Search results for: dynamic of networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6531

Search results for: dynamic of networks

4611 Study on Resource Allocation of Cloud Operating System Based on Multi-Tenant Data Resource Sharing Technology

Authors: Lin Yunuo, Seow Xing Quan, Burra Venkata Durga Kumar

Abstract:

In this modern era, the cloud operating system is the world trend applied in various industries such as business, healthy, etc. In order to deal with the large capacity of requirements in cloud computing, research come up with multi-tenant cloud computing to maximize the benefits of server providers and clients. However, there are still issues in multi-tenant cloud computing especially regarding resource allocation. Issues such as inefficient resource utilization, large latency, lack of scalability and elasticity and poor data isolation had caused inefficient resource allocation in multi-tenant cloud computing. Without a doubt, these issues prevent multitenancy reaches its best condition. In fact, there are multiple studies conducted to determine the optimal resource allocation to solve these problems these days. This article will briefly introduce the cloud operating system, Multi-tenant cloud computing and resource allocation in cloud computing. It then discusses resource allocation in multi-tenant cloud computing and the current challenges it faces. According to the issue ‘ineffective resource utilization’, we will discuss an efficient dynamic scheduling technique for multitenancy, namely Multi-tenant Dynamic Resource Scheduling Model (MTDRSM). Moreover, there also have some recommendations to improve the shortcoming of this model in this paper’s final section.

Keywords: cloud computing, cloud operation system, multitenancy, resource allocation, utilization of cloud resources

Procedia PDF Downloads 85
4610 A Real-Time Snore Detector Using Neural Networks and Selected Sound Features

Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

Abstract:

Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

Procedia PDF Downloads 207
4609 Dynamic Modeling of the Impact of Chlorine on Aquatic Species in Urban Lake Ecosystem

Authors: Zhiqiang Yan, Chen Fan, Yafei Wang, Beicheng Xia

Abstract:

Urban lakes play an invaluable role in urban water systems such as flood control, water supply, and public recreation. However, over 38% of the urban lakes have suffered from severe eutrophication in China. Chlorine that could remarkably inhibit the growth of phytoplankton in eutrophic, has been widely used in the agricultural, aquaculture and industry in the recent past. However, little information has been reported regarding the effects of chlorine on the lake ecosystem, especially on the main aquatic species.To investigate the ecological response of main aquatic species and system stability to chlorine interference in shallow urban lakes, a mini system dynamic model was developed based on the competition and predation of main aquatic species and total phosphorus circulation. The main species of submerged macrophyte, phytoplankton, zooplankton, benthos, spiroggra and total phosphorus in water and sediment were used as variables in the model,while the interference of chlorine on phytoplankton was represented by an exponential attenuation equation. Furthermore, the eco-exergy expressing the development degree of ecosystem was used to quantify the complexity of the shallow urban lake. The model was validated using the data collected in the Lotus Lake in Guangzhoufrom1 October 2015 to 31 January 2016.The correlation coefficient (R), root mean square error-observations standard deviation ratio (RSR) and index of agreement (IOA) were calculated to evaluate accuracy and reliability of the model.The simulated values showed good qualitative agreement with the measured values of all components. The model results showed that chlorine had a notable inhibitory effect on Microcystis aeruginos,Rachionus plicatilis, Diaphanosoma brachyurum Liévin and Mesocyclops leuckarti (Claus).The outbreak of Spiroggra.spp. inhibited the growth of Vallisneria natans (Lour.) Hara, leading to a gradual decrease of eco-exergy and the breakdown of ecosystem internal equilibria. This study gives important insight into using chlorine to achieve eutrophication control and understand mechanism process.

Keywords: system dynamic model, urban lake, chlorine, eco-exergy

Procedia PDF Downloads 235
4608 Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach

Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

Procedia PDF Downloads 277
4607 Detailed Analysis of Multi-Mode Optical Fiber Infrastructures for Data Centers

Authors: Matej Komanec, Jan Bohata, Stanislav Zvanovec, Tomas Nemecek, Jan Broucek, Josef Beran

Abstract:

