Search results for: and Large scale Testing.

Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: Machine learning, Imbalanced data, Data mining, Big data.

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Authors: Victor Krebss

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Task of object localization is one of the major challenges in creating intelligent transportation. Unfortunately, in densely built-up urban areas, localization based on GPS only produces a large error, or simply becomes impossible. New opportunities arise for the localization due to the rapidly emerging concept of a wireless ad-hoc network. Such network, allows estimating potential distance between these objects measuring received signal level and construct a graph of distances in which nodes are the localization objects, and edges - estimates of the distances between pairs of nodes. Due to the known coordinates of individual nodes (anchors), it is possible to determine the location of all (or part) of the remaining nodes of the graph. Moreover, road map, available in digital format can provide localization routines with valuable additional information to narrow node location search. However, despite abundance of well-known algorithms for solving the problem of localization and significant research efforts, there are still many issues that currently are addressed only partially. In this paper, we propose localization approach based on the graph mapped distances on the digital road map data basis. In fact, problem is reduced to distance graph embedding into the graph representing area geo location data. It makes possible to localize objects, in some cases even if only one reference point is available. We propose simple embedding algorithm and sample implementation as spatial queries over sensor network data stored in spatial database, allowing employing effectively spatial indexing, optimized spatial search routines and geometry functions.

Keywords: Intelligent Transportation System, Sensor Network, Localization, Spatial Query, GIS, Graph Embedding.

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Authors: Robson C. Santos, Julio C. P. Ribeiro, Iorran M. de Castro, Luan C. F. Rodrigues, Sandro R. L. Silva, Diego M. Quesada

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The work aims to develop a robot in the form of autonomous vehicle to detect, inspection and mapping of underground pipelines through the ATmega328 Arduino platform. Hardware prototyping is very similar to C / C ++ language that facilitates its use in robotics open source, resembles PLC used in large industrial processes. The robot will traverse the surface independently of direct human action, in order to automate the process of detecting buried pipes, guided by electromagnetic induction. The induction comes from coils that send the signal to the Arduino microcontroller contained in that will make the difference in intensity and the treatment of the information, and then this determines actions to electrical components such as relays and motors, allowing the prototype to move on the surface and getting the necessary information. This change of direction is performed by a stepper motor with a servo motor. The robot was developed by electrical and electronic assemblies that allowed test your application. The assembly is made up of metal detector coils, circuit boards and microprocessor, which interconnected circuits previously developed can determine, process control and mechanical actions for a robot (autonomous car) that will make the detection and mapping of buried pipelines plates. This type of prototype can prevent and identifies possible landslides and they can prevent the buried pipelines suffer an external pressure on the walls with the possibility of oil leakage and thus pollute the environment.

Keywords: Robotic, metal detector, embedded system, pipeline.

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Authors: Malinwo Estone Ayikpa

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With the rapid increase of grid-connected PV systems over the last decades, genuine challenges have arisen for engineers and professionals of energy field in the planning and operation of existing distribution networks with the integration of new generation sources. However, the conventional distribution network, in its design was not expected to receive other generation outside the main power supply. The tools generally used to analyze the networks become inefficient and cannot take into account all the constraints related to the operation of grid-connected PV systems. Some of these constraints are voltage control difficulty, reverse power flow, and especially voltage unbalance which could be due to the poor distribution of single-phase PV systems in the network. In order to analyze the impact of the connection of small and large number of PV systems to the distribution networks, this paper presents an efficient optimization tool that minimizes voltage unbalance in three-phase distribution networks with active and reactive power injections from the allocation of single-phase and three-phase PV plants. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. Good reduction of voltage unbalance can be achieved by reactive power control of the PV systems. The presented tool is based on the three-phase current injection method and the PV systems are modeled via an equivalent circuit. The primal-dual interior point method is used to obtain the optimal operating points for the systems.

Keywords: Photovoltaic generation, primal-dual interior point method, three-phase optimal power flow, unbalanced system.

