Search results for: fundamental natural bending frequency.

Authors: Lars Steiner, Zahra Ahmadi

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Public housing is a vital factor in community development. Successful city, housing and eco system regeneration design is essential in providing positive community development. This concerns work places, nice dwellings, providing premises for child care, care of the elderly, providing qualitative premises for different kinds of commercial service, providing a nice built environment and housing areas and not the least activating tenants. The public housing companies give value to society by stimulating people, renovating socially and economically sustainable as well as being partners to local business and authorities. By their activities the housing companies contribute to sustainable local and regional growth and the identity and reputation of cities. A Social, Economic and Ecological Reputation Effect (SEERE) model for actions to promote housing and community reputation is presented. The model emphasizes regenerative actions to restore natural eco systems as part of housing renewal strategies and to strengthen municipality reputation.

Keywords: Community Development, Image and Reputation, Public Housing, Renewal Strategies.

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Authors: Daniele Baldacci, Remo Pareschi

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Augmented Reality and Augmented Intelligence are radically changing information technology. The path that starts from the keyboard and then, passing through milestones such as Siri, Alexa and other vocal avatars, reaches a more fluid and natural communication with computers, thus converting the dichotomy between man and machine into a harmonious interaction, now heads unequivocally towards a new IT paradigm, where holographic computing will play a key role. The OLOS® platform contributes substantially to this trend in that it infuses computers with human features, by transferring the gestures and expressions of persons of flesh and bones to anthropomorphic holographic interfaces which in turn will use them to interact with real-life humans. In fact, we could say, boldly but with a solid technological background to back the statement, that OLOS® gives reality to an altogether new entity, placed at the exact boundary between nature and technology, namely the holographic human being. Holographic humans qualify as the perfect carriers for the virtual reincarnation of characters handed down from history and tradition. Thus, they provide for an innovative and highly immersive way of experiencing our cultural heritage as something alive and pulsating in the present.

Keywords: Human-computer interfaces, holographic simulation, digital cinematography, interactive museum exhibits.

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Authors: D. Vidhyaprakash, A. Elango

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In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.

Keywords: Wheeled mobile robot (WMR), terrain, wheel slippage, odometry error, navigation.

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Authors: Md. Khademul Islam Molla, Akimasa Sumi, M. Sayedur Rahman

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The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.

Keywords: Empirical mode decomposition, instantaneous frequency, Hilbert spectrum, Chi-square distribution, anthropogenic impact.

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Authors: Maohai Li, Bingrong Hong, Zesu Cai, Ronghua Luo

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This paper presents the novel Rao-Blackwellised particle filter (RBPF) for mobile robot simultaneous localization and mapping (SLAM) using monocular vision. The particle filter is combined with unscented Kalman filter (UKF) to extending the path posterior by sampling new poses that integrate the current observation which drastically reduces the uncertainty about the robot pose. The landmark position estimation and update is also implemented through UKF. Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem, and introducing the evolution strategies (ES) for avoiding particle impoverishment. The 3D natural point landmarks are structured with matching Scale Invariant Feature Transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-Tree in the time cost of O(log2 N). Experiment results on real robot in our indoor environment show the advantages of our methods over previous approaches.

Keywords: Mobile robot, simultaneous localization and mapping, Rao-Blackwellised particle filter, evolution strategies, scale invariant feature transform.

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: Behavior of winds, wind power, fuzzy logic, sustainable development.

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Authors: Y. Araki, M. Kim, S. Okayama, K. Ikago, K. Uetani

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We study dynamic instability in high-rise steel moment resisting frames (SMRFs) subjected to synthetic long-period ground motions caused by hypothetical huge subduction earthquakes. Since long duration as well as long dominant periods is a characteristic of long-period ground motions, interstory drifts may enter the negative postyield stiffness range many times when high-rise buildings are subjected to long-period ground motions. Through the case studies of 9 high-rise SMRFs designed in accordance with the Japanese design practice in 1980s, we demonstrate that drifting, or accumulation of interstory drifts in one direction, occurs at the lower stories of the SMRFs, if their natural periods are close to the dominant periods of the long-period ground motions. The drifting led to residual interstory drift ratio over 0.01, or to collapse if the design base shear was small.