With the exponential growth of social networks, video streaming and increasing demands on data rates, the number of newly built data centers rises proportionately. The data centers, however, have to adjust to the rapidly increased amount of data that has to be processed. For this purpose, multi-mode (MM) fiber based infrastructures are often employed. It stems from the fact, the connections in data centers are typically realized within a short distance, and the application of MM fibers and components considerably reduces costs. On the other hand, the usage of MM components brings specific requirements for installation service conditions. Moreover, it has to be taken into account that MM fiber components have a higher production tolerance for parameters like core and cladding diameters, eccentricity, etc. Due to the high demands for the reliability of data center components, the determination of properly excited optical field inside the MM fiber core belongs to the key parameters while designing such an MM optical system architecture. Appropriately excited mode field of the MM fiber provides optimal power budget in connections, leads to the decrease of insertion losses (IL) and achieves effective modal bandwidth (EMB). The main parameter, in this case, is the encircled flux (EF), which should be properly defined for variable optical sources and consequent different mode-field distribution. In this paper, we present detailed investigation and measurements of the mode field distribution for short MM links purposed in particular for data centers with the emphasis on reliability and safety. These measurements are essential for large MM network design. The various scenarios, containing different fibers and connectors, were tested in terms of IL and mode-field distribution to reveal potential challenges. Furthermore, we focused on estimation of particular defects and errors, which can realistically occur like eccentricity, connector shifting or dust, were simulated and measured, and their dependence to EF statistics and functionality of data center infrastructure was evaluated. The experimental tests were performed at two wavelengths, commonly used in MM networks, of 850 nm and 1310 nm to verify EF statistics. Finally, we provide recommendations for data center systems and networks, using OM3 and OM4 MM fiber connections.

Keywords: optical fiber, multi-mode, data centers, encircled flux

Procedia PDF Downloads 375
4606 Seismic Response of Structure Using a Three Degree of Freedom Shake Table

Authors: Ketan N. Bajad, Manisha V. Waghmare

Abstract:

Earthquakes are the biggest threat to the civil engineering structures as every year it cost billions of dollars and thousands of deaths, around the world. There are various experimental techniques such as pseudo-dynamic tests – nonlinear structural dynamic technique, real time pseudo dynamic test and shaking table test method that can be employed to verify the seismic performance of structures. Shake table is a device that is used for shaking structural models or building components which are mounted on it. It is a device that simulates a seismic event using existing seismic data and nearly truly reproducing earthquake inputs. This paper deals with the use of shaking table test method to check the response of structure subjected to earthquake. The various types of shake table are vertical shake table, horizontal shake table, servo hydraulic shake table and servo electric shake table. The goal of this experiment is to perform seismic analysis of a civil engineering structure with the help of 3 degree of freedom (i.e. in X Y Z direction) shake table. Three (3) DOF shaking table is a useful experimental apparatus as it imitates a real time desired acceleration vibration signal for evaluating and assessing the seismic performance of structure. This study proceeds with the proper designing and erection of 3 DOF shake table by trial and error method. The table is designed to have a capacity up to 981 Newton. Further, to study the seismic response of a steel industrial building, a proportionately scaled down model is fabricated and tested on the shake table. The accelerometer is mounted on the model, which is used for recording the data. The experimental results obtained are further validated with the results obtained from software. It is found that model can be used to determine how the structure behaves in response to an applied earthquake motion, but the model cannot be used for direct numerical conclusions (such as of stiffness, deflection, etc.) as many uncertainties involved while scaling a small-scale model. The model shows modal forms and gives the rough deflection values. The experimental results demonstrate shake table as the most effective and the best of all methods available for seismic assessment of structure.

Keywords: accelerometer, three degree of freedom shake table, seismic analysis, steel industrial shed

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4605 Assessing the Effect of Grid Connection of Large-Scale Wind Farms on Power System Small-Signal Angular Stability

Authors: Wenjuan Du, Jingtian Bi, Tong Wang, Haifeng Wang

Abstract:

Grid connection of a large-scale wind farm affects power system small-signal angular stability in two aspects. Firstly, connection of the wind farm brings about the change of load flow and configuration of a power system. Secondly, the dynamic interaction is introduced by the wind farm with the synchronous generators (SGs) in the power system. This paper proposes a method to assess the two aspects of the effect of the wind farm on power system small-signal angular stability. The effect of the change of load flow/system configuration brought about by the wind farm can be examined separately by displacing wind farms with constant power sources, then the effect of the dynamic interaction of the wind farm with the SGs can be also computed individually. Thus, a clearer picture and better understanding on the power system small-signal angular stability as affected by grid connection of the large-scale wind farm are provided. In the paper, an example power system with grid connection of a wind farm is presented to demonstrate the proposed approach.

