Search results for: complexity sciences
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2529

Search results for: complexity sciences

2049 Comparison of Seismic Retrofitting Methods for Existing Foundations in Seismological Active Regions

Authors: Peyman Amini Motlagh, Ali Pak

Abstract:

Seismic retrofitting of important structures is essential in seismological active zones. The importance is doubled when it comes to some buildings like schools, hospitals, bridges etc. because they are required to continue their serviceability even after a major earthquake. Generally, seismic retrofitting codes have paid little attention to retrofitting of foundations due to its construction complexity. In this paper different methods for seismic retrofitting of tall buildings’ foundations will be discussed and evaluated. Foundations are considered in three different categories. First, foundations those are in danger of liquefaction of their underlying soil. Second, foundations located on slopes in seismological active regions. Third, foundations designed according to former design codes and may show structural defects under earthquake loads. After describing different methods used in different countries for retrofitting of the existing foundations in seismological active regions, comprehensive comparison between these methods with regard to the above mentioned categories is carried out. This paper gives some guidelines to choose the best method for seismic retrofitting of tall buildings’ foundations in retrofitting projects.

Keywords: existing foundation, landslide, liquefaction, seismic retrofitting

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2048 Development of a Decision-Making Method by Using Machine Learning Algorithms in the Early Stage of School Building Design

Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

Procedia PDF Downloads 44
2047 Process Driven Architecture For The ‘Lessons Learnt’ Knowledge Sharing Framework: The Case Of A ‘Lessons Learnt’ Framework For KOC

Authors: Rima Al-Awadhi, Abdul Jaleel Tharayil

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On a regular basis, KOC engages into various types of Projects. However, due to very nature and complexity involved, each project experience generates a lot of ‘learnings’ that need to be factored into while drafting a new contract and thus avoid repeating the same mistakes. But, many a time these learnings are localized and remain as tacit leading to scope re-work, larger cycle time, schedule overrun, adjustment orders and claims. Also, these experiences are not readily available to new employees leading to steep learning curve and longer time to competency. This is to share our experience in designing and implementing a process driven architecture for the ‘lessons learnt’ knowledge sharing framework in KOC. It high-lights the ‘lessons learnt’ sharing process adopted, integration with the organizational processes, governance framework, the challenges faced and learning from our experience in implementing a ‘lessons learnt’ framework.

Keywords: lessons learnt, knowledge transfer, knowledge sharing, successful practices, Lessons Learnt Workshop, governance framework

Procedia PDF Downloads 558
2046 A Network-Theorical Perspective on Music Analysis

Authors: Alberto Alcalá-Alvarez, Pablo Padilla-Longoria

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The present paper describes a framework for constructing mathematical networks encoding relevant musical information from a music score for structural analysis. These graphs englobe statistical information about music elements such as notes, chords, rhythms, intervals, etc., and the relations among them, and so become helpful in visualizing and understanding important stylistic features of a music fragment. In order to build such networks, musical data is parsed out of a digital symbolic music file. This data undergoes different analytical procedures from Graph Theory, such as measuring the centrality of nodes, community detection, and entropy calculation. The resulting networks reflect important structural characteristics of the fragment in question: predominant elements, connectivity between them, and complexity of the information contained in it. Music pieces in different styles are analyzed, and the results are contrasted with the traditional analysis outcome in order to show the consistency and potential utility of this method for music analysis.

Keywords: computational musicology, mathematical music modelling, music analysis, style classification

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2045 Phytoadaptation in Desert Soil Prediction Using Fuzzy Logic Modeling

Authors: S. Bouharati, F. Allag, M. Belmahdi, M. Bounechada

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In terms of ecology forecast effects of desertification, the purpose of this study is to develop a predictive model of growth and adaptation of species in arid environment and bioclimatic conditions. The impact of climate change and the desertification phenomena is the result of combined effects in magnitude and frequency of these phenomena. Like the data involved in the phytopathogenic process and bacteria growth in arid soil occur in an uncertain environment because of their complexity, it becomes necessary to have a suitable methodology for the analysis of these variables. The basic principles of fuzzy logic those are perfectly suited to this process. As input variables, we consider the physical parameters, soil type, bacteria nature, and plant species concerned. The result output variable is the adaptability of the species expressed by the growth rate or extinction. As a conclusion, we prevent the possible strategies for adaptation, with or without shifting areas of plantation and nature adequate vegetation.

