Search results for: Artificial communication

Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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Authors: Sepehr M.H.Jamarani, M.H.Moradi, H.Behnam, G.A.Rezai Rad

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This paper presents an approach for early breast cancer diagnostic by employing combination of artificial neural networks (ANN) and multiwaveletpacket based subband image decomposition. The microcalcifications correspond to high-frequency components of the image spectrum, detection of microcalcifications is achieved by decomposing the mammograms into different frequency subbands,, reconstructing the mammograms from the subbands containing only high frequencies. For this approach we employed different types of multiwaveletpacket. We used the result as an input of neural network for classification. The proposed methodology is tested using the Nijmegen and the Mammographic Image Analysis Society (MIAS) mammographic databases and images collected from local hospitals. Results are presented as the receiver operating characteristic (ROC) performance and are quantified by the area under the ROC curve.

Keywords: Breast cancer, neural networks, diagnosis, multiwavelet packet, microcalcification.

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Authors: Qin Ding, Jim Gasvoda

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Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.

Keywords: Clustering, data mining, genetic algorithm, image data.

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Authors: E. G. Bautista, J. M. Reyes, O. Bautista, J. C. Arcos

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In this work, we analyze the deformation of surface waves in shallow flows conditions, propagating in a channel of slowly varying cross-section. Based on a singular perturbation technique, the main purpose is to predict the motion of waves by using a dimensionless formulation of the governing equations, considering that the longitudinal variation of the transversal section obey a power-law distribution. We show that the spatial distribution of the waves in the varying cross-section is a function of a kinematic parameter,κ , and two geometrical parameters εh and w ε . The above spatial behavior of the surface elevation is modeled by an ordinary differential equation. The use of single formulas to model the varying cross sections or transitions considered in this work can be a useful approximation to natural or artificial geometrical configurations.

Keywords: Surface waves, Asymptotic solution, Power law function, Non-dispersive waves.

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Authors: Mohie Eldin Mohamed Afifiy Elmashad

Abstract:

Desert regions around the Nile valley in Upper Egypt contain great extent of swelling soil. Many different comment procedures of treatment of the swelling soils for construction such as pre-swelling, load balance OR soil replacement. One of the measure factors which affect the level of the aggressiveness of the swelling soil is the direction of the infiltration water directions within the swelling soils. In this paper a physical model was installed to measure the effect of water on the swelling soil with replacement using fatty acid distillation residuals (FADR) mixed with sand as thick sand-FADR mixture to prevent the water pathway arrive to the swelling soil. Testing program have been conducted on different artificial samples with different sand to FADR contents ratios (4%, 6%, and 9%) to get the optimum value fulfilling the impermeable replacement. The tests show that a FADR content of 9% is sufficient to produce impermeable replacement.

Keywords: Swelling soil, FADR, soil improvement, permeability

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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: K.C. Deshmukh, P.G. Khot, Nikhil

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In the present communication, we have proposed some new generalized measure of fuzzy entropy based upon real parameters, discussed their and desirable properties, and presented these measures graphically. An important property, that is, monotonicity of the proposed measures has also been studied.

Keywords: Fuzzy numbers, Fuzzy entropy, Characteristicfunction, Crisp set, Monotonicity.

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Authors: E. M. Vieira, C. S. Vieira, L. P. Bonifácio, L. M. de Oliveira Ciabati, A. C. A. Franzon, F. S. Zaratini, J. A. C. Sanchez, M. S. Andrade, J. P. Dias de Souza