Keywords: power system small-signal angular stability, power system low-frequency oscillations, electromechanical oscillation modes, wind farms, double fed induction generator (DFIG)

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4604 Dynamic Simulation of a Hybrid Wind Farm with Wind Turbines and Distributed Compressed Air Energy Storage System

Authors: Eronini Iheanyi Umez-Eronini

Abstract:

Most studies and existing implementations of compressed air energy storage (CAES) coupled with a wind farm to overcome intermittency and variability of wind power are based on bulk or centralized CAES plants. A dynamic model of a hybrid wind farm with wind turbines and distributed CAES, consisting of air storage tanks and compressor and expander trains at each wind turbine station, is developed and simulated in MATLAB. An ad hoc supervisory controller, in which the wind turbines are simply operated under classical power optimizing region control while scheduling power production by the expanders and air storage by the compressors, including modulation of the compressor power levels within a control range, is used to regulate overall farm power production to track minute-scale (3-minutes sampling period) TSO absolute power reference signal, over an eight-hour period. Simulation results for real wind data input with a simple wake field model applied to a hybrid plant composed of ten 5-MW wind turbines in a row and ten compatibly sized and configured Diabatic CAES stations show the plant controller is able to track the power demand signal within an error band size on the order of the electrical power rating of a single expander. This performance suggests that much improved results should be anticipated when the global D-CAES control is combined with power regulation for the individual wind turbines using available approaches for wind farm active power control. For standalone power plant fuel electrical efficiency estimate of up to 60%, the round trip electrical storage efficiency computed for the distributed CAES wherein heat generated by running compressors is utilized in the preheat stage of running high pressure expanders while fuel is introduced and combusted before the low pressure expanders, was comparable to reported round trip storage electrical efficiencies for bulk Adiabatic CAES.

Keywords: hybrid wind farm, distributed CAES, diabatic CAES, active power control, dynamic modeling and simulation

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4603 Mobile Traffic Management in Congested Cells using Fuzzy Logic

Authors: A. A. Balkhi, G. M. Mir, Javid A. Sheikh

Abstract:

To cater the demands of increasing traffic with new applications the cellular mobile networks face new changes in deployment in infrastructure for making cellular networks heterogeneous. To reduce overhead processing the densely deployed cells require smart behavior with self-organizing capabilities with high adaptation to the neighborhood. We propose self-organization of unused resources usually excessive unused channels of neighbouring cells with densely populated cells to reduce handover failure rates. The neighboring cells share unused channels after fulfilling some conditional candidature criterion using threshold values so that they are not suffered themselves for starvation of channels in case of any abrupt change in traffic pattern. The cells are classified as ‘red’, ‘yellow’, or ‘green’, as per the available channels in cell which is governed by traffic pattern and thresholds. To combat the deficiency of channels in red cell, migration of unused channels from under-loaded cells, hierarchically from the qualified candidate neighboring cells is explored. The resources are returned back when the congested cell is capable of self-contained traffic management. In either of the cases conditional sharing of resources is executed for enhanced traffic management so that User Equipment (UE) is provided uninterrupted services with high Quality of Service (QoS). The fuzzy logic-based simulation results show that the proposed algorithm is efficiently in coincidence with improved successful handoffs.

Keywords: candidate cell, channel sharing, fuzzy logic, handover, small cells

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4602 The Thinking of Dynamic Formulation of Rock Aging Agent Driven by Data

Authors: Longlong Zhang, Xiaohua Zhu, Ping Zhao, Yu Wang

Abstract:

The construction of mines, railways, highways, water conservancy projects, etc., have formed a large number of high steep slope wounds in China. Under the premise of slope stability and safety, the minimum cost, green and close to natural wound space repair, has become a new problem. Nowadays, in situ element testing and analysis, monitoring, field quantitative factor classification, and assignment evaluation will produce vast amounts of data. Data processing and analysis will inevitably differentiate the morphology, mineral composition, physicochemical properties between rock wounds, by which to dynamically match the appropriate techniques and materials for restoration. In the present research, based on the grid partition of the slope surface, tested the content of the combined oxide of rock mineral (SiO₂, CaO, MgO, Al₂O₃, Fe₃O₄, etc.), and classified and assigned values to the hardness and breakage of rock texture. The data of essential factors are interpolated and normalized in GIS, which formed the differential zoning map of slope space. According to the physical and chemical properties and spatial morphology of rocks in different zones, organic acids (plant waste fruit, fruit residue, etc.), natural mineral powder (zeolite, apatite, kaolin, etc.), water-retaining agent, and plant gum (melon powder) were mixed in different proportions to form rock aging agents. To spray the aging agent with different formulas on the slopes in different sections can affectively age the fresh rock wound, providing convenience for seed implantation, and reducing the transformation of heavy metals in the rocks. Through many practical engineering practices, a dynamic data platform of rock aging agent formula system is formed, which provides materials for the restoration of different slopes. It will also provide a guideline for the mixed-use of various natural materials to solve the complex, non-uniformity ecological restoration problem.