Keywords: long-period ground motion, P-Delta effect, high-rise steel moment resisting frame (SMRF), subduction earthquake

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Authors: K. Ö. Kartal, L. Maul, M. Hägele

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With the development of new technologies come additional opportunities for the founding of companies and new markets to be created. The barriers to entry are lowered and technology makes old business models obsolete. Incumbent companies have to be adaptable to this quickly changing environment. They have to start the process of digital maturation and they have to be able to adapt quickly to new and drastic changes that might arise. One of the biggest barriers for organizations in order to do so is their culture. This paper shows the core elements of a corporate culture that supports the process of digital maturation in incumbent organizations. Furthermore, it is explored how ideation and innovation can be used in a strategy in order to facilitate these core elements of culture that promote digital maturity. Focus areas are identified for the design of ideation strategies, with the aim to make the facilitation and incitation process more effective, short to long term. Therefore, one in-depth case study is conducted with data collection from interviews, observation, document review and surveys. The findings indicate that digital maturity is connected to cultural shift and 11 relevant elements of digital culture are identified which have to be considered. Based on these 11 core elements, five focus areas that need to be regarded in the design of a strategy that uses ideation and innovation to facilitate the cultural shift are identified. These are: Focus topics, rewards and communication, structure and frequency, regions and new online formats.

Keywords: Digital transformation, innovation management, ideation strategy, creativity culture, change.

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Authors: Janice Haworth, Karamoko Camara, Marie-Therèse Dramou, Kokoly Haba, Daniel Léno, Augustin Mara, Adama Noël Oulari, Silafa Tolno, Noël Zoumanigui

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The traditional rhythms of the West African country of Guinea have played a centuries-long role in defining the different people groups that make up the country. Throughout their history, before and since colonization by the French, the different ethnicities have used their traditional music as a distinct part of their historical identities. That is starting to change. Guinea is an impoverished nation created in the early twentieth-century with little regard for the history and cultures of the people who were included. The traditional rhythms of the different people groups and their heritages have remained. Fifteen individual traditional Guinean rhythms were chosen to represent popular rhythms from the four geographical regions of Guinea. Each rhythm was traced back to its native village and video recorded on-site by as many different local performing groups as could be located. The cyclical patterns rhythms were transcribed via a circular, spatial design and then copied into a box notation system where sounds happening at the same time could be studied. These rhythms were analyzed for their consistency-overperformance in a Fundamental Rhythm Pattern analysis so rhythms could be compared for how they are changing through different performances. The analysis showed that the traditional rhythm performances of the Middle and Forest Guinea regions were the most cohesive and showed the least evidence of change between performances. The role of music in each of these regions is both limited and focused. The Coastal and High Guinea regions have much in common historically through their ethnic history and modern-day trade connections, but the rhythm performances seem to be less consistent and demonstrate more changes in how they are performed today. In each of these regions the role and usage of music is much freer and wide-spread. In spite of advances being made as a country, different ethnic groups still frequently only respond and participate (dance and sing) to the music of their native ethnicity. There is some evidence that this self-imposed musical barrier is beginning to change and evolve, partially through the development of better roads, more access to electricity and technology, the nationwide Ebola health crisis, and a growing self-identification as a unified nation.

Keywords: Cultural identity, Guinea, traditional rhythms, West Africa.

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Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin

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In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.

Keywords: Cash flow optimization, payment plan, procurement management, subcontracting plan.

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Authors: Angela Unna Chukwu, Samuel Oluwafemi Oyamakin

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We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a shape parameter (allometric). This was achieved by convoluting hyperbolic sine function on the intrinsic rate of growth in the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while the independence of the error term was confirmed using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE and AIC confirmed the predictive power of the Hyperbolic Gompertz growth models over its source model.

Keywords: Height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz.