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The quality of prenatal care is key to reduce maternal morbidity and mortality. Communication between the health service and users can stimulate prevention and care. M-health has been an important and low cost strategy to health education. The PRENACEL programme (prenatal in the cell phone) was developed. It consists of a programme of information via SMS from the 20^th week of pregnancy up to 12^th week after delivery. Messages were about prenatal care, birth, contraception and breastfeeding. Communication of the pregnant woman asking questions about their health was possible. The objective of this study was to evaluate the implementation of PRENACEL as a useful complement to the standard prenatal care. Twenty health clinics were selected and randomized by cluster, 10 as the intervention group and 10 as the control group. In the intervention group, women and their partner were invited to participate. The control group received the standard prenatal care. All women were interviewed in the immediate post-partum and in the 12^th and 24^th week post-partum. Most women were married, had more than 8 years of schooling and visit the clinic more than 6 times during prenatal care. The intervention group presented lowest percentage of higher economic participants (5.6%), less single mothers and no drug user. It also presented more prenatal care visits than the control group and it was less likely to present Severe Acute Maternal Mortality when compared to control group as well as higher percentage of partners (75.4%) was present at the birth compared to control group. Although the study is still being carried out, preliminary data are showing positive results of the compliance of women to prenatal care.

Keywords: Cellphone, health technology, prenatal care, prevention.

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Authors: Rauno Pääkkönen, Fabriziomaria Gobba, Leena Korpinen

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The objective of the study is to assess the implementation of LED lighting into forest machine work in the dark. In addition, the paper includes a wide variety of important and relevant safety and health parameters. In modern, computerized work in the cab of forest machines, artificial illumination is a demanding task when performing duties, such as the visual inspections of wood and computer calculations. We interviewed entrepreneurs and gathered the following as the most pertinent themes: (1) safety, (2) practical problems, and (3) work with LED lighting. The most important comments were in regards to the practical problems of LED lighting. We found indications of technical problems in implementing LED lighting, like snow and dirt on the surfaces of lamps that dim the emission of light. Moreover, service work in the dark forest is dangerous and increases the risks of on-site accidents. We also concluded that the amount of blue light to the eyes should be assessed, especially, when the drivers are working in a semi-dark cab.

Keywords: Forest machines, health, LED, safety.

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Authors: Huy Q. Tran, Bac V. Nguyen, Choonghyun Kang, Jungwon Huh

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Jumbo container crane is an important part of port structures that needs to be designed properly, even when the port locates in low seismicity zone such as in Korea. In this paper, 30 artificial ground motions derived from the elastic response spectra of Korean Building Code (2005) are used for time history analysis. It is found that the uplift might not occur in this analysis when the crane locates in the low seismic zone. Therefore, a selection of a pinned or a gap element for base supporting has not much effect on the determination of the total base shear. The relationships between the total base shear and peak ground acceleration (PGA) and the relationships between the portal drift and the PGA are proposed in this study.

Keywords: Jumbo container crane, portal drift, time history analysis, total base shear.

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Authors: Nermine Ahmed Hendy, Hania Farag

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Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time

Keywords: Classification, emotion recognition, features extraction, feature selection, neural network

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Authors: Saad Al-Baddai, Karema Al-Subari, Elmar Lang, Bernd Ludwig

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Empirical mode decomposition (EMD), a new data-driven of time-series decomposition, has the advantage of supposing that a time series is non-linear or non-stationary, as is implicitly achieved in Fourier decomposition. However, the EMD suffers of mode mixing problem in some cases. The aim of this paper is to present a solution for a common type of signals causing of EMD mode mixing problem, in case a signal suffers of an intermittency. By an artificial example, the solution shows superior performance in terms of cope EMD mode mixing problem comparing with the conventional EMD and Ensemble Empirical Mode decomposition (EEMD). Furthermore, the over-sifting problem is also completely avoided; and computation load is reduced roughly six times compared with EEMD, an ensemble number of 50.

Keywords: Empirical mode decomposition, mode mixing, sifting process, over-sifting.

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Authors: Rajkumar Verma, Bhu Dev Sharma

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In the present communication, the existing measures of fuzzy entropy are reviewed. A generalized parametric exponential fuzzy entropy is defined.Our study of the four essential and some other properties of the proposed measure, clearly establishes the validity of the measure as an entropy.

Keywords: fuzzy sets, fuzzy entropy, exponential entropy, exponential fuzzy entropy.

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Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca De Marchi

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This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes a larger monitored area available. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary, the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: Data compression, ultrasonic communication, guided waves, FEM analysis.