Keywords: climate changes, dry soil, phytopathogenicity, predictive model, fuzzy logic

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2044 A Review of HVDC Modular Multilevel Converters Subjected to DC and AC Faults

Authors: Jude Inwumoh, Adam P. R. Taylor, Kosala Gunawardane

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Modular multilevel converters (MMC) exhibit a highly scalable and modular characteristic with good voltage/power expansion, fault tolerance capability, low output harmonic content, good redundancy, and a flexible front-end configuration. Fault detection, location, and isolation, as well as maintaining fault ride-through (FRT), are major challenges to MMC reliability and power supply sustainability. Different papers have been reviewed to seek the best MMC configuration with fault capability. DC faults are the most common fault, while the probability that AC fault occurs in a modular multilevel converter (MCC) is low; though, AC faults consequence are severe. This paper reviews several MMC topologies and modulation techniques in tackling faults. These fault control strategies are compared based on cost, complexity, controllability, and power loss. A meshed network of half-bridge (HB) MMC topology was optimal in rendering fault ride through than any other MMC topologies but only when combined with DC circuit breakers (CBS), AC CBS, and fault current limiters (FCL).

Keywords: MMC-HVDC, DC faults, fault current limiters, control scheme

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2043 Navigating the Complexity of Guillain-Barré Syndrome and Miller Fisher Syndrome Overlap Syndrome: A Pediatric Case Report

Authors: Kamal Chafiq, Youssef Hadzine, Adel Elmekkaoui, Othmane Benlenda, Houssam Rajad, Soukaina Wakrim, Hicham Nassik

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Guillain-Barré syndrome/Miller Fishe syndrome (GBS/MFS) overlap syndrome is an extremely rare variant of Guillain-Barré syndrome (GBS) in which Miller Fisher syndrome (MFS) coexists with other characteristics of GBS, such as limb weakness, paresthesia, and facial paralysis. We report the clinical case of a 12-year-old patient, with no pathological history, who acutely presents with ophthalmoplegia, areflexia, facial diplegia, and swallowing and phonation disorders, followed by progressive, descending, and symmetrical paresis affecting first the upper limbs and then the lower limbs. An albuminocytological dissociation was found in the cerebrospinal fluid study. Magnetic resonance imaging of the spinal cord showed enhancement and thickening of the cauda equina roots. The patient was treated with immunoglobulins with a favorable clinical outcome.

Keywords: Guillain-Barré syndrome, Miller Fisher syndrome, overlap syndrome, anti-GQ1b antibodies

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2042 AM/E/c Queuing Hub Maximal Covering Location Model with Fuzzy Parameter

Authors: M. H. Fazel Zarandi, N. Moshahedi

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The hub location problem appears in a variety of applications such as medical centers, firefighting facilities, cargo delivery systems and telecommunication network design. The location of service centers has a strong influence on the congestion at each of them, and, consequently, on the quality of service. This paper presents a fuzzy maximal hub covering location problem (FMCHLP) in which travel costs between any pair of nodes is considered as a fuzzy variable. In order to consider the quality of service, we model each hub as a queue. Arrival rate follows Poisson distribution and service rate follows Erlang distribution. In this paper, at first, a nonlinear mathematical programming model is presented. Then, we convert it to the linear one. We solved the linear model using GAMS software up to 25 nodes and for large sizes due to the complexity of hub covering location problems, and simulated annealing algorithm is developed to solve and test the model. Also, we used possibilistic c-means clustering method in order to find an initial solution.