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Authors: Tessy Treesa Jose, Sripathy M. Bhat

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Nursing is recognized as a stressful occupation and has indicated a probable high prevalence of distress. It is a helping profession requiring a high degree of commitment and involvement. If stress is intense, continuous and repeated, it becomes a negative phenomenon or "distress," which can lead to physical illness and psychological disorders. The frequency of common psychosomatic symptoms including sleeping problems, tension headache, chronic fatigue, palpitation etc. may be an indicator of nurses’ work-related stress level. Objectives of the study were to determine psychiatric morbidity among nurses and to find its association with selected variables. The study population consisted of 1040 registered nurses working in selected medical college hospitals and government hospitals of Udupi and Mangalore districts. Descriptive survey design was used to conduct the study. Subjects were selected by using purposive sampling. Data were gathered by administering background proforma and General Health questionnaire. Severe distress was experienced by 0.9% of nurses and 5.6% had some evidence of distress. Subjects who did not have any distress were 93.5%. No significant association between psychiatric morbidity in nurses and demographic variables was observed. With regard to work variables significant association is observed between psychiatric morbidity and total years of experience (z=10.67, p=0.03) and experience in current area of work (z=9.43, p=0.02).

Keywords: Psychiatric morbidity, nurse, selected hospitals, working.

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Authors: Fatma Kürüm Varolgüneş, Fatih Canan

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Mardin is one of the unique cities in Turkey with its rich cultural and historical heritage. Mardin’s traditional dwellings have been affected both by natural data such as climate and topography and by cultural data like lifestyle and belief. However, in the new settlements, housing is formed with modern approaches and unsuitable forms clashing with Mardin’s culture and environment. While the city is expanding, traditional textures are ignored. Thus, traditional settlements are losing their identity and are vanishing because of the rapid change and transformation. The main aim of this paper is to determine the physical and social data needed to define the characteristic features of Mardin’s old and new settlements. In this context, based on social and cultural data, old and new settlement formations of Mardin have been investigated from various aspects. During this research, the following methods have been utilized: observations, interviews, public surveys, literature review, as well as site examination via maps, photographs and questionnaire methodology. In conclusion, this paper focuses on how changes in the physical forms of cities affect the typology and the identity of cities, as in the case of Mardin.

Keywords: Urban and local identity, historical city center, traditional settlements, Mardin, Turkey.

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Authors: Esam Jassim

Abstract:

Industries using conventional fossil fuels have an  interest in better understanding the mechanism of particulate  formation during combustion since such is responsible for emission  of undesired inorganic elements that directly impact the atmospheric  pollution level. Fine and ultrafine particulates have tendency to  escape the flue gas cleaning devices to the atmosphere. They also  preferentially collect on surfaces in power systems resulting in  ascending in corrosion inclination, descending in the heat transfer  thermal unit, and severe impact on human health. This adverseness  manifests particularly in the regions of world where coal is the  dominated source of energy for consumption.  This study highlights the behavior of calcium transformation as  mineral grains verses organically associated inorganic components  during pulverized coal combustion. The influence of existing type of  calcium on the coarse, fine and ultrafine mode formation mechanisms  is also presented. The impact of two sub-bituminous coals on particle  size and calcium composition evolution during combustion is to be  assessed. Three mixed blends named Blends 1, 2, and 3 are selected  according to the ration of coal A to coal B by weight. Calcium  percentage in original coal increases as going from Blend 1 to 3.  A mathematical model and a new approach of describing  constituent distribution are proposed. Analysis of experiments of  calcium distribution in ash is also modeled using Poisson distribution.  A novel parameter, called elemental index λ, is introduced as a  measuring factor of element distribution.  Results show that calcium in ash that originally in coal as mineral  grains has index of 17, whereas organically associated calcium  transformed to fly ash shown to be best described when elemental  index λ is 7.  As an alkaline-earth element, calcium is considered the  fundamental element responsible for boiler deficiency since it is the  major player in the mechanism of ash slagging process. The  mechanism of particle size distribution and mineral species of ash  particles are presented using CCSEM and size-segregated ash  characteristics. Conclusions are drawn from the analysis of  pulverized coal ash generated from a utility-scale boiler.

 

Keywords: Calcium transformation, Coal Combustion, Inorganic Element, Poisson distribution.

