Search results for: real time data analysis

Authors: M. Y. Misro, A. Ramli, J. M. Ali

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Bezier curves have useful properties for path generation problem, for instance, it can generate the reference trajectory for vehicles to satisfy the path constraints. Both algorithms join cubic Bezier curve segment smoothly to generate the path. Some of the useful properties of Bezier are curvature. In mathematics, curvature is the amount by which a geometric object deviates from being flat, or straight in the case of a line. Another extrinsic example of curvature is a circle, where the curvature is equal to the reciprocal of its radius at any point on the circle. The smaller the radius, the higher the curvature thus the vehicle needs to bend sharply. In this study, we use Bezier curve to fit highway-like curve. We use different approach to find the best approximation for the curve so that it will resembles highway-like curve. We compute curvature value by analytical differentiation of the Bezier Curve. We will then compute the maximum speed for driving using the curvature information obtained. Our research works on some assumptions; first, the Bezier curve estimates the real shape of the curve which can be verified visually. Even though, fitting process of Bezier curve does not interpolate exactly on the curve of interest, we believe that the estimation of speed are acceptable. We verified our result with the manual calculation of the curvature from the map.

Keywords: Speed estimation, path constraints, reference trajectory, Bezier curve.

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation.

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Authors: Vladimir Korovkin, Albert Park, Evgeny Kaganer

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Digital divide, the gap in the access to the world of digital technologies and the socio-economic opportunities that they create is an important phenomenon of the XXI century. This gap may exist between countries, regions within a country or socio-demographic groups, creating the classes of “digital have and have nots”. While the 1st-level divide (the difference in opportunities to access the digital networks) was demonstrated to diminish with time, the issues of 2nd level divide (the difference in skills and usage of digital systems) and 3rd level divide (the difference in effects obtained from digital technology) may grow. The paper offers a systemic review of literature on the measurement of the digital divide, noting the certain conceptual stagnation due to the lack of effective instruments that would capture the complex nature of the phenomenon. As a result, many important concepts do not receive the empiric exploration they deserve. As a solution the paper suggests a composite Digital Life Index, that studies separately the digital supply and demand across seven independent dimensions providing for 14 subindices. The Index is based on Internet-borne data, a distinction from traditional research approaches that rely on official statistics or surveys. The application of the model to the study of the digital divide between Russian regions and between cities in China have brought promising results. The paper advances the existing methodological literature on the 2nd level digital divide and can also inform practical decision-making regarding the strategies of national and regional digital development.

Keywords: Digital transformation, second-level digital divide, composite index, digital policy.

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Authors: R. Yeghnem, L. Boulefrakh, S. A. Meftah, A. Tounsi, E. A. Adda Bedia

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In this study, the time-dependent behavior of damaged reinforced concrete shear wall structures strengthened with composite plates having variable fibers spacing was investigated to analyze their seismic response. In the analytical formulation, the adherent and the adhesive layers are all modeled as shear walls, using the mixed Finite Element Method (FEM). The anisotropic damage model is adopted to describe the damage extent of the Reinforced Concrete shear walls. The phenomenon of creep and shrinkage of concrete has been determined by Eurocode 2. Large earthquakes recorded in Algeria (El-Asnam and Boumerdes) have been tested to demonstrate the accuracy of the proposed method. Numerical results are obtained for non-uniform distributions of carbon fibers in epoxy matrices. The effects of damage extent and the delay mechanism creep and shrinkage of concrete are highlighted. Prospects are being studied.

Keywords: RC shear wall structures, composite plates, creep and shrinkage, damaged reinforced concrete structures, finite element method.