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Authors: Tamanna Siddiqui, M. Afshar Alam

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Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.

Keywords: Knowledge discovery in database, quantification, dempster shafer theory, genetic programming, hierarchy, subsumption matrix.

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Authors: Mohammad Asif

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A large number of chemical, bio-chemical and pollution-control processes use heterogeneous fixed-bed reactors. The use of finite hollow cylindrical catalyst pellets can enhance conversion levels in such reactors. The absence of the pellet core can significantly lower the diffusional resistance associated with the solid phase. This leads to a better utilization of the catalytic material, which is reflected in the higher values for the effectiveness factor, leading ultimately to an enhanced conversion level in the reactor. It is however important to develop a rigorous heterogeneous model for the reactor incorporating the two-dimensional feature of the solid phase owing to the presence of the finite hollow cylindrical catalyst pellet. Presently, heterogeneous models reported in the literature invariably employ one-dimension solid phase models meant for spherical catalyst pellets. The objective of the paper is to present a rigorous model of the fixed-bed reactors containing finite hollow cylindrical catalyst pellets. The reaction kinetics considered here is the widely used Michaelis–Menten kinetics for the liquid-phase bio-chemical reactions. The reaction parameters used here are for the enzymatic degradation of urea. Results indicate that increasing the height to diameter ratio helps to improve the conversion level. On the other hand, decreasing the thickness is apparently not as effective. This could however be explained in terms of the higher void fraction of the bed that causes a smaller amount of the solid phase to be packed in the fixed-bed bio-chemical reactor.

Keywords: Fixed-bed reactor, Finite hollow cylinder, Catalyst pellet, Conversion, Michaelis-Menten kinetics.

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Authors: Alireza Mortezaei, Kimia Mortezaei

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Recordings from recent earthquakes have provided evidence that ground motions in the near field of a rupturing fault differ from ordinary ground motions, as they can contain a large energy, or “directivity" pulse. This pulse can cause considerable damage during an earthquake, especially to structures with natural periods close to those of the pulse. Failures of modern engineered structures observed within the near-fault region in recent earthquakes have revealed the vulnerability of existing RC buildings against pulse-type ground motions. This may be due to the fact that these modern structures had been designed primarily using the design spectra of available standards, which have been developed using stochastic processes with relatively long duration that characterizes more distant ground motions. Many recently designed and constructed buildings may therefore require strengthening in order to perform well when subjected to near-fault ground motions. Fiber Reinforced Polymers are considered to be a viable alternative, due to their relatively easy and quick installation, low life cycle costs and zero maintenance requirements. The objective of this paper is to investigate the adequacy of Artificial Neural Networks (ANN) to determine the three dimensional dynamic response of FRP strengthened RC buildings under the near-fault ground motions. For this purpose, one ANN model is proposed to estimate the base shear force, base bending moments and roof displacement of buildings in two directions. A training set of 168 and a validation set of 21 buildings are produced from FEA analysis results of the dynamic response of RC buildings under the near-fault earthquakes. It is demonstrated that the neural network based approach is highly successful in determining the response.

Keywords: Seismic evaluation, FRP, neural network, near-fault ground motion

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Authors: Chen Chou, Feng-Tyan Lin

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Big Data has been attracted a lot of attentions in many fields for analyzing research issues based on a large number of maternal data. Electronic Toll Collection (ETC) is one of Intelligent Transportation System (ITS) applications in Taiwan, used to record starting point, end point, distance and travel time of vehicle on the national freeway. This study, taking advantage of ETC big data, combined with urban planning theory, attempts to explore various phenomena of inter-city transportation activities. ETC, one of government's open data, is numerous, complete and quick-update. One may recall that living area has been delimited with location, population, area and subjective consciousness. However, these factors cannot appropriately reflect what people’s movement path is in daily life. In this study, the concept of "Living Area" is replaced by "Influence Range" to show dynamic and variation with time and purposes of activities. This study uses data mining with Python and Excel, and visualizes the number of trips with GIS to explore influence range of Tainan city and the purpose of trips, and discuss living area delimited in current. It dialogues between the concepts of "Central Place Theory" and "Living Area", presents the new point of view, integrates the application of big data, urban planning and transportation. The finding will be valuable for resource allocation and land apportionment of spatial planning.

