Search results for: Applications of Fuzzy Logic and Neural Networksin Robotics

Authors: W. V. W. H. Wickramaarachchi, S. Walpalage, S. M. Egodage

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Thermoplastic elastomer (TPE) is a multifunctional polymeric material which possesses a combination of excellent properties of parent materials. Basically, TPE has a rubber phase and a thermoplastic phase which gives processability as thermoplastics. When the rubber phase is partially or fully crosslinked in the thermoplastic matrix, TPE is called as thermoplastic elastomer vulcanizate (TPV). If the rubber phase is non-crosslinked, it is called as thermoplastic elastomer olefin (TPO). Nowadays TPEs are introduced into the commercial market with different products. However, the application of TPE as a roofing material is limited. Out of the commercially available roofing products from different materials, only single ply roofing membranes and plastic roofing sheets are produced from rubbers and plastics. Natural rubber (NR) and high density polyethylene (HDPE) are used in various industrial applications individually with some drawbacks. Therefore, this study was focused to develop both TPO and TPV blends from NR and HDPE at different compositions and then to identify the best blend composition to use as a roofing material. A series of blends by varying NR loading from 10 wt% to 50 wt%, at 10 wt% intervals, were prepared using a twin screw extruder. Dicumyl peroxide was used as a crosslinker for TPV. The standard properties for a roofing material like tensile properties tear strength, hardness, impact strength, water absorption, swell/gel analysis and thermal characteristics of the blends were investigated. Change of tensile strength after exposing to UV radiation was also studied. Tensile strength, hardness, tear strength, melting temperature and gel content of TPVs show higher values compared to TPOs at every loading studied, while water absorption and swelling index show lower values, suggesting TPVs are more suitable than TPOs for roofing applications. Most of the optimum properties were shown at 10/90 (NR/HDPE) composition. However, high impact strength and gel content were shown at 20/80 (NR/HDPE) composition. Impact strength, as being an energy absorbing property, is the most important for a roofing material in order to resist impact loads. Therefore, 20/80 (NR/HDPE) is identified as the best blend composition. UV resistance and other properties required for a roofing material could be achieved by incorporating suitable additives to TPVs.

Keywords: Thermoplastic elastomer, natural rubber, high density polyethylene, roofing material.

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

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Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.

Keywords: Backpropagation algorithm, conjugacy condition, line search, matrix perturbation

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Authors: B. Leela Devi, A. Sankar

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The web’s increased popularity has included a huge amount of information, due to which automated web page classification systems are essential to improve search engines’ performance. Web pages have many features like HTML or XML tags, hyperlinks, URLs and text contents which can be considered during an automated classification process. It is known that Webpage classification is enhanced by hyperlinks as it reflects Web page linkages. The aim of this study is to reduce the number of features to be used to improve the accuracy of the classification of web pages. In this paper, a novel feature selection method using an improved Particle Swarm Optimization (PSO) using principle of evolution is proposed. The extracted features were tested on the WebKB dataset using a parallel Neural Network to reduce the computational cost.

Keywords: Web page classification, WebKB Dataset, Term Frequency-Inverse Document Frequency (TF-IDF), Particle Swarm Optimization (PSO).

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Authors: Roman Ružarovský, Radovan Holubek, Daynier Rolando Delgado Sobrino

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Currently is characterized production engineering together with the integration of industrial automation and robotics such very quick view of to manufacture the products. The production range is continuously changing, expanding and producers have to be flexible in this regard. It means that need to offer production possibilities, which can respond to the quick change. Engineering product development is focused on supporting CAD software, such systems are mainly used for product design. That manufacturers are competitive, it should be kept procured machines made available capable of responding to output flexibility. In response to that problem is the development of flexible manufacturing systems, consisting of various automated systems. The integration of flexible manufacturing systems and subunits together with product design and of engineering is a possible solution for this issue. Integration is possible through the implementation of CIM systems. Such a solution and finding a hyphen between CAD and procurement system ICIM 3000 from Festo Co. is engaged in the research project and this contribution. This can be designed the products in CAD systems and watch the manufacturing process from order to shipping by the development of methods and processes of integration, This can be modeled in CAD systems products and watch the manufacturing process from order to shipping to develop methods and processes of integration, which will improve support for product design parameters by monitoring of the production process, by creating of programs for production using the CAD and therefore accelerates the a total of process from design to implementation.