Keywords: data-driven, dynamic state, high steep slope, rock aging agent, wounds

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4601 Troubleshooting Petroleum Equipment Based on Wireless Sensors Based on Bayesian Algorithm

Authors: Vahid Bayrami Rad

Abstract:

In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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4600 Stimulation of Nerve Tissue Differentiation and Development Using Scaffold-Based Cell Culture in Bioreactors

Authors: Simon Grossemy, Peggy P. Y. Chan, Pauline M. Doran

Abstract:

Nerve tissue engineering is the main field of research aimed at finding an alternative to autografts as a treatment for nerve injuries. Scaffolds are used as a support to enhance nerve regeneration. In order to successfully design novel scaffolds and in vitro cell culture systems, a deep understanding of the factors affecting nerve regeneration processes is needed. Physical and biological parameters associated with the culture environment have been identified as potentially influential in nerve cell differentiation, including electrical stimulation, exposure to extracellular-matrix (ECM) proteins, dynamic medium conditions and co-culture with glial cells. The mechanisms involved in driving the cell to differentiation in the presence of these factors are poorly understood; the complexity of each of them raises the possibility that they may strongly influence each other. Some questions that arise in investigating nerve regeneration include: What are the best protein coatings to promote neural cell attachment? Is the scaffold design suitable for providing all the required factors combined? What is the influence of dynamic stimulation on cell viability and differentiation? In order to study these effects, scaffolds adaptable to bioreactor culture conditions were designed to allow electrical stimulation of cells exposed to ECM proteins, all within a dynamic medium environment. Gold coatings were used to make the surface of viscose rayon microfiber scaffolds (VRMS) conductive, and poly-L-lysine (PLL) and laminin (LN) surface coatings were used to mimic the ECM environment and allow the attachment of rat PC12 neural cells. The robustness of the coatings was analyzed by surface resistivity measurements, scanning electron microscope (SEM) observation and immunocytochemistry. Cell attachment to protein coatings of PLL, LN and PLL+LN was studied using DNA quantification with Hoechst. The double coating of PLL+LN was selected based on high levels of PC12 cell attachment and the reported advantages of laminin for neural differentiation. The underlying gold coatings were shown to be biocompatible using cell proliferation and live/dead staining assays. Coatings exhibiting stable properties over time under dynamic fluid conditions were developed; indeed, cell attachment and the conductive power of the scaffolds were maintained over 2 weeks of bioreactor operation. These scaffolds are promising research tools for understanding complex neural cell behavior. They have been used to investigate major factors in the physical culture environment that affect nerve cell viability and differentiation, including electrical stimulation, bioreactor hydrodynamic conditions, and combinations of these parameters. The cell and tissue differentiation response was evaluated using DNA quantification, immunocytochemistry, RT-qPCR and functional analyses.

Keywords: bioreactor, electrical stimulation, nerve differentiation, PC12 cells, scaffold

Procedia PDF Downloads 245
4599 Mathieu Stability of Offshore Buoyant Leg Storage and Regasification Platform

Authors: S. Chandrasekaran, P. A. Kiran

Abstract:

Increasing demand for large-sized Floating, Storage and Regasification Units (FSRUs) for oil and gas industries led to the development of novel geometric form of Buoyant Leg Storage and Regasification Platform (BLSRP). BLSRP consists of a circular deck supported by six buoyant legs placed symmetrically with respect to wave direction. Circular deck is connected to buoyant legs using hinged joints, which restrain transfer of rotational response from the legs to deck and vice-versa. Buoyant legs are connected to seabed using taut moored system with high initial pretension, enabling rigid body motion in vertical plane. Encountered environmental loads induce dynamic tether tension variations, which in turn affect stability of the platform. The present study investigates Mathieu stability of BLSRP under the postulated tether pullout cases by inducing additional tension in the tethers. From the numerical studies carried out, it is seen that postulated tether pullout on any one of the buoyant legs does not result in Mathieu type instability even under excessive tether tension. This is due to the presence of hinged joints, which are capable of dissipating the unbalanced loads to other legs. However, under tether pullout of consecutive buoyant legs, Mathieu-type instability is observed.