Keywords: fuzzy modeling, location, possibilistic clustering, queuing

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2041 Adaptive Neuro Fuzzy Inference System Model Based on Support Vector Regression for Stock Time Series Forecasting

Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

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Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

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2040 Active Power Flow Control Using a TCSC Based Backstepping Controller in Multimachine Power System

Authors: Naimi Abdelhamid, Othmane Abdelkhalek

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With the current rise in the demand of electrical energy, present-day power systems which are large and complex, will continue to grow in both size and complexity. Flexible AC Transmission System (FACTS) controllers provide new facilities, both in steady state power flow control and dynamic stability control. Thyristor Controlled Series Capacitor (TCSC) is one of FACTS equipment, which is used for power flow control of active power in electric power system and for increase of capacities of transmission lines. In this paper, a Backstepping Power Flow Controller (BPFC) for TCSC in multimachine power system is developed and tested. The simulation results show that the TCSC proposed controller is capable of controlling the transmitted active power and improving the transient stability when compared with conventional PI Power Flow Controller (PIPFC).

Keywords: FACTS, thyristor controlled series capacitor (TCSC), backstepping, BPFC, PIPFC

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2039 Design Ultra Fast Gate Drive Board for Silicon Carbide MOSFET Applications

Authors: Syakirin O. Yong, Nasrudin A. Rahim, Bilal M. Eid, Buray Tankut

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The aim of this paper is to develop an ultra-fast gate driver for Silicon Carbide (SiC) based switching device applications such as AC/DC DC/AC converters. Wide bandgap semiconductors such as SiC switches are growing rapidly nowadays due to their numerous capabilities such as faster switching, higher power density and higher voltage level. Wide band-gap switches can work properly on high frequencies such 50-250 kHz which is very useful for many power electronic applications such as solar inverters. Increasing the frequency minimizes the output filter size and system complexity however, this causes huge spike between MOSFET’s drain and source leg which leads to the failure of MOSFET if the voltage rating is exceeded. This paper investigates and concludes the optimum design for a gate drive board for SiC MOSFET switches without causing spikes and noises.

Keywords: PV system, lithium-ion, charger, constant current, constant voltage, renewable energy

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2038 Effect of Plasticizer Additives on the Mechanical Properties of Cement Composite: A Molecular Dynamics Analysis

Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular/nanoscale models is demonstrated.

Keywords: cement composite, mechanical properties, molecular dynamics, plasticizer additives

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2037 Comparison of Different Methods to Produce Fuzzy Tolerance Relations for Rainfall Data Classification in the Region of Central Greece

Authors: N. Samarinas, C. Evangelides, C. Vrekos

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The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

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2036 A New Sign Subband Adaptive Filter Based on Dynamic Selection of Subbands

Authors: Mohammad Shams Esfand Abadi, Mehrdad Zalaghi, Reza ebrahimpour

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In this paper, we propose a sign adaptive filter algorithm with the ability of dynamic selection of subband filters which leads to low computational complexity compared with conventional sign subband adaptive filter (SSAF) algorithm. Dynamic selection criterion is based on largest reduction of the mean square deviation at each adaption. We demonstrate that this simple proposed algorithm has the same performance of the conventional SSAF and somewhat faster than it. In the presence of impulsive interferences robustness of the simple proposed algorithm as well as the conventional SSAF and outperform the conventional normalized subband adaptive filter (NSAF) algorithm. Therefore, it is preferred for environments under impulsive interferences. Simulation results are presented to verify these above considerations very well have been achieved.