Keywords: CAD- Computer Aided Design, CAM- Computer Aided Manufacturing, CIM- Computer integrated manufacturing, iCIM 3000, integration, direct production from CAD.

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Authors: Yu J. Chiu, Chia H. Yeh

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Innovation is more important in any companies. However, it is not easy to measure the innovation performance correctly. Patent is one of measuring index nowadays. This paper wants to purpose an approach for valuing patents based on market reaction to patent infringement litigations. The interesting phenomenon is found from collection of patent infringement litigation events. That is if any patent litigation event occurs the stock value will follow changing. The plaintiffs- stock value raises some percentage. According to this interesting phenomenon, the relationship between patent litigation and stock value is tested and verified. And then, the stock value variation is used to deduce the infringed patents- value. The purpose of this study is providing another concept model to evaluate the infringed patents. This study can provide a decision assist system to help drafting patent litigation strategy and determine the technology value

Keywords: Patent valuation, infringement litigations, stock value, artificial neural networks.

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. However, accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER benefiting from deep learning, especially CNN and VGG16. First, the data are pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning.

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Authors: Bhavneet Sidhu, Hardeep Singh, Amit Chhabra

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The world of wireless telecommunications is rapidly evolving. Technologies under research and development promise to deliver more services to more users in less time. This paper presents the emerging technologies helping wireless systems grow from where we are today into our visions of the future. This paper will cover the applications and characteristics of emerging wireless technologies: Wireless Local Area Networks (WiFi-802.11n), Wireless Personal Area Networks (ZigBee) and Wireless Metropolitan Area Networks (WiMAX). The purpose of this paper is to explain the impending 802.11n standard and how it will enable WLANs to support emerging media-rich applications. The paper will also detail how 802.11n compares with existing WLAN standards and offer strategies for users considering higher-bandwidth alternatives. The emerging IEEE 802.15.4 (ZigBee) standard aims to provide low data rate wireless communications with high-precision ranging and localization, by employing UWB technologies for a low-power and low cost solution. WiMAX (Worldwide Interoperability for Microwave Access) is a standard for wireless data transmission covering a range similar to cellular phone towers. With high performance in both distance and throughput, WiMAX technology could be a boon to current Internet providers seeking to become the leader of next generation wireless Internet access. This paper also explores how these emerging technologies differ from one another.

Keywords: MIMO technology, WiFi, WiMAX, ZigBee.

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Authors: Metehan Makinacı

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The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.

Keywords: Computer-aided diagnosis, support vector machines, Gauss-Markov random fields, texture classification.

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Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov

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This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.

Keywords: Autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem.

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Authors: R. Kanmaniraja, R. Freshipali, J. Abdullah, K. Niranjan, K. Balasubramani, V. R. Sanal Kumar

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The present environmental issues have made aircraft jet noise reduction a crucial problem in aero-acoustics research. Acoustic studies reveal that addition of chevrons to the nozzle reduces the sound pressure level reasonably with acceptable reduction in performance. In this paper comprehensive numerical studies on acoustic characteristics of different types of chevron nozzles have been carried out with non-reacting flows for the shape optimization of chevrons in supersonic nozzles for aerospace applications. The numerical studies have been carried out using a validated steady 3D density based, k-ε turbulence model. In this paper chevron with sharp edge, flat edge, round edge and U-type edge are selected for the jet acoustic characterization of supersonic nozzles. We observed that compared to the base model a case with round-shaped chevron nozzle could reduce 4.13% acoustic level with 0.6% thrust loss. We concluded that the prudent selection of the chevron shape will enable an appreciable reduction of the aircraft jet noise without compromising its overall performance. It is evident from the present numerical simulations that k-ε model can predict reasonably well the acoustic level of chevron supersonic nozzles for its shape optimization.

Keywords: Supersonic nozzle, Chevron, Acoustic level, Shape Optimization of Chevron Nozzles, Jet noise suppression.

