoori

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In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Keywords: BCI, EEG, Classifier, Fuzzy operator, OWA.

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Authors: Ramaswamy Palaniappan, Nai-Jen Huan

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Classification of electroencephalogram (EEG) signals extracted during mental tasks is a technique that is actively pursued for Brain Computer Interfaces (BCI) designs. In this paper, we compared the classification performances of univariateautoregressive (AR) and multivariate autoregressive (MAR) models for representing EEG signals that were extracted during different mental tasks. Multilayer Perceptron (MLP) neural network (NN) trained by the backpropagation (BP) algorithm was used to classify these features into the different categories representing the mental tasks. Classification performances were also compared across different mental task combinations and 2 sets of hidden units (HU): 2 to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different mental tasks from 4 subjects were used in the experimental study and combinations of 2 different mental tasks were studied for each subject. Three different feature extraction methods with 6th order were used to extract features from these EEG signals: AR coefficients computed with Burg-s algorithm (ARBG), AR coefficients computed with stepwise least square algorithm (ARLS) and MAR coefficients computed with stepwise least square algorithm. The best results were obtained with 20 to 100 HU using ARBG. It is concluded that i) it is important to choose the suitable mental tasks for different individuals for a successful BCI design, ii) higher HU are more suitable and iii) ARBG is the most suitable feature extraction method.

Keywords: Autoregressive, Brain-Computer Interface, Electroencephalogram, Neural Network.

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: M. Hossain, A. Abdkader, C. Cherif, A. Berger, M. Sparing, R. Hühne, L. Schultz, K. Nielsch

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Due to the best quality of yarn and the flexibility of the machine, the ring spinning process is the most widely used spinning method for short staple yarn production. However, the productivity of these machines is still much lower in comparison to other spinning systems such as rotor or air-jet spinning process. The main reason for this limitation lies on the twisting mechanism of the ring spinning process. In the ring/traveler twisting system, each rotation of the traveler along with the ring inserts twist in the yarn. The rotation of the traveler at higher speed includes strong frictional forces, which in turn generates heat. Different ring/traveler systems concerning with its geometries, material combinations and coatings have already been implemented to solve the frictional problem. However, such developments can neither completely solve the frictional problem nor increase the productivity. The friction free superconducting magnetic bearing (SMB) system can be a right alternative replacing the existing ring/traveler system. The unique concept of SMB bearings is that they possess a self-stabilizing behavior, i.e. they remain fully passive without any necessity for expensive position sensing and control. Within the framework of a research project funded by German research foundation (DFG), suitable concepts of the SMB-system have been designed, developed, and integrated as a twisting device of ring spinning replacing the existing ring/traveler system. With the help of the developed mathematical model and experimental investigation, the physical limitations of this innovative twisting device in the spinning process have been determined. The interaction among the parameters of the spinning process and the superconducting twisting element has been further evaluated, which derives the concrete information regarding the new spinning process. Moreover, the influence of the implemented SMB twisting system on the yarn quality has been analyzed with respect to different process parameters. The presented work reveals the enormous potential of the innovative twisting mechanism, so that the productivity of the ring spinning process especially in case of thermoplastic materials can be at least doubled for the first time in a hundred years. The SMB ring spinning tester has also been presented in the international fair “International Textile Machinery Association (ITMA) 2015”.

Keywords: Ring spinning, superconducting magnetic bearing, yarn properties, productivity.

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Authors: Ena Bhattacharyya

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The notion of communicative competence has been deemed fuzzy in communication studies. This fuzziness has led to tensions among engineers across tenures in interpreting what constitutes communicative competence. The study seeks to investigate novice and professional engineers- understanding of the said notion in terms of two main elements of communicative competence: linguistic and rhetorical competence. Novice engineers are final year engineering students, whilst professional engineers represent engineers who have at least 5 years working experience. Novice and professional engineers were interviewed to gauge their perceptions on linguistic and rhetorical features deemed necessary to enhance communicative competence for the profession. Both groups indicated awareness and differences on the importance of the sub-sets of communicative competence, namely, rhetorical explanatory competence, linguistic oral immediacy competence, technical competence and meta-cognitive competence. Such differences, a possible attribute of the learning theory, inadvertently indicate sublime differences in the way novice and professional engineers perceive communicative competence.