Keywords: acoustic echo cancellation (AEC), normalized subband adaptive filter (NSAF), dynamic selection subband adaptive filter (DS-NSAF), sign subband adaptive filter (SSAF), impulsive noise, robust filtering

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2035 Traditional Chinese Medicine Treatment for Coronary Heart Disease: a Meta-Analysis

Authors: Yuxi Wang, Xuan Gao

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Traditional Chinese medicine has been used in the treatment of coronary heart disease (CHD) for centuries, and in recent years, the research data on the efficacy of traditional Chinese medicine through clinical trials has gradually increased to explore its real efficacy and internal pharmacology. However, due to the complexity of traditional Chinese medicine prescriptions, the efficacy of each component is difficult to clarify, and pharmacological research is challenging. This study aims to systematically review and clarify the clinical efficacy of traditional Chinese medicine in the treatment of coronary heart disease through a meta-analysis. Based on PubMed, CNKI database, Wanfang data, and other databases, eleven randomized controlled trials and 1091 CHD subjects were included. Two researchers conducted a systematic review of the papers and conducted a meta-analysis supporting the positive therapeutic effect of traditional Chinese medicine in the treatment of CHD.

Keywords: coronary heart disease, Chinese medicine, treatment, meta-analysis

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2034 Spatially Encoded Hyperspectral Compressive Microscope for Broadband VIS/NIR Imaging

Authors: Lukáš Klein, Karel Žídek

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Hyperspectral imaging counts among the most frequently used multidimensional sensing methods. While there are many approaches to capturing a hyperspectral data cube, optical compression is emerging as a valuable tool to reduce the setup complexity and the amount of data storage needed. Hyperspectral compressive imagers have been created in the past; however, they have primarily focused on relatively narrow sections of the electromagnetic spectrum. A broader spectral study of samples can provide helpful information, especially for applications involving the harmonic generation and advanced material characterizations. We demonstrate a broadband hyperspectral microscope based on the single-pixel camera principle. Captured spatially encoded data are processed to reconstruct a hyperspectral cube in a combined visible and near-infrared spectrum (from 400 to 2500 nm). Hyperspectral cubes can be reconstructed with a spectral resolution of up to 3 nm and spatial resolution of up to 7 µm (subject to diffraction) with a high compressive ratio.

Keywords: compressive imaging, hyperspectral imaging, near-infrared spectrum, single-pixel camera, visible spectrum

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2033 Analysis of Q-Learning on Artificial Neural Networks for Robot Control Using Live Video Feed

Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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2032 Presentation of HVA Faults in SONELGAZ Underground Network and Methods of Faults Diagnostic and Faults Location

Authors: I. Touaїbia, E. Azzag, O. Narjes

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Power supply networks are growing continuously and their reliability is getting more important than ever. The complexity of the whole network comprises numerous components that can fail and interrupt the power supply for the end user. Underground distribution systems are normally exposed to permanent faults, due to specific construction characteristics. In these systems, visual inspection cannot be performed. In order to enhance service restoration, accurate fault location techniques must be applied. This paper describes the different faults that affect the underground distribution system of SONELGAZ (National Society of Electricity and Gas of Algeria), and cable fault location procedure with impulse reflection method (TDR), based in the analyses of the cable response of the electromagnetic impulse, allows cable fault prelocation. The results are obtained from real test in the underground distribution feeder from electrical network of energy distribution company of Souk-Ahras, in order to know the influence of cable characteristics in the types and frequency of faults.

Keywords: distribution networks, fault location, TDR, underground cable

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2031 Curriculum Based Measurement and Precision Teaching in Writing Empowerment Enhancement: Results from an Italian Learning Center

Authors: I. Pelizzoni, C. Cavallini, I. Salvaderi, F. Cavallini

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We present the improvement in writing skills obtained by 94 participants (aged between six and 10 years) with special educational needs through a writing enhancement program based on fluency principles. The study was planned and conducted with a single-subject experimental plan for each of the participants, in order to confirm the results in the literature. These results were obtained using precision teaching (PT) methodology to increase the number of written graphemes per minute in the pre- and post-test, by curriculum based measurement (CBM). Results indicated an increase in the number of written graphemes for all participants. The average overall duration of the intervention is 144 minutes in five months of treatment. These considerations have been analyzed taking account of the complexity of the implementation of measurement systems in real operational contexts (an Italian learning center) and important aspects of replicability and cost-effectiveness of such interventions.