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Authors: T. Hirner, J. Polec

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This paper presents an approach for an unequal error protection of facial features of personal ID images coding. We consider unequal error protection (UEP) strategies for the efficient progressive transmission of embedded image codes over noisy channels. This new method is based on the progressive image compression embedded zerotree wavelet (EZW) algorithm and UEP technique with defined region of interest (ROI). In this case is ROI equal facial features within personal ID image. ROI technique is important in applications with different parts of importance. In ROI coding, a chosen ROI is encoded with higher quality than the background (BG). Unequal error protection of image is provided by different coding techniques and encoding LL band separately. In our proposed method, image is divided into two parts (ROI, BG) that consist of more important bytes (MIB) and less important bytes (LIB). The proposed unequal error protection of image transmission has shown to be more appropriate to low bit rate applications, producing better quality output for ROI of the compresses image. The experimental results verify effectiveness of the design. The results of our method demonstrate the comparison of the UEP of image transmission with defined ROI with facial features and the equal error protection (EEP) over additive white gaussian noise (AWGN) channel.

Keywords: Embedded zerotree wavelet (EZW), equal error protection (EEP), facial features, personal ID images, region of interest (ROI), unequal error protection (UEP)

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Authors: Reza Keihani, Ali Bahadori-Jahromi, Timothy James Clacy

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Plastic as an environmental burden is a well-rehearsed topic in the research area. This is due to its global demand and destructive impacts on the environment, which has been a significant concern to the governments. Typically, the use of plastic in the construction industry is seen across low-density, non-structural applications due to its diverse range of benefits including high strength-to-weight ratios, manipulability and durability. It can be said that with the level of plastic consumption experienced in the construction industry, an ongoing responsibility is shown for this sector to continually innovate alternatives for application of recycled plastic waste such as using plastic made replacement from polyethylene, polystyrene, polyvinyl and polypropylene in the concrete mix design. In this study, the impact of partially replaced fine aggregate with polypropylene in the concrete mix design was investigated to evaluate the concrete’s compressive strength by conducting an experimental work which comprises of six concrete mix batches with polypropylene replacements ranging from 0.5 to 3.0%. The results demonstrated a typical decline in the compressive strength with the addition of plastic aggregate, despite this reduction generally mitigated as the level of plastic in the concrete mix increased. Furthermore, two of the six plastic-containing concrete mixes tested in the current study exceeded the ST5 standardised prescribed concrete mix compressive strength requirement at 28-days containing 1.50% and 2.50% plastic aggregates, which demonstrated the potential for use of recycled polypropylene in structural applications, as a partial by mass, fine aggregate replacement in the concrete mix.

Keywords: Compressive strength, concrete, polypropylene, sustainability.

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Authors: Z. M. Najmi

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Over the years, the question around Artificial Intelligence has always been one with many answers. Whether by means of use in business and industry or complicated algorithmic programming, management of these technologies has always been the core focus. More recently, technologies have been questioned in industry and society alike as to whether they have improved human-centred design, assisted choices and objectives, and had a hand in systematic processes across the board. With these questions the answer may lie within AI technologies, and the steps needed in removing common human error. Elements such as Machine Learning, Deep Learning, Recommender Systems and Natural Language Processing will all be features to consider moving forward. Our previous intervention with AI applications has resulted in increased productivity, however, raised concerns for the continuation of traditional human-centred occupations. Emerging technologies such as Augmented Reality and Virtual Reality have all played a part in this during AI’s prominent rise. As mentioned, AI has been constantly under the microscope; the benefits and drawbacks may seem endless is wide, but AI is something we must take notice of and adapt into our everyday lives. The aim of this paper is to give an overview of the technologies surrounding A.I. and its’ related technologies. A comprehensive review has been written as a timeline of the developing events and key points in the history of Artificial Intelligence. This research is gathered entirely from secondary research, academic statements of knowledge and gathered to produce an understanding of the timeline of AI.

Keywords: Artificial Intelligence, Deep Learning, Augmented Reality, Reinforcement Learning, Machine Learning, Supervised Learning.