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Authors: S. H. J. Liu

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This paper aims to explore the role of peer Corrective Feedback (CF) in improving written productions by English-as-a- foreign-language (EFL) learners who work together via Wikispaces. It attempted to determine the effect of peer CF on form accuracy in English, such as grammar and lexis. Thirty-four EFL learners at the tertiary level were randomly assigned into the experimental (with peer feedback) or the control (without peer feedback) group; each group was subdivided into small groups of two or three. This resulted in six and seven small groups in the experimental and control groups, respectively. In the experimental group, each learner played a role as an assessor (providing feedback to others), as well as an assessee (receiving feedback from others). Each participant was asked to compose his/her written work and revise it based on the feedback. In the control group, on the other hand, learners neither provided nor received feedback but composed and revised their written work on their own. Data collected from learners’ compositions and post-task interviews were analyzed and reported in this study. Following the completeness of three writing tasks, 10 participants were selected and interviewed individually regarding their perception of collaborative learning in the Computer-Mediated Communication (CMC) environment. Language aspects to be analyzed included lexis (e.g., appropriate use of words), verb tenses (e.g., present and past simple), prepositions (e.g., in, on, and between), nouns, and articles (e.g., a/an). Feedback types consisted of CF, affective, suggestive, and didactic. Frequencies of feedback types and the accuracy of the language aspects were calculated. The results first suggested that accurate items were found more in the experimental group than in the control group. Such results entail that those who worked collaboratively outperformed those who worked non-collaboratively on the accuracy of linguistic aspects. Furthermore, the first type of CF (e.g., corrections directly related to linguistic errors) was found to be the most frequently employed type, whereas affective and didactic were the least used by the experimental group. The results further indicated that most participants perceived that peer CF was helpful in improving the language accuracy, and they demonstrated a favorable attitude toward working with others in the CMC environment. Moreover, some participants stated that when they provided feedback to their peers, they tended to pay attention to linguistic errors in their peers’ work but overlook their own errors (e.g., past simple tense) when writing. Finally, L2 or FL teachers or practitioners are encouraged to employ CMC technologies to train their students to give each other feedback in writing to improve the accuracy of the language and to motivate them to attend to the language system.

Keywords: Peer corrective feedback, computer-mediated communication, second or foreign language learning, Wikispaces.

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Authors: Javed Ahmed, M. N. Jafri, J. Ahmad, Muhammad I. Khan

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Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.

Keywords: Image processing, machine vision, neural networks, real-time object tracking.

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Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

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More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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Authors: André Smith, Amr Abdel-Dayem

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The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: Colour data, local stereo matching, stereo correspondence, disparity map.

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems do not scale well on cluster containing multiple Central Processing Units (multi-CPUs cluster) or cluster containing multiple Graphics Processing Units (multi-GPUs cluster). For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration, instead of two for standard CG (Conjugate Gradient). The standard and pipelined CG methods need the vector entries generated by current GPU and other GPUs for matrix-vector product. So the communication between GPUs becomes a major performance bottleneck on miltiGPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: Conjugate Gradient, GPU, parallel programming, pipelined algorithm.

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Authors: Masoud Madadelahi, Amir Shamloo, Seyedeh Sara Salehi

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Previously, some materials like solid metals and their alloys have been used as implants in human’s body. In order to amend fixation of these artificial hard human tissues, some porous structures have been introduced. In this way, tissues in vicinity of the porous structure can be attached more easily to the inserted implant. In particular, the porous bone scaffolds are useful since they can deliver important biomolecules like growth factors and proteins. This study focuses on the properties of the degradable porous hard tissues using a three-dimensional numerical Finite Element Method (FEM). The most important studied properties of these structures are diffusivity flux and concentration of different species like glucose, oxygen, and lactate. The process of cells migration into the scaffold is considered as a diffusion process, and related parameters are studied for different values of production/consumption rates.

Keywords: Bone scaffolds, diffusivity, numerical simulation, tissue engineering.

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Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade

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The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.