Keywords: curriculum based measurement, precision teaching, writing skill, Italian learning center

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2030 Communication Design in Newspapers: A Comparative Study of Graphic Resources in Portuguese and Spanish Publications

Authors: Fátima Gonçalves, Joaquim Brigas, Jorge Gonçalves

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As a way of managing the increasing volume and complexity of information that circulates in the present time, graphical representations are increasingly used, which add meaning to the information presented in communication media, through an efficient communication design. The visual culture itself, driven by technological evolution, has been redefining the forms of communication, so that contemporary visual communication represents a major impact on society. This article presents the results and respective comparative analysis of four publications in the Iberian press, focusing on the formal aspects of newspapers and the space they dedicate to the various communication elements. Two Portuguese newspapers and two Spanish newspapers were selected for this purpose. The findings indicated that the newspapers show a similarity in the use of graphic solutions, which corroborate a visual trend in communication design. The results also reveal that Spanish newspapers are more meticulous with graphic consistency. This study intended to contribute to improving knowledge of the Iberian generalist press.

Keywords: communication design, graphic resources, Iberian press, visual journalism

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2029 Intelligent Software Architecture and Automatic Re-Architecting Based on Machine Learning

Authors: Gebremeskel Hagos Gebremedhin, Feng Chong, Heyan Huang

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Software system is the combination of architecture and organized components to accomplish a specific function or set of functions. A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture. The main aim of this paper is to analyze prove architecture design and automatic re-architecting using machine learning. Intelligence software architecture and automatic re-architecting process is reorganizing in to more suitable one of the software organizational structure system using the user access dataset for creating relationship among the components of the system. The 3-step approach of data mining was used to analyze effective recovery, transformation and implantation with the use of clustering algorithm. Therefore, automatic re-architecting without changing the source code is possible to solve the software complexity problem and system software reuse.

Keywords: intelligence, software architecture, re-architecting, software reuse, High level design

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2028 Growth of Public Listed Construction Companies in Malaysia

Authors: M. C. Theong, F. L. Ang, G. J. Muga

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Growth of firms is influenced by environmental changes such as the global and national economy. On the other hand, it indicates the economic situation of a country. Therefore, it is imperative for firms to be sensitive to changes and to stay competitive and remain compatible with the environment. The Malaysian construction industry is prone to environmental changes due to its complexity. In order to survive in the construction industry, focus on the development of the firms themselves to achieve long term their long term goals is vital besides maximizing profits. The objective of this paper is to measure growth of the public listed construction companies in Malaysia and to investigate the development of the companies with highest, moderate and lowest growth. Growth is measured based on the companies' sales between year 2008 and 2012 collected via secondary data collection method. Findings show that the highest average growth created is 235.20 % while the lowest average growth is -22.75%. The construction companies remained active in the construction industry by implementing different sets of strategies and involving in several types of construction projects.

Keywords: growth, Malaysian construction industry, public listed companies, sales

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2027 Executive Function and Attention Control in Bilingual and Monolingual Children: A Systematic Review