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Authors: Chan Weng Howe, Mohd Saberi Mohamad

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Protein residue contact map is a compact representation of secondary structure of protein. Due to the information hold in the contact map, attentions from researchers in related field were drawn and plenty of works have been done throughout the past decade. Artificial intelligence approaches have been widely adapted in related works such as neural networks, genetic programming, and Hidden Markov model as well as support vector machine. However, the performance of the prediction was not generalized which probably depends on the data used to train and generate the prediction model. This situation shown the importance of the features or information used in affecting the prediction performance. In this research, support vector machine was used to predict protein residue contact map on different combination of features in order to show and analyze the effectiveness of the features.

Keywords: contact map, protein residue contact, support vector machine, protein structure prediction

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Authors: Pin-Hsu Kao, Wen-Shou Tseng, Hung-Ming Tai, Yuan-Ming Chang, Jenh-Yih Juang

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We report a lithography-free approach to fabricate the biomimetics, quasi-beehive Si nanostructures (QBSNs), on Si-substrates. The self-assembled SiGe nanoislands via the strain induced surface roughening (Asaro-Tiller-Grinfeld instability) during in-situ annealing play a key role as patterned sacrifice regions for subsequent reactive ion etching (RIE) process performed for fabricating quasi-beehive nanostructures on Si-substrates. As the measurements of field emission, the bare QBSNs show poor field emission performance, resulted from the existence of the native oxide layer which forms an insurmountable barrier for electron emission. In order to dramatically improve the field emission characteristics, the platinum nanopillars (Pt-NPs) were deposited on QBSNs to form Pt-NPs/QBSNs heterostructures. The turn-on field of Pt-NPs/QBSNs is as low as 2.29 V/μm (corresponding current density of 1 μA/cm2), and the field enhancement factor (β-value) is significantly increased to 6067. More importantly, the uniform and continuous electrons excite light emission, due to the surrounding filed emitters from Pt-NPs/QBSNs, can be easily obtained. This approach does not require an expensive photolithographic process and possesses great potential for applications.

Keywords: Biomimetics, quasi-beehive Si, SiGe nanoislands, platinum nanopillars, field emission.

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Authors: Ahmad R. Zamani, Luigi Sanguigno, Angelo R. Maligno

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A 3D woven composite, designed for automotive applications, is studied using Abaqus Finite Element (FE) software suite. Python scripts were developed to build FE models of the woven composite in Complete Abaqus Environment (CAE). They can read TexGen or WiseTex files and automatically generate consistent meshes of the fabric and the matrix. A user menu is provided to help define parameters for the FE models, such as type and size of the elements in fabric and matrix as well as the type of matrix-fabric interaction. Node-to-node constraints were imposed to guarantee periodicity of the deformed shapes at the boundaries of the representative volume element of the composite. Tensile loads in three axes and biaxial loads in x-y directions have been applied at different Fibre Volume Fractions (FVFs). A simple damage model was implemented via an Abaqus user material (UMAT) subroutine. Existing tools for homogenization were also used, including voxel mesh generation from TexGen as well as Abaqus Micromechanics plugin. Linear relations between homogenised elastic properties and the FVFs are given. The FE models of composite exhibited balanced behaviour with respect to warp and weft directions in terms of both stiffness and strength.

Keywords: 3D woven composite, meso-scale finite element modelling, homogenisation of elastic material properties, Abaqus Python scripting.

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Authors: Kiran Kumar K, Ramesh Babu Bejjam, Atul Najan

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A thermosyphon system is a heat transfer loop which operates on the basis of gravity and buoyancy forces. It guarantees a good reliability and low maintenance cost as it does not involve any mechanical pump. Therefore, it can be used in many industrial applications such as refrigeration and air conditioning, electronic cooling, nuclear reactors, geothermal heat extraction, etc. But flow instabilities and loop configuration are the major problems in this system. Several previous researchers studied that stabilities can be suppressed by using nanofluids as loop fluid. In the present study a rectangular thermosyphon loop with end heat exchangers are considered for the study. This configuration is more appropriate for many practical applications such as solar water heater, geothermal heat extraction, etc. In the present work, steady-state analysis is carried out on thermosyphon loop with parallel flow coaxial heat exchangers at heat source and heat sink. In this loop nanofluid is considered as the loop fluid and water is considered as the external fluid in both hot and cold heat exchangers. For this analysis onedimensional homogeneous model is developed. In this model, conservation equations like conservation of mass, momentum, energy are discretized using finite difference method. A computer code is written in MATLAB to simulate the flow in thermosyphon loop. A comparison in terms of heat transfer is made between water and nanofluid as working fluids in the loop.