Keywords: Big Data, ITS, influence range, living area, central place theory, visualization.

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Authors: A. S. Gorobtsov, A. S. Polyanina, A. E. Andreev

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The movement of points feet of the anthropomorphous robot in space occurs along some stable trajectory of a known form. A large number of modifications to the methods of control of biped robots indicate the fundamental complexity of the problem of stability of the program trajectory and, consequently, the stability of the control for the deviation for this trajectory. Existing gait generators use piecewise interpolation of program trajectories. This leads to jumps in the acceleration at the boundaries of sites. Another interpolation can be realized using differential equations with fractional derivatives. In work, the approach to synthesis of generators of program trajectories is considered. The resulting system of nonlinear differential equations describes a smooth trajectory of movement having rectilinear sites. The method is based on the theory of an asymptotic stability of invariant sets. The stability of such systems in the area of localization of oscillatory processes is investigated. The boundary of the area is a bounded closed surface. In the corresponding subspaces of the oscillatory circuits, the resulting stable limit cycles are curves having rectilinear sites. The solution of the problem is carried out by means of synthesis of a set of the continuous smooth controls with feedback. The necessary geometry of closed trajectories of movement is obtained due to the introduction of high-order nonlinearities in the control of stabilization systems. The offered method was used for the generation of trajectories of movement of point’s feet of the anthropomorphous robot. The synthesis of the robot's program movement was carried out by means of the inverse method.

Keywords: Control, limits cycle, robot, stability.

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Authors: Felix Platzer, Eric Fimbinger

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In Discrete Element Method (DEM) simulations, the breakage behavior of particles can be simulated based on different principles. In the case of large, complex-shaped particles that show various breakage patterns depending on the scenario leading to the failure and often only break locally instead of fracturing completely, some of these principles do not lead to realistic results. The reason for this is that in said cases, the methods in question, such as the Particle Replacement Method (PRM) or Voronoi Fracture, replace the initial particle (that is intended to break) into several sub-particles when certain breakage criteria are reached, such as exceeding the fracture energy. That is why those methods are commonly used for the simulation of materials that fracture completely instead of breaking locally. That being the case, when simulating local failure, it is advisable to pre-build the initial particle from sub-particles that are bonded together. The dimensions of these sub-particles  consequently define the minimum size of the fracture results. This structure of bonded sub-particles enables the initial particle to break at the location of the highest local loads – due to the failure of the bonds in those areas – with several sub-particle clusters being the result of the fracture, which can again also break locally. In this project, different methods for the generation and calibration of complex-shaped particle conglomerates using bonded particle modeling (BPM) to enable the ability to depict more realistic fracture behavior were evaluated based on the example of filter cake. The method that proved suitable for this purpose and which furthermore  allows efficient and realistic simulation of breakage behavior of complex-shaped particles applicable to industrial-sized simulations is presented in this paper.

Keywords: Bonded particle model (BPM), DEM, filter cake, particle breakage, particle fracture.

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Authors: Akrem Sellami, Imed Riadh Farah

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Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: Hyperspectral image, spatial hypergraph, dimensionality reduction, semantic interpretation, band selection, feature extraction.