Authors: Zihan Geng, L. Quentin Dixon

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It has been proposed that early bilingual experience confers a number of advantages in the development of executive control mechanisms. Although the literature provides empirical evidence for bilingual benefits, some studies also reported null or mixed results. To make sense of these contradictory findings, the current review synthesize recent empirical studies investigating bilingual effects on children’s executive function and attention control. The publication time of the studies included in the review ranges from 2010 to 2017. The key searching terms are bilingual, bilingualism, children, executive control, executive function, and attention. The key terms were combined within each of the following databases: ERIC (EBSCO), Education Source, PsycINFO, and Social Science Citation Index. Studies involving both children and adults were also included but the analysis was based on the data generated only by the children group. The initial search yielded 137 distinct articles. Twenty-eight studies from 27 articles with a total of 3367 participants were finally included based on the selection criteria. The selective studies were then coded in terms of (a) the setting (i.e., the country where the data was collected), (b) the participants (i.e., age and languages), (c) sample size (i.e., the number of children in each group), (d) cognitive outcomes measured, (e) data collection instruments (i.e., cognitive tasks and tests), and (f) statistic analysis models (e.g., t-test, ANOVA). The results show that the majority of the studies were undertaken in western countries, mainly in the U.S., Canada, and the UK. A variety of languages such as Arabic, French, Dutch, Welsh, German, Spanish, Korean, and Cantonese were involved. In relation to cognitive outcomes, the studies examined children’s overall planning and problem-solving abilities, inhibition, cognitive complexity, working memory (WM), and sustained and selective attention. The results indicate that though bilingualism is associated with several cognitive benefits, the advantages seem to be weak, at least, for children. Additionally, the nature of the cognitive measures was found to greatly moderate the results. No significant differences are observed between bilinguals and monolinguals in overall planning and problem-solving ability, indicating that there is no bilingual benefit in the cooperation of executive function components at an early age. In terms of inhibition, the mixed results suggest that bilingual children, especially young children, may have better conceptual inhibition measured in conflict tasks, but not better response inhibition measured by delay tasks. Further, bilingual children showed better inhibitory control to bivalent displays, which resembles the process of maintaining two language systems. The null results were obtained for both cognitive complexity and WM, suggesting no bilingual advantage in these two cognitive components. Finally, findings on children’s attention system associate bilingualism with heightened attention control. Together, these findings support the hypothesis of cognitive benefits for bilingual children. Nevertheless, whether these advantages are observable appears to highly depend on the cognitive assessments. Therefore, future research should be more specific about the cognitive outcomes (e.g., the type of inhibition) and should report the validity of the cognitive measures consistently.

Keywords: attention, bilingual advantage, children, executive function

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2026 Using Wearable Technology to Monitor Workers’ Stress for Construction Safety: A Conceptual Framework

Authors: Namhun Lee, Seong Jin Kim

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The construction industry represents one of the largest industries in the United States, yet it continues to face several occupational health and safety challenges. Many workers on construction sites are suffering from extended exposure to stressful situations such as poor and hazardous work environments and task complexity. Stress can be commonly defined as a feeling of emotional or physical tension, which can easily impact construction safety and result in a higher rate of job-related injuries in the construction industry. Physiological signals transmitted from wearable biosensors can be used to detect excessive stress. Therefore, workers’ stress should be detected and mitigated to prevent any type of serious incident or accident proactively. By doing this, construction productivity, as well as job satisfaction, would also be improved in the construction industry. To establish a foundation in this field of research, a conceptual framework for using wearable technology for construction safety has been developed for continuous and automatic monitoring of worker’s stress. The conceptual framework will serve as a foothold in future studies on the application of wearable technology for construction safety.

Keywords: construction safety, occupational stress, stress monitoring, wearable biosensors

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2025 Evaluation of the Environmental Risk from the Co-Deposition of Waste Rock Material and Fly Ash

Authors: A. Mavrikos, N. Petsas, E. Kaltsi, D. Kaliampakos

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The lignite-fired power plants in the Western Macedonia Lignite Center produce more than 8 106 t of fly ash per year. Approximately 90% of this quantity is used for restoration-reclamation of exhausted open-cast lignite mines and slope stabilization of the overburden. The purpose of this work is to evaluate the environmental behavior of the mixture of waste rock and fly ash that is being used in the external deposition site of the South Field lignite mine. For this reason, a borehole was made within the site and 86 samples were taken and subjected to chemical analyses and leaching tests. The results showed very limited leaching of trace elements and heavy metals from this mixture. Moreover, when compared to the limit values set for waste acceptable in inert waste landfills, only few excesses were observed, indicating only minor risk for groundwater pollution. However, due to the complexity of both the leaching process and the contaminant pathway, more boreholes and analyses should be made in nearby locations and a systematic groundwater monitoring program should be implemented both downstream and within the external deposition site.