Keywords: Heat exchanger, Heat transfer, Nanofluid, Thermosyphon loop.

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Authors: R. Rishma Rodrigo, R. Radhika, M. Vanitha Lakshmi

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Numerous signal processing based speech enhancement systems have been proposed to improve intelligibility in the presence of noise. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A method is presented for recording high-frequency speech components into a low-frequency region, to increase audibility for hearing loss listeners. The purpose of the paper is to enhance the formant of the speech based on the Kaiser window. The pitch and formant of the signal is based on the auto correlation, zero crossing and magnitude difference function. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain. A MATLAB software’s are used for the implementation of the system with low complexity is developed.

Keywords: Formant estimation, formant enhancement, pitch detection, speech analysis.

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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: Miguel Angel Garcia-Ruiz, Pedro Cesar Santana-Mancilla, Laura Sanely Gaytan-Lugo

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This paper describes the design and application of a short in-class project conducted in Algoma University’s Human-Computer Interaction (HCI) course taught at the Bachelor of Computer Science. The project was based on the Maker Movement (people using and reusing electronic components and everyday materials to tinker with technology and make interactive applications), where students applied low-cost and easy-to-use electronic components, the Arduino Uno microcontroller board, software tools, and everyday objects. Students collaborated in small teams by completing hands-on activities with them, making an interactive walking cane for blind people. At the end of the course, students filled out a Technology Acceptance Model version 2 (TAM2) questionnaire where they evaluated microcontroller boards’ applications in HCI classes. We also asked them about applying the Maker Movement in HCI classes. Results showed overall students’ positive opinions and response about using microcontroller boards in HCI classes. We strongly suggest that every HCI course should include practical activities related to tinkering with technology such as applying microcontroller boards, where students actively and constructively participate in teams for achieving learning objectives.

Keywords: Maker movement, microcontrollers, learning, projects, course, technology acceptance.

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Authors: Christian Mayr, Holger Eisenreich, Stephan Henker, René Schüffny

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Image convolution similar to the receptive fields found in mammalian visual pathways has long been used in conventional image processing in the form of Gabor masks. However, no VLSI implementation of parallel, multi-layered pulsed processing has been brought forward which would emulate this property. We present a technical realization of such a pulsed image processing scheme. The discussed IC also serves as a general testbed for VLSI-based pulsed information processing, which is of interest especially with regard to the robustness of representing an analog signal in the phase or duration of a pulsed, quasi-digital signal, as well as the possibility of direct digital manipulation of such an analog signal. The network connectivity and processing properties are reconfigurable so as to allow adaptation to various processing tasks.

Keywords: Neural image processing, pulse computation application, pulsed Gabor convolution, VLSI pulse routing.

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Authors: Javed Parvez, Mushtaq Ahmad Peer

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Mobile Ad hoc networks (MANETs) are collections of wireless mobile nodes dynamically reconfiguring and collectively forming a temporary network. These types of networks assume existence of no fixed infrastructure and are often useful in battle-field tactical operations or emergency search-and-rescue type of operations where fixed infrastructure is neither feasible nor practical. They also find use in ad hoc conferences, campus networks and commercial recreational applications carrying multimedia traffic. All of the above applications of MANETs require guaranteed levels of performance as experienced by the end-user. This paper focuses on key challenges in provisioning predetermined levels of such Quality of Service (QoS). It also identifies functional areas where QoS models are currently defined and used. Evolving functional areas where performance and QoS provisioning may be applied are also identified and some suggestions are provided for further research in this area. Although each of the above functional areas have been discussed separately in recent research studies, since these QoS functional areas are highly correlated and interdependent, a comprehensive and comparative analysis of these areas and their interrelationships is desired. In this paper we have attempted to provide such an overview.