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Authors: Ayman A. El-Saleh, Mahamod Ismail, Mohd. A. M. Ali, Ahmed N. H. Alnuaimy

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The dynamic spectrum allocation solutions such as cognitive radio networks have been proposed as a key technology to exploit the frequency segments that are spectrally underutilized. Cognitive radio users work as secondary users who need to constantly and rapidly sense the presence of primary users or licensees to utilize their frequency bands if they are inactive. Short sensing cycles should be run by the secondary users to achieve higher throughput rates as well as to provide low level of interference to the primary users by immediately vacating their channels once they have been detected. In this paper, the throughput-sensing time relationship in local and cooperative spectrum sensing has been investigated under two distinct scenarios, namely, constant primary user protection (CPUP) and constant secondary user spectrum usability (CSUSU) scenarios. The simulation results show that the design of sensing slot duration is very critical and depends on the number of cooperating users under CPUP scenario whereas under CSUSU, cooperating more users has no effect if the sensing time used exceeds 5% of the total frame duration.

Keywords: Capacity, cognitive radio, optimization, spectrumsensing.

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Authors: L. Salhi, M. Talbi, A. Cherif

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This paper presents a new strategy of identification and classification of pathological voices using the hybrid method based on wavelet transform and neural networks. After speech acquisition from a patient, the speech signal is analysed in order to extract the acoustic parameters such as the pitch, the formants, Jitter, and shimmer. Obtained results will be compared to those normal and standard values thanks to a programmable database. Sounds are collected from normal people and patients, and then classified into two different categories. Speech data base is consists of several pathological and normal voices collected from the national hospital “Rabta-Tunis". Speech processing algorithm is conducted in a supervised mode for discrimination of normal and pathology voices and then for classification between neural and vocal pathologies (Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation results will be presented in function of the disease and will be compared with the clinical diagnosis in order to have an objective evaluation of the developed tool.

Keywords: Formants, Neural Networks, Pathological Voices, Pitch, Wavelet Transform.

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Authors: Martin Cermak, Stanislav Sysala

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In this paper we present the efficient parallel implementation of elastoplastic problems based on the TFETI (Total Finite Element Tearing and Interconnecting) domain decomposition method. This approach allow us to use parallel solution and compute this nonlinear problem on the supercomputers and decrease the solution time and compute problems with millions of DOFs. In our approach we consider an associated elastoplastic model with the von Mises plastic criterion and the combination of linear isotropic-kinematic hardening law. This model is discretized by the implicit Euler method in time and by the finite element method in space. We consider the system of nonlinear equations with a strongly semismooth and strongly monotone operator. The semismooth Newton method is applied to solve this nonlinear system. Corresponding linearized problems arising in the Newton iterations are solved in parallel by the above mentioned TFETI. The implementation of this problem is realized in our in-house MatSol packages developed in MatLab.

Keywords: Isotropic-kinematic hardening, TFETI, domain decomposition, parallel solution.

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Authors: S. P. Singh

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This paper measures technical and scale efficiencies of 40 Indian sugar companies for the period from 2004-05 to 2013-14. The efficiencies are estimated through input-oriented DEA models using one output variable—value of output (VOP) and five input variables—capital cost (CA), employee cost (EMP), raw material (RW), energy & fuel (E&F) and other manufacturing expenses (OME). The sugar companies are classified into integrated and non-integrated categories to know which one achieves higher level of efficiency. Sources of inefficiency in the industry are identified through decomposing the overall technical efficiency (TE) into pure technical efficiency (PTE) and scale efficiency (SE). The paper also estimates input-reduction targets for relatively inefficient companies and suggests measures to improve their efficiency level. The findings reveal that the TE does not evince any trend rather it shows fluctuations across years, largely due to erratic and cyclical pattern of sugar production. Further, technical inefficiency in the industry seems to be driven more by the managerial inefficiency than the scale inefficiency, which implies that TE can be improved through better conversion of inputs into output.

Keywords: Sugar industry, companies, technical efficiency, data envelopment analysis, targets.