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Authors: Jeries J. Abou-Hanna

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Several techniques exist for determining stress-intensity factors in linear elastic fracture mechanics analysis. These techniques are based on analytical, numerical, and empirical approaches that have been well documented in literature and engineering handbooks. However, not all techniques share the same merit. In addition to overly-conservative results, the numerical methods that require extensive computational effort, and those requiring copious user parameters hinder practicing engineers from efficiently evaluating stress-intensity factors. This paper investigates the prospects of reducing the complexity and required variables to determine stress-intensity factors through the utilization of the stress gradient and a weighting function. The heart of this work resides in the understanding that fracture emanating from stress concentration locations cannot be explained by a single maximum stress value approach, but requires use of a critical volume in which the crack exists. In order to understand the effectiveness of this technique, this study investigated components of different notch geometry and varying levels of stress gradients. Two forms of weighting functions were employed to determine stress-intensity factors and results were compared to analytical exact methods. The results indicated that the “exponential” weighting function was superior to the “absolute” weighting function. An error band +/- 10% was met for cases ranging from a steep stress gradient in a sharp v-notch to the less severe stress transitions of a large circular notch. The incorporation of the proposed method has shown to be a worthwhile consideration.

Keywords: Fracture mechanics, finite element method, stress intensity factor, stress gradient.

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Authors: David Xiaoqian Sun, Khairunnisa Binti Haji Sibah, Jr., Lejak Anak Ambol

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The purpose of the study was to examine the relationships between objectively measured physical activity levels (PALs), enjoyment of physical activity (EPA), and body mass index (BMI) among adolescents. A total of 188 12-14-year-old Bruneian secondary school adolescents (88 boys and 100 girls) voluntarily took part in this study. Subjects wore the RT3 accelerometer for seven consecutive days in order to measure their PALs. Times of students’ engagement in total (TPA), light (LPA), moderate (MPV), and vigorous PA (VPA) were obtained from the accelerometer. Their BMIs were calculated from their body height and weight. Physical Activity Enjoyment Scale (PACES) was administrated to obtain their EPA levels. Four key enjoyment factors including fun factors, positive perceptions, unexciting in doing activities, and negative perceptions were identified. Subjects’ social economic status (SES) was provided by school administration. Results show that all the adolescents did not meet the recommended PA guidelines even though boys were engaged in more MVPA than girls. No relationships were found between BMI and all PALs in both boys and girls. BMI was significantly related to the PACES scores (r = -.22, p = 0.01), fun factors (r = -.20, p = 0.05) and positive perceptions (r =- .21, p < 0.05). The PACES scores were significantly related to LPA (r = .18, p = 0.01) but not related to MVPA (r = .04, p > 0.05). After controlling for age and SES, BMI was only significantly related to the PACES scores in girls (r = -.27, p < .01) but boys (r = -.06, p > 0.05). Fun factors were significantly related to LPA and MVPA (p < .01) in girls while negative perceptions were significantly related to LPA and MVPA (p < .01) in boys. This study provides evidence that enjoyment may be a trigger of LPA but MVPA and may be influenced by their BMI status particularly in girls. Based on these findings, physical and health educators are suggested to not only make PA more enjoyable, but also consider gender differences in promoting adolescents' participation in MVPA

Keywords: Accelerometer, body mass index, enjoyment of physical activity, moderate to vigorous physical activity.

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Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

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One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: Data-Driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis.

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Authors: Prima Luna, Afroditi Chatzifragkou, Dimitris Charalampopoulos

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Sorghum byproducts, namely bran, stalk, and panicle are examples of lignocellulosic biomass. These raw materials contain large amounts of polysaccharides, in particular hemicelluloses, celluloses, and lignins, which if efficiently extracted, can be utilised for the development of a range of added value products with potential applications in agriculture and food packaging sectors. The aim of this study was to characterise fractions extracted from sorghum bran and stalk with regards to their physicochemical properties that could determine their applicability as food-packaging materials. A sequential alkaline extraction was applied for the isolation of cellulosic, hemicellulosic and lignin fractions from sorghum stalk and bran. Lignin content, phenolic content and antioxidant capacity were also investigated in the case of the lignin fraction. Thermal analysis using differential scanning calorimetry (DSC) and X-Ray Diffraction (XRD) revealed that the glass transition temperature (T_g) of cellulose fraction of the stalk was ~78.33 ^oC at amorphous state (~65%) and water content of ~5%. In terms of hemicellulose, the T_g value of stalk was slightly lower compared to bran at amorphous state (~54%) and had less water content (~2%). It is evident that hemicelluloses generally showed a lower thermal stability compared to cellulose, probably due to their lack of crystallinity. Additionally, bran had higher arabinose-to-xylose ratio (0.82) than the stalk, a fact that indicated its low crystallinity. Furthermore, lignin fraction had T_g value of ~93 ^oC at amorphous state (~11%). Stalk-derived lignin fraction contained more phenolic compounds (mainly consisting of p-coumaric and ferulic acid) and had higher lignin content and antioxidant capacity compared to bran-derived lignin fraction.