Keywords: offshore platforms, stability, postulated failure, dynamic tether tension

Procedia PDF Downloads 179
4598 Fatigue Analysis of Spread Mooring Line

Authors: Chanhoe Kang, Changhyun Lee, Seock-Hee Jun, Yeong-Tae Oh

Abstract:

Offshore floating structure under the various environmental conditions maintains a fixed position by mooring system. Environmental conditions, vessel motions and mooring loads are applied to mooring lines as the dynamic tension. Because global responses of mooring system in deep water are specified as wave frequency and low frequency response, they should be calculated from the time-domain analysis due to non-linear dynamic characteristics. To take into account all mooring loads, environmental conditions, added mass and damping terms at each time step, a lot of computation time and capacities are required. Thus, under the premise that reliable fatigue damage could be derived through reasonable analysis method, it is necessary to reduce the analysis cases through the sensitivity studies and appropriate assumptions. In this paper, effects in fatigue are studied for spread mooring system connected with oil FPSO which is positioned in deep water of West Africa offshore. The target FPSO with two Mbbls storage has 16 spread mooring lines (4 bundles x 4 lines). The various sensitivity studies are performed for environmental loads, type of responses, vessel offsets, mooring position, loading conditions and riser behavior. Each parameter applied to the sensitivity studies is investigated from the effects of fatigue damage through fatigue analysis. Based on the sensitivity studies, the following results are presented: Wave loads are more dominant in terms of fatigue than other environment conditions. Wave frequency response causes the higher fatigue damage than low frequency response. The larger vessel offset increases the mean tension and so it results in the increased fatigue damage. The external line of each bundle shows the highest fatigue damage by the governed vessel pitch motion due to swell wave conditions. Among three kinds of loading conditions, ballast condition has the highest fatigue damage due to higher tension. The riser damping occurred by riser behavior tends to reduce the fatigue damage. The various analysis results obtained from these sensitivity studies can be used for a simplified fatigue analysis of spread mooring line as the reference.

Keywords: mooring system, fatigue analysis, time domain, non-linear dynamic characteristics

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4597 Controlled Shock Response Spectrum Test on Spacecraft Subsystem Using Electrodynamic Shaker

Authors: M. Madheswaran, A. R. Prashant, S. Ramakrishna, V. Ramesh Naidu, P. Govindan, P. Aravindakshan

Abstract:

Shock Response spectrum (SRS) tests are one of the tests that are conducted on some critical systems of spacecraft as part of environmental testing. The SRS tests are conducted to simulate the pyro shocks that occur during launch phases as well as during deployment of spacecraft appendages. Some of the methods to carryout SRS tests are pyro technique method, impact hammer method, drop shock method and using electro dynamic shakers. The pyro technique, impact hammer and drop shock methods are open loop tests, whereas SRS testing using electrodynamic shaker is a controlled closed loop test. SRS testing using electrodynamic shaker offers various advantages such as simple test set up, better controllability and repeatability. However, it is important to devise a a proper test methodology so that safety of the electro dynamic shaker and that of test specimen are not compromised. This paper discusses the challenges that are involved in conducting SRS tests, shaker validation and the necessary precautions to be considered. Approach involved in choosing various test parameters like synthesis waveform, spectrum convergence level, etc., are discussed. A case study of SRS test conducted on an optical payload of Indian Geo stationary spacecraft is presented.