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Authors: O. Mauroner, L. Le, S. Best

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Digital technologies offer many opportunities in the design and implementation of brand communication and advertising. Augmented reality (AR) is an innovative technology in marketing communication that focuses on the fact that virtual interaction with a product ad offers additional value to consumers. AR enables consumers to obtain (almost) real product experiences by the way of virtual information even before the purchase of a certain product. Aim of AR applications in relation with advertising is in-depth examination of product characteristics to enhance product knowledge as well as brand knowledge. Interactive design of advertising provides observers with an intense examination of a specific advertising message and therefore leads to better brand knowledge. The elaboration likelihood model and the central route to persuasion strongly support this argumentation. Nevertheless, AR in brand communication is still in an initial stage and therefore scientific findings about the impact of AR on information processing and brand attitude are rare. The aim of this paper is to empirically investigate the potential of AR applications in combination with traditional print advertising. To that effect an experimental design with different levels of interactivity is built to measure the impact of interactivity of an ad on different variables o advertising effectiveness.

Keywords: Advertising effectiveness, augmented reality, brand communication, brand recall, interactivity.

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Authors: Zhang Xiuping, Yang Guowu, Zheng Desheng

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Embedded hardware simulator is a valuable computeraided tool for embedded application development. This paper focuses on the ARM926EJ-S MMU, builds state transition models and formally verifies critical properties for the models. The state transition models include loading instruction model, reading data model, and writing data model. The properties of the models are described by CTL specification language, and they are verified in VIS. The results obtained in VIS demonstrate that the critical properties of MMU are satisfied in the state transition models. The correct models can be used to implement the MMU component in our simulator. In the end of this paper, the experimental results show that the MMU can successfully accomplish memory access requests from CPU.

Keywords: MMU, State transition, Model, Simulation.

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Authors: Sadaf Moeez, Madiha Khalid, Zoya Khalid, Sania Shaheen, Sumbul Khalid

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Background: Inter-individual variation in response to metformin, which has been considered as a first line therapy for T2DM treatment is considerable. In the current study, it was aimed to investigate the impact of two genetic variants Leu125Phe (rs77474263) and Gly64Asp (rs77630697) in gene SLC47A1 on the clinical efficacy of metformin in T2DM Pakistani patients. Methods: The study included 800 T2DM patients (400 metformin responders and 400 metformin non-responders) along with 400 ethnically matched healthy individuals. The genotypes were determined by allele-specific polymerase chain reaction. In-silico analysis was done to confirm the effect of the two SNPs on the structure of genes. Association was statistically determined using SPSS software. Results: Minor allele frequency for rs77474263 and rs77630697 was 0.13 and 0.12. For SLC47A1 rs77474263 the homozygotes of one mutant allele ‘T’ (CT) of rs77474263 variant were fewer in metformin responders than metformin non-responders (29.2% vs. 35.5 %). Likewise, the efficacy was further reduced (7.2% vs. 4.0 %) in homozygotes of two copies of ‘T’ allele (TT). Remarkably, T2DM cases with two copies of allele ‘C’ (CC) had 2.11 times more probability to respond towards metformin monotherapy. For SLC47A1 rs77630697 the homozygotes of one mutant allele ‘A’ (GA) of rs77630697 variant were fewer in metformin responders than metformin non-responders (33.5% vs. 43.0 %). Likewise, the efficacy was further reduced (8.5% vs. 4.5%) in homozygotes of two copies of ‘A’ allele (AA). Remarkably, T2DM cases with two copies of allele ‘G’ (GG) had 2.41 times more probability to respond towards metformin monotherapy. In-silico analysis revealed that these two variants affect the structure and stability of their corresponding proteins. Conclusion: The present data suggest that SLC47A1 Leu125Phe (rs77474263) and Gly64Asp (rs77630697) polymorphisms were associated with the therapeutic response of metformin in T2DM patients of Pakistan.

Keywords: Diabetes, T2DM, SLC47A1, Pakistan, polymorphism.