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Authors: Asif Husain, Majid Matouq Assas

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In recent years demolished concrete waste handling and management is the new primary challenging issue faced by the countries all over the world. It is very challenging and hectic problem that has to be tackled in an indigenous manner, it is desirable to completely recycle demolished concrete waste in order to protect natural resources and reduce environmental pollution. In this research paper an experimental study is carried out to investigate the feasibility and recycling of demolished waste concrete for new construction. The present investigation to be focused on recycling demolished waste materials in order to reduce construction cost and resolving housing problems faced by the low income communities of the world. The crushed demolished concrete wastes is segregated by sieving to obtain required sizes of aggregate, several tests were conducted to determine the aggregate properties before recycling it into new concrete. This research shows that the recycled aggregate that are obtained from site make good quality concrete. The compressive strength test results of partial replacement and full recycled aggregate concrete and are found to be higher than the compressive strength of normal concrete with new aggregate.

Keywords: Demolished, concrete waste, recycle, new concrete, fresh coarse aggregate.

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: Evolutionary Algorithms, Chemical Reaction Optimization, Traveling Salesman, Board Drilling.

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Authors: Yananda Siraphatthada

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The current study was the succession of a previous study on value added of recycling business management. Its aims are to 1) explore conditions on how to increasing value add of Thai recycling business, and 2) exam the implementation of the 3-staged plan (short, medium, and long term), suggested by the former study, to increase value added of the recycling business as immediate mechanisms to accelerate government operation. Quantitative and qualitative methods were utilized in this research. A qualitative research consisted of in-depth interviews and focus group discussions. Responses were obtained from owners of the waste separation plants, and recycle shops, as well as officers in relevant governmental agencies. They were randomly selected via Quota Sampling. Data was analyzed via content analysis. The sample used for quantitative method consisted of 1,274 licensed recycling operators in eight provinces. The operators were randomly stratified via sampling method. Data were analyzed via descriptive statistics frequency, percentage, average (Mean) and standard deviation.The study recommended three-staged plan: short, medium, and long terms. The plan included the development of logistics, the provision of quality market/plants, the amendment of recycling rules/regulation, the restructuring recycling business, the establishment of green-purchasing recycling center, support for the campaigns run by the International Green Purchasing Network (IGPN), conferences/workshops as a public forum to share insights among experts/concern people.

Keywords: Strategies, Value Added, Recycle Business.

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Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez

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It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.

Keywords: Education, evolutionary algorithms, evolution strategies, interactive learning applications.

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Authors: Mohammad Hasan Raouf, Ahmad Rouhani, Mohammad Abedini, Ebrahim Rasooli Anarmarzi

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In this paper the application of a hierarchical fuzzy system (HFS) based on MPSS and SVC in multi-machine environment is studied. Also the effect of communication lines active power variance signal between two ΔP_Tie-line regions, as one of the inputs of hierarchical fuzzy multi-input PSS and SVC (HFMPSS & SVC), on the increase of low frequency oscillation damping is examined. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type PSS. The number of rules grows exponentially with the number of variables in a classic fuzzy system. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. Phasor model of SVC is described and used in this paper. The performances of MPSS and ΔP_Tie-line based HFMPSS and also the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. The efficiency of the proposed model is examined by simulating a four-machine power system. Results show that the proposed method is performing satisfactorily within the whole range of disturbances and reduces the cost of system.

Keywords: Communication lines active power variance signal, Hierarchical fuzzy system (HFS), Multi-input power system stabilizer (MPSS), Static VAR compensator (SVC).

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Authors: Christopher Paterson, Richard Curry, Alan Purvis, Simon Johnson

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Emerging Bio-engineering fields such as Brain Computer Interfaces, neuroprothesis devices and modeling and simulation of neural networks have led to increased research activity in algorithms for the detection, isolation and classification of Action Potentials (AP) from noisy data trains. Current techniques in the field of 'unsupervised no-prior knowledge' biosignal processing include energy operators, wavelet detection and adaptive thresholding. These tend to bias towards larger AP waveforms, AP may be missed due to deviations in spike shape and frequency and correlated noise spectrums can cause false detection. Also, such algorithms tend to suffer from large computational expense. A new signal detection technique based upon the ideas of phasespace diagrams and trajectories is proposed based upon the use of a delayed copy of the AP to highlight discontinuities relative to background noise. This idea has been used to create algorithms that are computationally inexpensive and address the above problems. Distinct AP have been picked out and manually classified from real physiological data recorded from a cockroach. To facilitate testing of the new technique, an Auto Regressive Moving Average (ARMA) noise model has been constructed bases upon background noise of the recordings. Along with the AP classification means this model enables generation of realistic neuronal data sets at arbitrary signal to noise ratio (SNR).