Keywords: maxi-max spectrum, SRS (shock response spectrum), SDOf (single degree of freedom), wavelet synthesis

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4596 Coordinated Interference Canceling Algorithm for Uplink Massive Multiple Input Multiple Output Systems

Authors: Messaoud Eljamai, Sami Hidouri

Abstract:

Massive multiple-input multiple-output (MIMO) is an emerging technology for new cellular networks such as 5G systems. Its principle is to use many antennas per cell in order to maximize the network's spectral efficiency. Inter-cellular interference remains a fundamental problem. The use of massive MIMO will not derogate from the rule. It improves performances only when the number of antennas is significantly greater than the number of users. This, considerably, limits the networks spectral efficiency. In this paper, a coordinated detector for an uplink massive MIMO system is proposed in order to mitigate the inter-cellular interference. The proposed scheme combines the coordinated multipoint technique with an interference-cancelling algorithm. It requires the serving cell to send their received symbols, after processing, decision and error detection, to the interfered cells via a backhaul link. Each interfered cell is capable of eliminating intercellular interferences by generating and subtracting the user’s contribution from the received signal. The resulting signal is more reliable than the original received signal. This allows the uplink massive MIMO system to improve their performances dramatically. Simulation results show that the proposed detector improves system spectral efficiency compared to classical linear detectors.

Keywords: massive MIMO, COMP, interference canceling algorithm, spectral efficiency

Procedia PDF Downloads 147
4595 Elaboration and Characterization of Silver Nanoparticles for Therapeutic and Environmental Applications

Authors: Manel Bouloudenine, Karima Djeddou, Hadjer Ben Manser, Hana Soualah Alila, Mohmed Bououdina

Abstract:

This survey research involves the elaboration and characterization of silver nanoparticles for therapeutic and environmental applications. The silver nanoparticles "Ag NPs" were synthesized by reducing AgNO3 with microwaves. The characterization of nanoparticles was done by using Transmission Electron Microscopy " TEM ", Energy Dispersive Spectroscopy "EDS", Selected Area Electron Diffraction "SEAD", UV-Visible Spectroscopy and Dynamic Light Scattering "DLS". Transmission Electron Microscopy and Electron Diffraction have confirmed the nanoscale, the shape, and the crystalline quality of as synthesized silver nanoparticles. Elementary analysis has proved the purity of Ag NPs and the presence of the Surface Plasmon Resonance phenomenon "SPR". A strong absorption shift was observed in the visible range of the UV-visible spectrum of as synthesized Ag NPs, which indicates the presence of metallic silver. When the strong absorption in the ultraviolet range of the spectrum has revealed the presence of ionic Ag NPs ionic Ag aggregates species. The autocorrelation function measured by the Dynamic Light Scattering has shown a strong monodispersed character of Ag NPs, which is indicated by the presence of a single size population, with a minima and a maxima laying between 40 and 111 nm. Related to other research, our results confirm the performance properties of as synthesized Ag NPs, which allows them to be performing in many technological applications, including therapeutic and environmental ones.

Keywords: silvers nanoparticles, microwaves, EDS, TEM

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4594 Development and Experimental Evaluation of a Semiactive Friction Damper

Authors: Juan S. Mantilla, Peter Thomson

Abstract:

Seismic events may result in discomfort on occupants of the buildings, structural damage or even buildings collapse. Traditional design aims to reduce dynamic response of structures by increasing stiffness, thus increasing the construction costs and the design forces. Structural control systems arise as an alternative to reduce these dynamic responses. A commonly used control systems in buildings are the passive friction dampers, which adds energy dissipation through damping mechanisms induced by sliding friction between their surfaces. Passive friction dampers are usually implemented on the diagonal of braced buildings, but such devices have the disadvantage that are optimal for a range of sliding force and out of that range its efficiency decreases. The above implies that each passive friction damper is designed, built and commercialized for a specific sliding/clamping force, in which the damper shift from a locked state to a slip state, where dissipates energy through friction. The risk of having a variation in the efficiency of the device according to the sliding force is that the dynamic properties of the building can change as result of many factor, even damage caused by a seismic event. In this case the expected forces in the building can change and thus considerably reduce the efficiency of the damper (that is designed for a specific sliding force). It is also evident than when a seismic event occurs the forces in each floor varies in the time what means that the damper's efficiency is not the best at all times. Semi-Active Friction devices adapt its sliding force trying to maintain its motion in the slipping phase as much as possible, because of this, the effectiveness of the device depends on the control strategy used. This paper deals with the development and performance evaluation of a low cost Semiactive Variable Friction Damper (SAVFD) in reduced scale to reduce vibrations of structures subject to earthquakes. The SAVFD consist in a (1) hydraulic brake adapted to (2) a servomotor which is controlled with an (3) Arduino board and acquires accelerations or displacement from (4) sensors in the immediately upper and lower floors and a (5) power supply that can be a pair of common batteries. A test structure, based on a Benchmark structure for structural control, was design and constructed. The SAVFD and the structure are experimentally characterized. A numerical model of the structure and the SAVFD is developed based on the dynamic characterization. Decentralized control algorithms were modeled and later tested experimentally using shaking table test using earthquake and frequency chirp signals. The controlled structure with the SAVFD achieved reductions greater than 80% in relative displacements and accelerations in comparison to the uncontrolled structure.