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Authors: Rafik Medjoudj, Rabah Medjoudj, D. Aissani

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The electrical substation components are often subject to degradation due to over-voltage or over-current, caused by a short circuit or a lightning. A particular interest is given to the circuit breaker, regarding the importance of its function and its dangerous failure. This component degrades gradually due to the use, and it is also subject to the shock process resulted from the stress of isolating the fault when a short circuit occurs in the system. In this paper, based on failure mechanisms developments, the wear out of the circuit breaker contacts is modeled. The aim of this work is to evaluate its reliability and consequently its residual lifetime. The shock process is based on two random variables such as: the arrival of shocks and their magnitudes. The arrival of shocks was modeled using homogeneous Poisson process (HPP). By simulation, the dates of short-circuit arrivals were generated accompanied with their magnitudes. The same principle of simulation is applied to the amount of cumulative wear out contacts. The objective reached is to find the formulation of the wear function depending on the number of solicitations of the circuit breaker.

Keywords: reliability, short-circuit, models of shocks.

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Authors: R. Uthayakumar, D. Easwaramoorthy

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This paper investigates the fractals generated by the dynamical system of intuitionistic fuzzy contractions in the intuitionistic fuzzy metric spaces by generalizing the Hutchinson-Barnsley theory. We prove some existence and uniqueness theorems of fractals in the standard intuitionistic fuzzy metric spaces by using the intuitionistic fuzzy Banach contraction theorem. In addition to that, we analyze some results on intuitionistic fuzzy fractals in the standard intuitionistic fuzzy metric spaces with respect to the Hausdorff intuitionistic fuzzy metrics.

Keywords: Fractal Analysis, Fixed Point, Contraction, Iterated Function System, Intuitionistic Fuzzy Metric Space.

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Authors: G. Hodaifa, J. A. Páez, C. Agabo, E. Ramos, J. C. Gutiérrez, A. Rosal

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Currently, continuous two-phase decanter process used for olive oil production is the more internationally widespread. The wastewaters generated from this industry (OMW) are a real environmental problem because of its high organic load. Among proposed treatments for these wastewaters, advanced oxidation technologies (Fenton, ozone, photoFenton, etc.) are the most favourable. The direct application of these processes is somewhat expensive. Therefore, the application of a previous stage based on a flocculation-sedimentation operation is of high importance. In this research five commercial flocculants (three cationic, and two anionic) have been used to achieve the separation of phases (liquid clarifiedsludge). For each flocculant, different concentrations (0-1000 mg/L) have been studied. In these experiments, sludge volume formed and the final water quality were determined. The final removal percentages of total phenols (11.3-25.1%), COD (5.6-20.4%), total carbon (2.3-26.5%), total organic carbon (1.50-23.8%), total nitrogen (1.45-24.8%), and turbidity (27.9-61.4%) were determined. The variation on electric conductivity reduction percentage (1-8%) was also determined. Finally, the best flocculants with highest removal percentages have been determined (QG2001 and Flocudex CS49).

Keywords: Flocculants, flocculation, olive oil mill wastewater, water quality.

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: Video surveillance, disentanglement, face detection.

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Authors: Tlou J. Ramabu

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Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.

Keywords: Blended learning, higher education, WhatsApp, programming, novices, lecturers.

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Authors: Daesung Moon, Woo-Yong Choi, Kiyoung Moon

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Fuzzy fingerprint vault is a recently developed cryptographic construct based on the polynomial reconstruction problem to secure critical data with the fingerprint data. However, the previous researches are not applicable to the fingerprint having a few minutiae since they use a fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use an adaptive degree of the polynomial considering the number of minutiae extracted from each user. Also, we apply multiple polynomials to avoid the possible degradation of the security of a simple solution(i.e., using a low-degree polynomial). Based on the experimental results, our method can make the possible attack difficult 2192 times more than using a low-degree polynomial as well as verify the users having a few minutiae.

Keywords: Fuzzy vault, fingerprint recognition multiple polynomials.

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Authors: Padmakumar S., Vivek Agarwal, Kallol Roy

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A new observer based fault detection and diagnosis scheme for predicting induction motors- faults is proposed in this paper. Prediction of incipient faults, using different variants of Kalman filter and their relative performance are evaluated. Only soft faults are considered for this work. The data generation, filter convergence issues, hypothesis testing and residue estimates are addressed. Simulink model is used for data generation and various types of faults are considered. A comparative assessment of the estimates of different observers associated with these faults is included.