Keywords: Communicative competence, technical oral presentation, linguistic competence, rhetorical competence.

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Authors: Sung-Hun Lee, Yun-Seong Lee, Jin-O Kim

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Reliability Centered Maintenance(RCM) is one of most widely used methods in the modern power system to schedule a maintenance cycle and determine the priority of inspection. In order to apply the RCM method to the Smart Grid, a precedence study for the new structure of rearranged system should be performed due to introduction of additional installation such as renewable and sustainable energy resources, energy storage devices and advanced metering infrastructure. This paper proposes a new method to evaluate the priority of maintenance and inspection of the power system facilities in the Smart Grid using the Risk Priority Number. In order to calculate that risk index, it is required that the reliability block diagram should be analyzed for the Smart Grid system. Finally, the feasible technical method is discussed to estimate the risk potential as part of the RCM procedure.

Keywords: Expert System, FMECA, Fuzzy Theory, Reliability Centered Maintenance, Risk Priority Number

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Authors: Melvin Ballera, Mosbah Mohamed Elssaedi, Ahmed Khalil Zohdy

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Collaborative problem solving in e-learning can take in the form of discussion among learner, creating a highly social learning environment and characterized by participation and interactivity. This paper, designed a collaborative learning environment where agent act as co-learner, can play different roles during interaction. Since different roles have been assigned to the agent, learner will assume that multiple co-learner exists to help and guide him all throughout the collaborative problem solving process, but in fact, alone during the learning process. Specifically, it answers the questions what roles of the agent should be incorporated to contribute better learning outcomes, how agent will facilitate the communication process to provide social learning and interactivity and what are the specific instructional strategies that facilitate learner participation, increased skill acquisition and develop critical thinking.

Keywords: Collaborative e-learning, collaborative problem solving, , imaginary co-learner, social learning.

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Authors: Oliver Haala, Bernhard Wagner, Maximilian Hofmann, Martin Marz

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The excellent suitability of the externally excited synchronous machine (EESM) in automotive traction drive applications is justified by its high efficiency over the whole operation range and the high availability of materials. Usually, maximum efficiency is obtained by modelling each single loss and minimizing the sum of all losses. As a result, the quality of the optimization highly depends on the precision of the model. Moreover, it requires accurate knowledge of the saturation dependent machine inductances. Therefore, the present contribution proposes a method to minimize the overall losses of a salient pole EESM and its inverter in steady state operation based on measurement data only. Since this method does not require any manufacturer data, it is well suited for an automated measurement data evaluation and inverter parametrization. The field oriented control (FOC) of an EESM provides three current components resp. three degrees of freedom (DOF). An analytic minimization of the copper losses in the stator and the rotor (assuming constant inductances) is performed and serves as a first approximation of how to choose the optimal current reference values. After a numeric offline minimization of the overall losses based on measurement data the results are compared to a control strategy that satisfies cos (ϕ) = 1.

Keywords: Current control, efficiency, externally excited synchronous machine, optimization.