Keywords: earthquake response, friction damper, semiactive control, shaking table

Procedia PDF Downloads 378
4593 Speech Detection Model Based on Deep Neural Networks Classifier for Speech Emotions Recognition

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

Abstract:

Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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4592 Power Grid Line Ampacity Forecasting Based on a Long-Short-Term Memory Neural Network

Authors: Xiang-Yao Zheng, Jen-Cheng Wang, Joe-Air Jiang

Abstract:

Improving the line ampacity while using existing power grids is an important issue that electricity dispatchers are now facing. Using the information provided by the dynamic thermal rating (DTR) of transmission lines, an overhead power grid can operate safely. However, dispatchers usually lack real-time DTR information. Thus, this study proposes a long-short-term memory (LSTM)-based method, which is one of the neural network models. The LSTM-based method predicts the DTR of lines using the weather data provided by Central Weather Bureau (CWB) of Taiwan. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed LSTM-based prediction method. A case study that targets the 345 kV power grid of TaiPower in Taiwan is utilized to examine the performance of the proposed method. The simulation results show that the proposed method is useful to provide the information for the smart grid application in the future.

Keywords: electricity dispatch, line ampacity prediction, dynamic thermal rating, long-short-term memory neural network, smart grid

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4591 Experimental Study on the Variation of Young's Modulus of Hollow Clay Brick Obtained from Static and Dynamic Tests

Authors: M. Aboudalle, Le Btth, M. Sari, F. Meftah

Abstract:

In parallel with the appearance of new materials, brick masonry had and still has an essential part of the construction market today, with new technical challenges in designing bricks to meet additional requirements. Being used in structural applications, predicting the performance of clay brick masonry allows a significant cost reduction, in terms of practical experimentation. The behavior of masonry walls depends on the behavior of their elementary components, such as bricks, joints, and coatings. Therefore, it is necessary to consider it at different scales (from the scale of the intrinsic material to the real scale of the wall) and then to develop appropriate models, using numerical simulations. The work presented in this paper focuses on the mechanical characterization of the terracotta material at ambient temperature. As a result, the static Young’s modulus obtained from the flexural test shows different values in comparison with the compression test, as well as with the dynamic Young’s modulus obtained from the Impulse excitation of vibration test. Moreover, the Young's modulus varies according to the direction in which samples are extracted, where the values in the extrusion direction diverge from the ones in the orthogonal directions. Based on these results, hollow bricks can be considered as transversely isotropic bimodulus material.

Keywords: bimodulus material, hollow clay brick, ımpulse excitation of vibration, transversely isotropic material, young’s modulus

Procedia PDF Downloads 197
4590 The Data Quality Model for the IoT based Real-time Water Quality Monitoring Sensors

Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

Abstract:

IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

Procedia PDF Downloads 139
4589 Tomato-Weed Classification by RetinaNet One-Step Neural Network

Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

Abstract:

The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

Procedia PDF Downloads 103
4588 Seismic Behaviour of Bi-Symmetric Buildings

Authors: Yogendra Singh, Mayur Pisode

Abstract:

Many times it is observed that in multi-storeyed buildings the dynamic properties in the two directions are similar due to which there may be a coupling between the two orthogonal modes of the building. This is particularly observed in bi-symmetric buildings (buildings with structural properties and periods approximately equal in the two directions). There is a swapping of vibrational energy between the modes in the two orthogonal directions. To avoid this coupling the draft revision of IS:1893 proposes a minimum separation of more than 15% between the frequencies of the fundamental modes in the two directions. This study explores the seismic behaviour of bi-symmetrical buildings under uniaxial and bi-axial ground motions. For this purpose, three different types of 8 storey buildings symmetric in plan are modelled. The first building has square columns, resulting in identical periods in the two directions. The second building, with rectangular columns, has a difference of 20% in periods in orthogonal directions, and the third building has half of the rectangular columns aligned in one direction and other half aligned in the other direction. The numerical analysis of the seismic response of these three buildings is performed by using a set of 22 ground motions from PEER NGA database and scaled as per FEMA P695 guidelines to represent the same level of intensity corresponding to the Design Basis Earthquake. The results are analyzed in terms of the displacement-time response of the buildings at roof level and corresponding maximum inter-storey drift ratios.