Keywords: Extended Kalman Filter, Fault detection and diagnosis, Induction motor model, Unscented Kalman Filter

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Authors: Amir Reza Talaghat

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Since 2015, a new approach and policy regarding energy resources protection and using renewable energies has been started in Iran which was developing new projects. Investigating about the feasibility study of these new projects helped to figure out five steps to prepare an executive feasibility study of the concerned projects, which are proper site selections, authorizations, design and simulation, economic study and programming, respectively. The results were interesting and essential for decision makers and investors to start implementing of these projects in reliable condition. The research is obtained through collection and study of the project's documents as well as recalculation to review conformity of the results with GIS data and the technical information of the bidders. In this paper, it is attempted to describe the result of the performed research by describing the five steps as an executive methodology, for preparing a feasible study of installing a 10 MW – solar farm project. The corresponding results of the research also help decision makers to start similar projects is explained in this paper as follows: selecting the best location for the concerned PV plant, reliable and safe conditions for investment and the required authorizations to start implementing the solar farm project in the concerned region, selecting suitable component to achieve the best possible performance for the plant, economic profit of the investment, proper programming to implement the project on time.

Keywords: Solar farm, solar energy, execution of PV power plant, PV power plant, feasibility study.

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Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

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The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: Complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT.

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Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate crosstalk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds, since biological information is inherently included inside the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: Brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning.

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Authors: Bin Su

Abstract:

A hotel mainly uses its energy on water heating, space heating, refrigeration, space cooling, cooking, lighting and other building services. A number of 4-5 stars hotels in Auckland city are selected for this study. Comparing with the energy used for others, the energy used for the internal space thermal control (e.g. internal space heating) is more closely related to the hotel building itself. This study not only investigates relationship between annual energy (and winter energy) consumptions and building design data but also relationships between winter extra energy consumption and building design data. This study is to identify the major design factors that significantly impact hotel energy consumption for improving the future hotel design for energy efficient.

Keywords: Hotel building design, building energy, building passive design, energy efficiency.

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Authors: Hany Mahgoub

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This paper presents a system for discovering association rules from collections of unstructured documents called EART (Extract Association Rules from Text). The EART system treats texts only not images or figures. EART discovers association rules amongst keywords labeling the collection of textual documents. The main characteristic of EART is that the system integrates XML technology (to transform unstructured documents into structured documents) with Information Retrieval scheme (TF-IDF) and Data Mining technique for association rules extraction. EART depends on word feature to extract association rules. It consists of four phases: structure phase, index phase, text mining phase and visualization phase. Our work depends on the analysis of the keywords in the extracted association rules through the co-occurrence of the keywords in one sentence in the original text and the existing of the keywords in one sentence without co-occurrence. Experiments applied on a collection of scientific documents selected from MEDLINE that are related to the outbreak of H5N1 avian influenza virus.

Keywords: Association rules, information retrieval, knowledgediscovery in text, text mining.

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Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

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Average temperatures worldwide are expected to continue to rise. At the same time, major cities in developing countries are becoming increasingly populated and polluted. Governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of a model, which is able to estimate the occupant exposure to extreme temperatures and high air pollution within domestic buildings. Building physics simulations were performed using the EnergyPlus building physics software. An accurate metamodel is then formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) have been compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: Neural Networks, Radial Basis Functions, Metamodelling, Python machine learning libraries.

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Authors: M. Najafi

Abstract:

In the present paper, a large turbo-generator shaft train including a heavy-duty gas turbine engine, a coupling, and a generator is established. The method of analysis is based on finite element simplified model for lateral and torsional vibration calculation. The basic elements of rotor are the shafts and the disks which are represented as circular cross section flexible beams and rigid body elements, respectively. For more accurate results, the gyroscopic effect and bearing dynamics coefficients and function of rotation are taken into account, and for the influence of shear effect, rotor has been modeled in the form of Timoshenko beam. Lateral critical speeds, critical speed map, damped mode shapes, Campbell diagram, zones of instability, amplitudes, phase angles response due to synchronous forces of excitation and amplification factor are calculated. Also, in the present paper, the effect of imbalanced rotor and effects of changing in internal force and temperature are studied.