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Authors: K. Ranjani, M. Raja, B. Anitha

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In this paper, ANN controller for maximum power point tracking of photovoltaic (PV) systems is proposed and PV modeling is discussed. Maximum power point tracking (MPPT) methods are used to maximize the PV array output power by tracking continuously the maximum power point. ANN controller with hill-climbing algorithm offers fast and accurate converging to the maximum operating point during steady-state and varying weather conditions compared to conventional hill-climbing. The proposed algorithm gives a good maximum power operation of the PV system. Simulation results obtained are presented and compared with the conventional hill-climbing algorithm. Simulation results show the effectiveness of the proposed technique.

Keywords: Artificial neural network (ANN), hill-climbing, maximum power-point tracking (MPPT), photovoltaic.

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Authors: Hooman Jafarabadi

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In this paper application of artificial intelligence for baby and children caring is studied. Then a new idea for injury prevention and safety announcement is presented by using digital image processing. The paper presents the structure of the proposed system. The system determines the possibility of the dangers for children and babies in yards, gardens and swimming pools or etc. In the presented idea, multi camera System is used and receiver videos are processed to find the hazardous areas then the entrance of children and babies in the determined hazardous areas are analyzed. In this condition the system does the programmed action capture, produce alarm or tone or send message.

Keywords: Baby and children Care and Nursing, Intelligent Control Systems for Nursing, Electronic Care and Nursing, Dangers and safety for children and babies, Motion detection, Expert danger alarm systems.

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Authors: Andreas Theissler, Ian Dear

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The one-class support vector machine “support vector data description” (SVDD) is an ideal approach for anomaly or outlier detection. However, for the applicability of SVDD in real-world applications, the ease of use is crucial. The results of SVDD are massively determined by the choice of the regularisation parameter C and the kernel parameter  of the widely used RBF kernel. While for two-class SVMs the parameters can be tuned using cross-validation based on the confusion matrix, for a one-class SVM this is not possible, because only true positives and false negatives can occur during training. This paper proposes an approach to find the optimal set of parameters for SVDD solely based on a training set from one class and without any user parameterisation. Results on artificial and real data sets are presented, underpinning the usefulness of the approach.

Keywords: Support vector data description, anomaly detection, one-class classification, parameter tuning.

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Authors: V. K. Banga, R. Kumar, Y. Singh

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In this paper, we present optimal control for movement and trajectory planning for four degrees-of-freedom robot using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs) for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like; Movement, Friction and Settling Time in robotic arm movement have been compensated using Fuzzy logic and Genetic Algorithms. The development of a fuzzy genetic optimization algorithm is presented and discussed. The result are compared only GA and Fuzzy GA. This paper describes genetic algorithms, which is designed to optimize robot movement and trajectory. Though the model represents is a general model for redundant structures and could represent any n-link structures. The result is a complete trajectory planning with Fuzzy logic and Genetic algorithms demonstrating the flexibility of this technique of artificial intelligence.

Keywords: Inverse kinematics, Genetic algorithms (GAs), Fuzzy logic (FL), Trajectory planning.

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Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

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In this paper, a novel associative memory model will be proposed and applied to memory retrievals based on the conventional continuous time model. The conventional model presents memory capacity is very low and retrieval process easily converges to an equilibrium state which is very different from the stored patterns. Genetic Algorithms is well-known with the capability of global optimal search escaping local optimum on progress to reach a global optimum. Based on the well-known idea of Genetic Algorithms, this work proposes a heuristic rule to make a mutation when the state of the network is trapped in a spurious memory. The proposal heuristic associative memory show the stored capacity does not depend on the number of stored patterns and the retrieval ability is up to ~ 1.

Keywords: Artificial Intelligent, Soft Computing, NeuralNetworks, Genetic Algorithms, Hopfield Neural Networks, andAssociative Memories.