Keywords: co-deposition, fly ash, leaching tests, lignite, waste rock

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2024 Framework for Socio-Technical Issues in Requirements Engineering for Developing Resilient Machine Vision Systems Using Levels of Automation through the Lifecycle

Authors: Ryan Messina, Mehedi Hasan

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This research is to examine the impacts of using data to generate performance requirements for automation in visual inspections using machine vision. These situations are intended for design and how projects can smooth the transfer of tacit knowledge to using an algorithm. We have proposed a framework when specifying machine vision systems. This framework utilizes varying levels of automation as contingency planning to reduce data processing complexity. Using data assists in extracting tacit knowledge from those who can perform the manual tasks to assist design the system; this means that real data from the system is always referenced and minimizes errors between participating parties. We propose using three indicators to know if the project has a high risk of failing to meet requirements related to accuracy and reliability. All systems tested achieved a better integration into operations after applying the framework.

Keywords: automation, contingency planning, continuous engineering, control theory, machine vision, system requirements, system thinking

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2023 The Narrative Coherence of Autistic Children’s Accounts of an Experienced Event over Time

Authors: Fuming Yang, Telma Sousa Almeida, Xinyu Li, Yunxi Deng, Heying Zhang, Michael E. Lamb

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Twenty-seven children aged 6-15 years with autism spectrum disorder (ASD) and 32 typically developing children were questioned about their participation in a set of activities after a two-week delay and again after a two-month delay, using a best-practice interview protocol. This paper assessed the narrative coherence of children’s reports based on key story grammar elements and temporal features included in their accounts of the event. Results indicated that, over time, both children with ASD and typically developing (TD) children decreased their narrative coherence. Children with ASD were no different from TD peers with regards to story length and syntactic complexity. However, they showed significantly less coherence than TD children. They were less likely to use the gist of the story to organize their narrative coherence. Interviewer prompts influenced children’s narrative coherence. The findings indicated that children with ASD could provide meaningful and reliable testimony about an event they personally experienced, but the narrative coherence of their reports deteriorates over time and is affected by interviewer prompts.

Keywords: autism spectrum disorders, delay, eyewitness testimony, narrative coherence

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2022 A Review on Water Models of Surface Water Environment

Authors: Shahbaz G. Hassan

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Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods.

Keywords: empirical models, mathematical, statistical, water quality

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2021 Sustainable Building Design for Energy Efficiency and Healthier Electromagnetic Environment

Authors: Riadh Habash, Kristina Djukic, Gandhi Habash

Abstract:

Sustainable design is one of the emerging milestones in building construction. This concept is defined as buildings that on a yearly average consume as much energy as they generate using renewable energy sources. Realization of sustainable buildings requires a wide range of technologies, systems and solutions with varying degrees of complexity and sophistication, depending upon the location and surrounding environmental conditions. This paper will address not only the role of the above technologies and solutions but will provide solutions to reduce the electromagnetic fields (EMFs) in the building as much as possible so that the occupiers can recover from electro-hyper-sensitivity, if any. The objective is to maximize energy efficiency, optimize occupant comfort, reduce dependency on the grid and provide safer and healthier EMF environment especially for hypersensitive people. Creative architectural and engineering solutions that capitalize on the design of energy efficient technologies; combined cooling, heating and power (CCHP) microgrid (MG); and EMF mitigation will be presented.

Keywords: sustainable buildings, energy efficiency, thermal simulation, electromagnetic environment

Procedia PDF Downloads 281
2020 Using of Particle Swarm Optimization for Loss Minimization of Vector-Controlled Induction Motors

Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

Abstract:

This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

Procedia PDF Downloads 616