Keywords: Action potential detection, Low SNR, Phase spacediagrams/trajectories, Unsupervised/no-prior knowledge.

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Authors: Madhu Sudan, G. N. Tiwari

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In this paper, an attempt has been made to analyze the effect of wall window orientation on Daylight Illuminance Ratio (DIR) and energy saving in a building known as “SODHA BERS COMPLEX (SBC)” at Varanasi, UP, India. The building has been designed incorporating all passive concepts for thermal comfort as well daylighting concepts to maximize the use of natural daylighting for the occupants in the day to day activities. The annual average DIR and the energy saving has been estimated by using the DIR model for wall window with different orientations under clear sky condition. It has been found that for south oriented window the energy saving per square meter is more compared to the other orientations due to the higher level of solar insolation for the south window in northern hemisphere whereas energy saving potential is minimum for north oriented wall window. The energy saving potential was 26%, 81% and 51% higher for east, south and west oriented window in comparison to north oriented window. The average annual DIR has same trends of variation as the annual energy saving and it is maximum for south oriented window and minimum for north oriented window.

Keywords: Clear sky, Daylight Illuminance Ratio, Energy saving, Wall window.

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Authors: Lakshmi Pujitha Dachuri, Nalini Uppala

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In many applications retransmissions of lost packets are not permitted. OFDM is a multi-carrier modulation scheme having excellent performance which allows overlapping in frequency domain. With OFDM there is a simple way of dealing with multipath relatively simple DSP algorithms.

 In this paper, an image frame is compressed using DWT, and the compressed data is arranged in data vectors, each with equal number of coefficients. These vectors are quantized and binary coded to get the bit steams, which are then packetized and intelligently mapped to the OFDM system. Based on one-bit channel state information at the transmitter, the descriptions in order of descending priority are assigned to the currently good channels such that poorer sub-channels can only affect the lesser important data vectors. We consider only one-bit channel state information available at the transmitter, informing only about the sub-channels to be good or bad. For a good sub-channel, instantaneous received power should be greater than a threshold P_th. Otherwise, the sub-channel is in fading state and considered bad for that batch of coefficients. In order to reduce the system power consumption, the mapped descriptions onto the bad sub channels are dropped at the transmitter. The binary channel state information gives an opportunity to map the bit streams intelligently and to save a reasonable amount of power. By using MAT LAB simulation we can analysis the performance of our proposed scheme, in terms of system energy saving without compromising the received quality in terms of peak signal-noise ratio.

Keywords: Binary channel state, Channel state feedback, DWT-OFDM system, Energy saving, Fading broadcast channel.

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Authors: Cristian Păuna

Abstract:

After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: Algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction.

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Authors: Dixit Garg, S. Luthra, A. Haleem

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During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances and cost performances in the supply chain.

Keywords: Analytical Hierarchy Process (AHP), Green Supply Chain Management, Performance Measures (PM), Sustainability.

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Authors: Hazem M. El-Bakry

Abstract:

In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR signal. To calculate these parameters efficiently, a new model called modified Hopfield neural network is designed. The main achievement of this paper over the work in literature [30] is that the speed of the modified Hopfield neural network is accelerated. This is done by applying cross correlation in the frequency domain between the input values and the input weights. The modified Hopfield neural network can accomplish complex dignals perfectly with out any additinal computation steps. This is a valuable advantage as NMR signals are complex-valued. In addition, a technique called “modified sequential extension of section (MSES)" that takes into account the damping rate of the NMR signal is developed to be faster than that presented in [30]. Simulation results show that the calculation precision of the spectrum improves when MSES is used along with the neural network. Furthermore, MSES is found to reduce the local minimum problem in Hopfield neural networks. Moreover, the performance of the proposed method is evaluated and there is no effect on the performance of calculations when using the modified Hopfield neural networks.