Keywords: Alkaline extraction, bran, cellulose, hemicellulose, lignin, sorghum, stalk.

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Authors: S. Ziaran, M. Musil, M. Cekan, O. Chlebo

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The paper analyzes the response of buildings and industrially structures on seismic waves (low frequency mechanical vibration) generated by blasting operations. The principles of seismic analysis can be applied for different kinds of excitation such as: earthquakes, wind, explosions, random excitation from local transportation, periodic excitation from large rotating and/or machines with reciprocating motion, metal forming processes such as forging, shearing and stamping, chemical reactions, construction and earth moving work, and other strong deterministic and random energy sources caused by human activities. The article deals with the response of seismic, low frequency, mechanical vibrations generated by nearby blasting operations on a residential home. The goal was to determine the fundamental natural frequencies of the measured structure; therefore it is important to determine the resonant frequencies to design a suitable modal damping. The article also analyzes the package of seismic waves generated by blasting (Primary waves – P-waves and Secondary waves S-waves) and investigated the transfer regions. For the detection of seismic waves resulting from an explosion, the Fast Fourier Transform (FFT) and modal analysis, in the frequency domain, is used and the signal was acquired and analyzed also in the time domain. In the conclusions the measured results of seismic waves caused by blasting in a nearby quarry and its effect on a nearby structure (house) is analyzed. The response on the house, including the fundamental natural frequency and possible fatigue damage is also assessed.

Keywords: Building structure, seismic waves, spectral analysis, structural response.

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Authors: Y. S. Zhou, C. R. Li, L. L. Tang, C. X. Gao, D. J. Wang, Y. Y. Guo

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Triangular trihedral corner reflector (CR) has been widely used as point target for synthetic aperture radar (SAR) calibration and image quality assessment. The additional “tip” of the triangular plate does not contribute to the reflector’s theoretical RCS and if it interacts with a perfectly reflecting ground plane, it will yield an increase of RCS at the radar bore-sight and decrease the accuracy of SAR calibration and image quality assessment. Regarding this problem, two types of CRs were manufactured. One was the hexagonal trihedral CR. It is a self-illuminating CR with relatively small plate edge length, while large edge length usually introduces unexpected edge diffraction error. The other was the triangular trihedral CR with extended bottom plate which considers the effect of ‘tip’ into the total RCS. In order to assess the performance of the two types of new CRs, flight campaign over the National Calibration and Validation Site for High Resolution Remote Sensors was carried out. Six hexagonal trihedral CRs and two bottom-extended trihedral CRs, as well as several traditional triangular trihedral CRs, were deployed. KOMPSAT-5 X-band SAR image was acquired for the performance analysis of the hexagonal trihedral CRs. C-band airborne SAR images were acquired for the performance analysis of the bottom-extended trihedral CRs. The analysis results showed that the impulse response function of both the hexagonal trihedral CRs and bottom-extended trihedral CRs were much closer to the ideal sinc-function than the traditional triangular trihedral CRs. The flight campaign results validated the advantages of new types of CRs and they might be useful in the future SAR calibration mission.

Keywords: Synthetic Aperture Radar, calibration, corner reflector, KOMPSAT-5.