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Authors: Leila Mohammadi

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This paper presents the impact of persuasive communication implemented by fertility clinics websites, and how this information influences women at their decision-making for undertaking this procedure. The influential factors for women decisions to do social egg freezing (SEF) are analyzed from a framing theory perspective, with a specific focus on the impact of persuasive information on women’s decision making. This study follows a quantitative approach. A two-phase survey has been conducted to examine the interest rate to undertake SEF. In the first phase, a questionnaire was available during a month (May 2015) to women to answer whether or not they knew enough information of this process, with a total of 230 answers. The second phase took place in the two last weeks of July 2015. All the respondents were invited to a seminars called ‘All about egg freezing’ and afretwards they were requested to answer the second questionnaire. After the seminar, in which they were given an extensive amount of information about egg freezing, a total of 115 women replied the questionnaire. The collected data during this process were analyzed using descriptive statistics. Most of the respondents changed their opinion in the second questionaire which was after receiving information. Although in the first questionnaire their self-evaluation of having knowledge about this process and the implemented technologies was very high, they realized that they still need to access more information from different sources in order to be able to make a decision. The study reached the conclusion that persuasive and framed information by clinics would affect the decisions of these women. Despite the reasons women have to do egg freezing and their motivations behind it, providing people necessary information and unprejudiced data about this process (such as its positive and negative aspects, requirements, suppositions, possibilities and consequences) would help them to make a more precise and reasonable decision about what they are buying.

Keywords: Decision making, fertility clinics, framing theory, persuasive information, social egg freezing.

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Authors: Hanh Thi My Nguyen

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The purpose of this research is to examine the experiences of parents of children who are deaf or hard of hearing in supporting their children to access education in Vietnam. Parents play a crucial role in supporting their children to gain full access to education. It was widely reported that parents of those children confronted a range of problems to support their children to access education. To author’s best knowledge, there has been a lack of research exploring the experiences of those parents in literature. This research examines factors affecting those parents in supporting their children to access education. To conduct the study, qualitative approach using a phenomenological research design was chosen to explore the central phenomena. Ten parents of children who were diagnosed as deaf or hard of hearing and aged 6-9 years were recruited through the support of the Association of Parents of Children with Hearing Impairment. Participants were interviewed via telephone with a mix of open and closed questions; interviews were audio recorded, transcribed and thematically analysed. The research results show that there are nine main factors that affected the parents in this study in making decisions relating to education for their children including: lack of information resources, perspectives of those parents on communication approaches, the families’ financial capacity, the psychological impact on the participants after their children’ diagnosis, the attitude of family members, attitude of school administrators, lack of local schools and qualified teachers, and current education system for the deaf in Vietnam. Apart from those factors, the lack of knowledge of the participants’ partners about deaf education and the partners’ employment are barriers to educational access and successful communication with their child.

Keywords: Access to education, deaf, hard of hearing, parents experience.

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Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

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In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: Inverse problems, multi-component solutions, neural networks, Raman spectroscopy.

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Authors: Shahana T. K., Babita R. Jose, K. Poulose Jacob, Sreela Sasi

Abstract:

The modern telecommunication industry demands higher capacity networks with high data rate. Orthogonal frequency division multiplexing (OFDM) is a promising technique for high data rate wireless communications at reasonable complexity in wireless channels. OFDM has been adopted for many types of wireless systems like wireless local area networks such as IEEE 802.11a, and digital audio/video broadcasting (DAB/DVB). The proposed research focuses on a concatenated coding scheme that improve the performance of OFDM based wireless communications. It uses a Redundant Residue Number System (RRNS) code as the outer code and a convolutional code as the inner code. Here, a direct conversion of analog signal to residue domain is done to reduce the conversion complexity using sigma-delta based parallel analog-to-residue converter. The bit error rate (BER) performances of the proposed system under different channel conditions are investigated. These include the effect of additive white Gaussian noise (AWGN), multipath delay spread, peak power clipping and frame start synchronization error. The simulation results show that the proposed RRNS-Convolutional concatenated coding (RCCC) scheme provides significant improvement in the system performance by exploiting the inherent properties of RRNS.

Keywords: Analog-to-residue converter, Concatenated codes, OFDM, Redundant Residue Number System, Sigma-delta modulator, Wireless communication

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