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Authors: Zoe Chang, Max Williams, Gautham Das

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The purpose of this study is to evaluate the incorporation of hemp fibers (HF) in concrete. Hemp fiber reinforced concrete (HFRC) is becoming more popular as an alternative for regular mix designs. This study was done to evaluate the compressive strength of HFRC regarding mix procedure. HF were obtained from the manufacturer and hand processed to ensure uniformity in width and length. The fibers were added to concrete as both wet and dry mix to investigate and optimize the mix design process. Results indicated that the dry mix had a compressive strength of 1157 psi compared to the wet mix of 985 psi. This dry mix compressive strength was within range of the standard mix compressive strength of 1533 psi. The statistical analysis revealed that the mix design process needs further optimization and uniformity concerning the addition of HF. Regression analysis revealed that the standard mix design had a coefficient of 0.9 as compared to the dry mix of 0.375 indicating a variation in the mixing process. While completing the dry mix, the addition of plain HF caused them to intertwine creating lumps and inconsistency. However, during the wet mixing process, combining water and HF before incorporation allows the fibers to uniformly disperse within the mix hence the regression analysis indicated a better coefficient of 0.55. This study concludes that HRFC is a viable alternative to regular mixes however more research surrounding its characteristics needs to be conducted.

Keywords: hemp fibers, hemp reinforced concrete, wet and dry, freeze thaw testing, compressive strength

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Authors: Udeme O. Ini, Edikan E. Akpanibah

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This paper studies the optimal investment strategies for a plan member (PM) in a defined contribution (DC) pension scheme with transaction cost, taxes on invested funds and couple risky assets (stocks) under the Ornstein-Uhlenbeck (O-U) process. The PM’s portfolio is assumed to consist of a risk-free asset and two risky assets where the two risky assets are driven by the O-U process. The Legendre transformation and dual theory is use to transform the resultant optimal control problem which is a nonlinear partial differential equation (PDE) into linear PDE and the resultant linear PDE is then solved for the explicit solutions of the optimal investment strategies for PM exhibiting constant absolute risk aversion (CARA) using change of variable technique. Furthermore, theoretical analysis is used to study the influences of some sensitive parameters on the optimal investment strategies with observations that the optimal investment strategies for the two risky assets increase with increase in the dividend and decreases with increase in tax on the invested funds, risk averse coefficient, initial fund size and the transaction cost.

Keywords: Ornstein-Uhlenbeck process, portfolio management, Legendre transforms, CARA utility.

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Authors: Mafawez Alharbi, Mahdi Jemmali

Abstract:

E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: Artificial intelligence, architecture, e-learning, software engineering, processing.

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Authors: Abdelali Joumad, Abdelaziz Nasroallah

Abstract:

In unsupervised segmentation context, we propose a bi-dimensional hidden Markov chain model (X,Y) that we adapt to the image segmentation problem. The bi-dimensional observed process Y = (Y 1, Y 2) is such that Y 1 represents the noisy image and Y 2 represents a noisy supplementary information on the image, for example a noisy proportion of pixels of the same type in a neighborhood of the current pixel. The proposed model can be seen as a competitive alternative to the Hilbert-Peano scan. We propose a bayesian algorithm to estimate parameters of the considered model. The performance of this algorithm is globally favorable, compared to the bi-dimensional EM algorithm through numerical and visual data.

Keywords: Image segmentation, Hidden Markov chain with a bi-dimensional observed process, Peano-Hilbert scan, Bayesian approach, MCMC methods, Bi-dimensional EM algorithm.

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Authors: Xing Feng, Yuanbin Li

Abstract:

Oil spills at sea can cause severe marine environmental damage, including bringing huge hazards to living resources and human beings. In situ burning or chemical dispersant methods can be used to handle the oil spills sometimes, but these approaches will bring secondary pollution and fail in some situations. Oil recovery techniques have also been developed to recover oil using oil skimmer equipment installed on ships, while the hydrodynamic process of the oil flowing through the oil skimmer is very complicated and important for evaluating the recovery efficiency. Based on this, a two-dimensional numerical simulation platform for simulating the hydrodynamic process of the oil flowing through the oil skimmer is established based on the Navier-Stokes equations for viscous, incompressible fluid. Finally, the influence of the design of the flow channel in the curved plane oil skimmer on the hydrodynamic process of the oil flowing through the oil skimmer is investigated based on the established simulation platform.

Keywords: Curved plane oil skimmer, flow channel, CFD, VOF.

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