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Authors: Ranojoy Dutta, Adam Barker

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Multifamily residential buildings are increasingly being built with large glazed areas to provide tenants with greater daylight and outdoor views. However, traditional double-glazed window assemblies can lead to significant thermal discomfort from high radiant temperatures as well as increased cooling energy use to address solar gains. Dynamic glazing provides an effective solution by actively controlling solar transmission to maintain indoor thermal comfort, without compromising the visual connection to outdoors. This study uses thermal simulations across three Canadian cities (Toronto, Vancouver and Montreal) to verify if dynamic glazing along with operable windows and ceiling fans can maintain the indoor operative temperature of a prototype southwest facing high-rise apartment unit within the ASHRAE 55 adaptive comfort range for a majority of the year, without any mechanical cooling. Since this study proposes the use of natural ventilation for cooling and the typical building life cycle is 30-40 years, the typical weather files have been modified based on accepted global warming projections for increased air temperatures by 2050. Results for the prototype apartment confirm that thermal discomfort with dynamic glazing occurs only for less than 0.7% of the year. However, in the baseline scenario with low-E glass there are up to 7% annual hours of discomfort despite natural ventilation with operable windows and improved air movement with ceiling fans.

Keywords: Electrochromic, operable windows, thermal comfort, natural ventilation, adaptive comfort.

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Authors: H. Shayeghi, A. Jalili

Abstract:

This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Keywords: AGC, Hybrid Fuzzy Controller, Deregulated Power System, Power System Control, GAs.

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Authors: M. Ondova, A. Estokova

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Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO₂ emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills.

Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: Life cycle assessment, fly ash, waste, concrete pavements

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Authors: S. Rawangwong, J. Chatthong, W. Boonchouytan

Abstract:

The objective of the research was to study of foot anthropometry of children aged 7-12 years in the South of Thailand Thirty-three dimensions were measured on 305 male and 295 female subjects with 3 age ranges (7-12 years old). The instrumentation consists of four types of anthropometer, digital vernier caliper, digital height gauge and measuring tape. The mean values and standard deviations of average age, height, and weight of the male subjects were 9.52(±1.70) years, 137.80(±11.55) cm, and 37.57(±11.65) kg. Female average age, height, and weight subjects were 9.53(±1.70) years, 137.88(±11.55) cm, and 34.90(±11.57) kg respectively. The comparison of the 33 comparison measured anthropometric. Between male and female subjects were sexual differences in size on women in almost all areas of significance (p<0.05). The comparison of size and proportion elementary school students 11-12 years old men in Southern of Thailand with Thai boys aged 11-12 years of industrial standards at stage 4 year A.D. 2000-2001 Number nine ratio. Concluded that students male in Southern of Thailand has a size different from the proportions of research Industrial Standards. Ministry of Industry, Phase 4, when every year from A.D. 2000-2001 ratio was significantly (p<0.05).All of the feet studied were classified into 4 categories according to the ratios of diagonal foot breadth to the maximum foot length and heel breadth to the foot breadth. They were short but thick, small but long, small, and large. The numbers of the males feet classified in these categories were 86, 64, 40, and 115 persons or 28.20, 20.98, 13.11, and 37.70% respectively. For the female feet, the same values were 46, 59, 81, and 109 persons or 15.59, 20.00, 27.46, and 36.95% respectively.

Keywords: Ergonomics, foot anthropometry, male and female, primary school children

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Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, adaptive antenna array, Deep Neural Network, LS-SVM optimization model, radial basis function, MSE.

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Authors: Kazuhisa Koda, Tsutomu Kobayashi, Rebecca Lorennji, Alington Robert, Halston DeBrum, Julious Lucky, Paul Paul

Abstract:

Atolls are low-lying small islands with highly permeable ground that does not allow rivers and lakes to develop. As the water resources on these atolls basically rely on precipitation, groundwater becomes a very important water resource during droughts. Freshwater lenses develop as groundwater on relatively large atoll islands and play a key role in the stable water supply. Atoll islands in the Pacific Ocean sometimes suffer from drought due to El Nino. The global warming effects are noticeable, particularly on atoll islands. The Republic of the Marshall Islands in Oceania is burdened with the problems common to atoll islands. About half of its population lives in the capital, Majuro, and securing water resources for these people is a crucial issue. There is a freshwater lens on the largest, Laura Island, which serves as a water source for the downtown area. A serious drought that occurred in 1998 resulted in excessive water intake from the freshwater lens on Laura Island causing up-coning. Up-coning mixes saltwater into groundwater pumped from water-intake wells. Because up-coning makes the freshwater lens unusable, there was a need to investigate the freshwater lens on Laura Island. In this study, we observed the electrical conductivities of the groundwater at different depths in existing monitoring wells to determine the total storage volume of the freshwater lens on Laura Island from 2010 to 2013. Our results indicated that most of the groundwater that seeped into the freshwater lens had flowed out into the sea.

Keywords: Atoll islands, drought, El-Nino, freshwater lens, groundwater observation.

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Authors: Satyanadh Gundimada, Vijayan K Asari

Abstract:

A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.

Keywords: Discriminant analysis, intra-class probability distribution, principal component analysis, phase congruency.

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Authors: Yesubai Rubavathi Charles, Ravi Ramraj

Abstract:

In order to retrieve images efficiently from a large database, a unique method integrating color and texture features using genetic programming has been proposed. Opponent color histogram which gives shadow, shade, and light intensity invariant property is employed in the proposed framework for extracting color features. For texture feature extraction, fast discrete curvelet transform which captures more orientation information at different scales is incorporated to represent curved like edges. The recent scenario in the issues of image retrieval is to reduce the semantic gap between user’s preference and low level features. To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user’s preference images. Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000. Experimental results clearly show that the proposed system surpassed other existing systems in terms of precision and recall. The proposed work achieves highest performance with average precision of 88.2% on COIL-100 and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3% on Corel. Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.

Keywords: Content based image retrieval, Curvelet transform, Genetic algorithm, Opponent color histogram, Relevance feedback.

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Authors: Masoud Mahdavi, Mojtaba Farzaneh Moghadam

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The seismic forces caused by the waves created in the depths of the earth during the earthquake hit the structure and cause the building to vibrate. Creating large seismic forces will cause low-strength sections in the structure to suffer extensive surface damage. The use of new steel shear walls in steel structures has caused the strength of the building and its main members (columns) to increase due to the reduction and depreciation of seismic forces during earthquakes. In the present study, an attempt was made to evaluate a type of steel shear wall that has regular holes in the inner sheet by modeling the finite element model with Abacus software. The shear wall of the steel plate, measuring 6000 × 3000 mm (one floor) and 3 mm thickness, was modeled with four different pores with a cross-sectional area. The shear wall was dynamically subjected to a time history of 5 seconds by three accelerators, El Centro, Imperial Valley and Kobe. The results showed that increasing the distance between the geometric center of the hole and the geometric center of the inner plate in the steel shear wall (increasing the R_CS index) caused the total maximum acceleration to be transferred from the perimeter of the hole to horizontal and vertical beams. The results also show that there is no direct relationship between R_CS index and total acceleration in steel shear wall and R_CS index is separate from the peak ground acceleration value of earthquake.

Keywords: Hollow Steel plate shear wall, time history analysis, finite element method, Abaqus Software.

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Authors: R. A. Isabel, E. Baburaj

Abstract:

Wireless Body Area Networks (WBANs) are essential for real-time health monitoring of patients and in diagnosing of many diseases. WBANs comprise many sensors to monitor a large range of ambient conditions. Quality of Service (QoS) is a key challenge in WBAN, because the different state information of the neighboring nodes has to be monitored in an accurate manner. However, energy consumption gets increased while predicting and maintaining the exact information in highly dynamic environments. In order to reduce energy consumption and end to end delay, Markov Chain Based Quality of Service Support (MC-QoSS) method is designed in the health monitoring services of WBAN communication. The energy consumption gets reduced by forming a Markov chain with high energy nodes in the sensor networks communication path. The low energy level sensor nodes are removed using transitional probability in order to reduce end to end delay. High energy nodes are formed in the chain structure of its corresponding path to enhance communication. After choosing the communication path through high energy nodes, the packets are sent to the sink node from the source node with a higher Packet Delivery Ratio. The simulation result shows that MC-QoSS method improves the packet delivery ratio and reduces energy consumption with minimum end to end delay, compared to existing methods.