Keywords: Bandwidth Reservation, Congestion, DynamicNetwork Topology, End-to-End Delay, Flexible QoS Model forMANET(FQMM), Hidden Terminal, Mobile AdhocNetwork(MANET), Packet Jitter, Queuing, Quality-of-Service(QoS), Relative Bandwidth Service Differentiation(RBSD), Resource ReSerVation Protocol (RSVP).

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Authors: Vojtěch Gybas, Libor Klubal, Kateřina Kostolányová

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Nowadays, mobile touch technologies, such as tablets, are an integral part of teaching and learning in many special elementary schools. Many special education teachers tend to choose an iPad tablet with iOS. The reason is simple; the iPad has a function for pupils with special educational needs. If we decide to use tablets in teaching, in general, first we should try to stimulate the cognitive abilities of the pupil at the highest level, while holding the pupil’s attention on the task, when working with the device. This paper will describe how student attention can be increased by eliminating the working environment of selected applications, while using iPads with pupils in a special elementary school. Assisted function approach is highly effective at eliminating unwanted touching by a pupil when working on the desktop iPad, thus actively increasing the pupil´s attention while working on specific educational applications. During the various stages of the action, the research was conducted via data collection and interpretation. After a phase of gaining results and ideas for practice and actions, we carried out the check measurement, this time using the tool-assisted approach. In both cases, the pupils worked in the Math Board application and the resulting differences were evident.

Keywords: Special elementary school, mobile touch device, iPad, attention, math board.

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Authors: V. Kabeer, N.K.Narayanan

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This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.

Keywords: Face recognition, Image analysis, Wavelet feature extraction, Pattern recognition, Classifier algorithms

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Authors: Michaela Skulinova, Wanping Zheng, Yan-Ru Hu, Yvan Soucy

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Space exploration is a highly visible endeavour of humankind to seek profound answers to questions about the origins of our solar system, whether life exists beyond Earth, and how we could live on other worlds. Different platforms have been utilized in planetary exploration missions, such as orbiters, landers, rovers, and penetrators. Having low mass, good mechanical contact with the surface, ability to acquire high quality scientific subsurface data, and ability to be deployed in areas that may not be conducive to landers or rovers, Penetrators provide an alternative and complimentary solution that makes possible scientific exploration of hardly accessible sites (icy areas, gully sites, highlands etc.). The Canadian Space Agency (CSA) has put space exploration as one of the pillars of its space program, and established ExCo program to prepare Canada for future international planetary exploration. ExCo sets surface mobility as its focus and priority, and invests mainly in the development of rovers because of Canada's niche space robotics technology. Meanwhile, CSA is also investigating how micro-penetrators can help Canada to fulfill its scientific objectives for planetary exploration. This paper presents a review of the micro-penetrator technologies, past missions, and lessons learned. It gives a detailed analysis of the technical challenges of micro-penetrators, such as high impact survivability, high precision guidance navigation and control, thermal protection, communications, and etc. Then, a Canadian perspective of a possible micro-penetrator mission is given, including Canadian scientific objectives and priorities, potential instruments, and flight opportunities.

Keywords: micro-penetrator, CSA, planetary exploration

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Authors: Fl. Loury, P. Sablonière

Abstract:

In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.

Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.

Keywords: Molten Salt Storage System, Concentrated Solar Tower Power Plant, Robust Stochastic Model Predictive Control.

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Authors: C. Ardil

Abstract:

Fighter aircraft selection is one of the most critical strategies for defense multiple criteria decision-making analysis to increase the decisive power of air defense and its superior power in the defense strategy. Vague set theory is an adequate approach for modeling vagueness, uncertainty, and imprecision in decision-making problems. This study integrates vague set theory and the technique for order of preference by similarity to ideal solution (TOPSIS) to support fighter aircraft selection. The proposed method is applied in the selection of fighter aircraft for the Air Force. In the proposed approach, the ratings of alternatives and the importance weights of criteria for fighter aircraft selection are represented by the vague set theory. Finally, an illustrative example for fighter aircraft selection is given to demonstrate the applicability and effectiveness of the proposed approach. The fighter aircraft candidates were selected under six criteria including costability, payloadability, maneuverability, speedability, stealthility, and survivability. Analysis results show that the best fighter aircraft is selected with the highest closeness coefficient value. The proposed method can also be applied to solve other multiple criteria decision analysis problems. 