Keywords: Hopfield Neural Networks, Cross Correlation, Nuclear Magnetic Resonance, Magnetic Resonance Spectroscopy, Fast Fourier Transform.

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Authors: Moustafa S. El-Sammany

Abstract:

Flash floods are considered natural disasters that can cause casualties and demolishing of infra structures. The problem is that flash floods, particularly in arid and semi arid zones, take place in very short time. So, it is important to forecast flash floods earlier to its events with a lead time up to 48 hours to give early warning alert to avoid or minimize disasters. The flash flood took place over Wadi Watier - Sinai Peninsula, in October 24th, 2008, has been simulated, investigated and analyzed using the state of the art regional weather model. The Weather Research and Forecast (WRF) model, which is a reliable short term forecasting tool for precipitation events, has been utilized over the study area. The model results have been calibrated with the real data, for the same date and time, of the rainfall measurements recorded at Sorah gauging station. The WRF model forecasted total rainfall of 11.6 mm while the real measured one was 10.8 mm. The calibration shows significant consistency between WRF model and real measurements results.

Keywords: Early warning system, Flash floods forecasting, WadiWatier, WRF model.

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Authors: Nagalingam Arun Prasanth, Ahmed Syed Adnan, S. H. Yeo

Abstract:

Surface topography plays a significant role in the functional performance of engineered parts. It is important to have a control on the surface geometry and understanding on the surface details to get the desired performance. Hence, in the current research contribution, a non-contact micro-texturing technique has been explored and developed. The technique involves ultrasonic excitation of a tool as a prime source of surface texturing for aluminum alloy workpieces. The specimen surface is polished first and is then immersed in a liquid bath containing 10% weight concentration of Ti6Al4V grade 5 spherical powders. A submerged slurry jet is used to recirculate the spherical powders under the ultrasonic horn which is excited at an ultrasonic frequency and amplitude of 40 kHz and 70 µm respectively. The distance between the horn and workpiece surface was remained fixed at 200 µm using a precision control stage. Texturing effects were investigated for different process timings of 1, 3 and 5 s. Thereafter, the specimens were cleaned in an ultrasonic bath for 5 mins to remove loose debris on the surface. The developed surfaces are characterized by optical and contact surface profiler. The optical microscopic images show a texture of circular spots on the workpiece surface indented by titanium spherical balls. Waviness patterns obtained from contact surface profiler supports the texturing effect produced from the proposed technique. Furthermore, water droplet tests were performed to show the efficacy of the proposed technique to develop hydrophilic surfaces and to quantify the texturing effect produced.

Keywords: Surface texturing, surface modification, topography, ultrasonic.

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Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

Abstract:

With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: Dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation; pressure drop.

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

Abstract:

The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications.

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Authors: Amira Shakila Razali, Faridah Lisa Supian, Muhammad Mat Salleh, Suraini Abu Bakar

Abstract:

Water contamination by toxic compound is one of the serious environmental problems today. These toxic compounds mostly originated from industrial effluents, agriculture, natural sources and human waste. These studies focus on modification of multiwalled carbon nanotube (MWCNTs) with nanoparticle of calixarene and explore the possibility of using this modification for the remediation of cadmium in water. The nanocomposites were prepared by dissolving calixarene in chloroform solution as solvent, followed by additional multiwalled carbon nanotube (MWCNTs) then sonication process for 3 hour and fabricated the nanocomposites on substrate by spin coating method. Finally, the nanocomposites were tested on cadmium ion (10 mg/ml). The morphology of nanocomposites was investigated by FESEM showing the formation of calixarene on the outer walls of carbon nanotube and cadmium ion also clearly seen from the micrograph. This formation was supported by using energy dispersive x-ray (EDX). The presence of cadmium ions in the films, leads to some changes in the surface potential and Fourier Transform Infrared spectroscopy (FTIR).The nanocomposites MWCNTs-calixarene have potential for development of sensor for pollutant monitoring and nanoelectronics devices applications.

Keywords: Calixarene, Multiwalled Carbon Nanotubes, Cadmium, Surface Potential.

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