Keywords: Wireless body area networks, quality of service, Markov chain, health monitoring services.

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Authors: Ahmed R. Z. Baghdadi, Amira A. A. Abdallah

Abstract:

Background: With the perceived pain and poor function experienced following knee arthroplasty, patients usually feel un-satisfied. Yet, a controversy still persists on the appropriate operative technique that doesn’t affect proprioception much.

Purpose: This study compared the effects of Cruciate Retaining (CR) and Posterior Stabilized (PS) total knee arthroplasty (TKA) and uni-compartmental knee arthroplasty (UKA) on dynamic balance, pain and functional performance following rehabilitation.

Methods: Fifteen patients with CRTKA (group I), fifteen with PSTKA (group II), fifteen with UKA (group III) and fifteen indicated for arthroplasty but weren’t operated on yet (group IV) participated in the study. The mean age was 54.53±3.44, 55.13±3.48, 52.8±1.93 and 55.33±2.32 years and BMI 35.7±3.03, 35.7±1.99, 35.6±1.88 and 35.73±1.03 kg/m² for group I, II, III and IV respectively. The Berg Balance Scale (BBS), WOMAC pain subscale and Timed Up-and-Go (TUG) and Stair-Climbing (SC) tests were used for assessment. Assessments were conducted four and eight weeks pre- and post-operatively with the control group being assessed at the same time intervals. The post-operative rehabilitation involved hospitalization (1^st week), home-based (2^nd-4^th weeks), and outpatient clinic (5^th-8^th weeks) programs.

Results: The Mixed design MANOVA revealed that group III had significantly higher BBS scores, and lower pain scores and TUG and SC time than groups I and II four and eight weeks post-operatively. In addition, group I had significantly lower pain scores and SC time compared with group II eight weeks post-operatively. Moreover, the BBS scores increased significantly and the pain scores and TUG and SC time decreased significantly eight weeks post-operatively compared with the three other assessments in group I, II and III with the opposite being true four weeks post-operatively.

Interpretation/Conclusion: CRTKA is preferable to PSTKA with UKA being generally superior to TKA, possibly due to the preserved human proprioceptors in the un-excised compartmental articular surface.

Keywords: Dynamic Balance, Functional Performance, Knee Arthroplasty, Pain.

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Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang

Abstract:

Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R² of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.

Keywords: Chronic kidney disease, microfluidics, linear regression, VITROS analyzer, urinary albumin.

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Authors: Brian Considine, Aonghus McNabola, John Gallagher, Prashant Kumar

Abstract:

Passive air pollution control devices known as aspiration efficiency reducers (AER) have been developed using aspiration efficiency (AE) concepts. Their purpose is to reduce the concentration of particulate matter (PM) drawn into a building air handling unit (AHU) through alterations in the inlet design improving energy consumption. In this paper an examination is conducted into the effect of installing a deflector system around an AER-AHU inlet for both a forward and rear-facing orientations relative to the wind. The results of the study found that these deflectors are an effective passive control method for reducing AE at various ambient wind speeds over a range of microparticles of varying diameter. The deflector system was found to induce a large wake zone at low ambient wind speeds for a rear-facing AER-AHU, resulting in significantly lower AE in comparison to without. As the wind speed increased, both contained a wake zone but have much lower concentration gradients with the deflectors. For the forward-facing models, the deflector system at low ambient wind speed was preferred at higher Stokes numbers but there was negligible difference as the Stokes number decreased. Similarly, there was no significant difference at higher wind speeds across the Stokes number range tested. The results demonstrate that a deflector system is a viable passive control method for the reduction of ventilation energy consumption.

Keywords: Aspiration efficiency, energy, particulate matter, ventilation.

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