Keywords: fighter aircraft selection, vague set theory, fuzzy set theory, neutrosophic set theory, multiple criteria decision making analysis, MCDMA, TOPSIS

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Authors: Hilal A. Abdelwali, Elsayed E.M. Ellaimony, Ahmad E.M. Murad, Jasem M.S. Al-Rajhi

Abstract:

Due to the excess of a vehicle operation through its life, some elements may face failure and deteriorate with time. This leads us to carry out maintenance, repair, tune up or full overhaul. After a certain period, the vehicle elements deteriorations increase with time which causes a very high increase of doing the maintenance operations and their costs. However, the logic decision at this point is to replace the current vehicle by a new one with minimum failure and maximum income. The importance of studying vehicle replacement problems come from the increase of stopping days due to many deteriorations in the vehicle parts. These deteriorations increase year after year causing an increase of operating costs and decrease the vehicle income. Vehicle replacement aims to determine the optimum time to keep, maintain, overhaul, renew and replace vehicles. This leads to an improvement in vehicle income, total operating costs, maintenance cost, fuel and oil costs, ton-kilometers, vehicle and engine performance, vehicle noise, vibration, and pollution. The aim of this paper is to find the optimum replacement policies of Kuwait Passenger Transport Company (KPTCP) fleet of busses. The objective of these policies is to maximize the busses pure profits. The dynamic programming (D.P.) technique is used to generate the busses optimal replacement policies

Keywords: Replacement Problem, Automotive Replacement, Dynamic Programming, Equipment Replacement, K.P.T.C.

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Authors: Seddeq E. Ghrare, Salahaddin M. Shreef

Abstract:

Medical image modalities such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), X-ray are adapted to diagnose disease. These modalities provide flexible means of reviewing anatomical cross-sections and physiological state in different parts of the human body. The raw medical images have a huge file size and need large storage requirements. So it should be such a way to reduce the size of those image files to be valid for telemedicine applications. Thus the image compression is a key factor to reduce the bit rate for transmission or storage while maintaining an acceptable reproduction quality, but it is natural to rise the question of how much an image can be compressed and still preserve sufficient information for a given clinical application. Many techniques for achieving data compression have been introduced. In this study, three different MRI modalities which are Brain, Spine and Knee have been compressed and reconstructed using wavelet transform. Subjective and objective evaluation has been done to investigate the clinical information quality of the compressed images. For the objective evaluation, the results show that the PSNR which indicates the quality of the reconstructed image is ranging from (21.95 dB to 30.80 dB, 27.25 dB to 35.75 dB, and 26.93 dB to 34.93 dB) for Brain, Spine, and Knee respectively. For the subjective evaluation test, the results show that the compression ratio of 40:1 was acceptable for brain image, whereas for spine and knee images 50:1 was acceptable.

Keywords: Medical Image, Magnetic Resonance Imaging, Image Compression, Discrete Wavelet Transform, Telemedicine.

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Authors: Ong Sing Goh, C. Ardil, Chun Che Fung, Kok Wai Wong, Arnold Depickere

Abstract:

In this paper, we proposed a new framework to incorporate an intelligent agent software robot into a crisis communication portal (CCNet) in order to send alert news to subscribed users via email and other mobile services such as Short Message Service (SMS), Multimedia Messaging Service (MMS) and General Packet Radio Services (GPRS). The content on the mobile services can be delivered either through mobile phone or Personal Digital Assistance (PDA). This research has shown that with our proposed framework, the embodied conversation agents system can handle questions intelligently with our multilayer architecture. At the same time, the extended framework can take care of delivery content through a more humanoid interface on mobile devices.

Keywords: Crisis Communication Network (CCNet), EmbodiedConversational Agents (ECAs), Mobile Services, ArtificialIntelligence Neural-network Identity (AINI)

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