Keywords: Rotor dynamic analysis, Finite element method, shaft train, Campbell diagram.

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Authors: R. B. Ogunrinde

Abstract:

This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: Differential equations, Numerical, Initial value problem, Polynomials.

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Authors: Claudia L. Zuñiga, Andres F. Millan, Jose L. Abadia, Monica Lora, Andres Navarro, Juan C. Burguillo, Pedro S. Rodriguez

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The increasing popularity of wireless technologies and mobile computing devices has enabled new application areas and research. One of these new areas is pervasive systems in urban environments, because urban environments are characterized by high concentration of these technologies and devices. In this paper we will show the process of pervasive system design in urban environments, using as use case a local zoo in Cali, Colombia. Based on an ethnographic studio, we present the design of a pervasive system for urban computing based on service oriented architecture to controlled environment of Cali Zoo. In this paper, the reader will find a methodological approach for the design of similar systems, using data collection methods, conceptual frameworks for urban environments and considerations of analysis and design of service oriented systems.

Keywords: Service Oriented Architecture, Urban Computing, Design of pervasive systems for urban environments, PSP Design Framework (Public Social Private), Cali Zoo.

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Authors: K. Sarrafan, A. Darabi

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In this paper, the steady-state temperature of a sample 500 KW two rotor one stator Non-slotted axial flux permanent magnet motor is calculated using the finite element simulator software package. Due to the high temperature in various parts of the machine, especially at stator winding, a cooling system is designed for the motor and the temperature is recalculated. The results show that the temperature obtained for the parts is within the permissible range.

Keywords: Axial Flux, Cooling System, Permanent Magnet, Thermal Analysis.

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Authors: Rukaiya Suleiman Umar, Annah Kwadu Medugu

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Moringa oleifera is mainly used as herbal medicine in most homes in Northern Nigeria. The plant is easy to grow and thrives very well regardless the type of soil. Use of moringa leaves in food production can yield attractive varieties on menu. This paper evaluates the acceptability of dishes produced with fresh moringa leaves with a view to promoting it in popular restaurants. A three course menu consisting of cream of moringa soup as the starter, mixed meat moringa sauce with semovita as the main dish and moringa roll as sweet was produced and served to a 60-member taste panel made of three groups of 20 each. Respondents were asked to rate the organoleptic qualities of the samples on a 10-point bipolar scale ranging from 1 (Dislike extremely) – 10 (Like extremely). Data collected were treated to one sample t-test and One Way ANOVA. Results show that the panelists extremely like the moringa products. It is recommended that Moringa oleifera should be incorporated into meals which is more readily acceptable than medicine.

Keywords: Moringa oleifera, food production, menu planning, healthy living.

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Authors: Ebtehal Alawi Alsaggaf, Shehab A. Gamalel-Din

Abstract:

Exploring an autistic child in Elementary school is a difficult task that must be fully thought out and the teachers should be aware of the many challenges they face raising their child especially the behavioral problems of autistic children. Hence there arises a need for developing Artificial intelligence (AI) Contemporary Techniques to help diagnosis to discover autistic people. In this research, we suggest designing architecture of expert system that combine Cognitive Maps (CM) with Case Based Reasoning technique (CBR) in order to reduce time and costs of traditional diagnosis process for the early detection to discover autistic children. The teacher is supposed to enter child's information for analyzing by CM module. Then, the reasoning processor would translate the output into a case to be solved a current problem by CBR module. We will implement a prototype for the model as a proof of concept using java and MYSQL. This will be provided a new hybrid approach that will achieve new synergies and improve problem solving capabilities in AI. And we will predict that will reduce time, costs, the number of human errors and make expertise available to more people who want who want to serve autistic children and their families.

Keywords: Autism, Cognitive Maps (CM), Case Based Reasoning technique (CBR).

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