Keywords: bi-symmetric buildings, design code, dynamic coupling, multi-storey buildings, seismic response

Procedia PDF Downloads 241
4587 Preparation, Solid State Characterization of Etraverine Co-Crystals with Improved Solubility for the Treatment of Human Immunodeficiency Virus

Authors: B. S. Muddukrishna, Karthik Aithal, Aravind Pai

Abstract:

Introduction: Preparation of binary cocrystals of Etraverine (ETR) by using Tartaric Acid (TAR) as a conformer was the main focus of this study. Etravirine is a Class IV drug, as per the BCS classification system. Methods: Cocrystals were prepared by slow evaporation technique. A mixture of total 500mg of ETR: TAR was weighed in molar ratios of 1:1 (371.72mg of ETR and 128.27mg of TAR). Saturated solution of Etravirine was prepared in Acetone: Methanol (50:50) mixture in which tartaric acid is dissolved by sonication and then this solution was stirred using a magnetic stirrer until the solvent got evaporated. Shimadzu FTIR – 8300 system was used to acquire the FTIR spectra of the cocrystals prepared. Shimadzu thermal analyzer was used to achieve DSC measurements. X-ray diffractometer was used to obtain the X-ray powder diffraction pattern. Shake flask method was used to determine the equilibrium dynamic solubility of pure, physical mixture and cocrystals of ETR. USP buffer (pH 6.8) containing 1% of Tween 80 was used as the medium. The pure, physical mixture and the optimized cocrystal of ETR were accurately weighed sufficient to maintain the sink condition and were filled in hard gelatine capsules (size 4). Electrolab-Tablet Dissolution tester using basket apparatus at a rotational speed of 50 rpm and USP phosphate buffer (900 mL, pH = 6.8, 37 ˚C) + 1% Tween80 as a media, was used to carry out dissolution. Shimadzu LC-10 series chromatographic system was used to perform the analysis with PDA detector. An Hypersil BDS C18 (150mm ×4.6 mm ×5 µm) column was used for separation with mobile phase comprising of a mixture of ace¬tonitrile and phosphate buffer 20mM, pH 3.2 in the ratio 60:40 v/v. The flow rate was 1.0mL/min and column temperature was set to 30°C. The detection was carried out at 304 nm for ETR. Results and discussions: The cocrystals were subjected to various solid state characterization and the results confirmed the formation of cocrystals. The C=O stretching vibration (1741cm-1) in tartaric acid was disappeared in the cocrystal and the peak broadening of primary amine indicates hydrogen bond formation. The difference in the melting point of cocrystals when compared to pure Etravirine (265 °C) indicates interaction between the drug and the coformer which proves that first ordered transformation i.e. melting endotherm has disappeared. The difference in 2θ values of pure drug and cocrystals indicates the interaction between the drug and the coformer. Dynamic solubility and dissolution studies were also conducted by shake flask method and USP apparatus one respectively and 3.6 fold increase in the dynamic solubility were observed and in-vitro dissolution study shows four fold increase in the solubility for the ETR: TAR (1:1) cocrystals. The ETR: TAR (1:1) cocrystals shows improved solubility and dissolution as compared to the pure drug which was clearly showed by solid state characterization and dissolution studies.

Keywords: dynamic solubility, Etraverine, in vitro dissolution, slurry method

Procedia PDF Downloads 358
4586 Comparison of Computerized Dynamic Posturography and Functional Head Impulse Test Scores after of Hatha Yoga Practice and Resistance-Based Aerobic Exercise in Adult Female Yoga Practitioners

Authors: Çağla Aras, Kübra Bi̇nay, Aysberg Şamil önlü, Mine Baydan Aran, Dicle Aras

Abstract:

The purpose of the present research was to investigate the acute effects of 30-min hatha yoga and 30-min resistance-based aerobic exercise (RBAE) on computerized dynamic posturography (CDP) and functional head impulse test (fHIT) scores in adult female yoga practitioners. To reach this aim, ten participants executed CDP and fHIT three times in total: at rest, after yoga, and after RBAE. The yoga practice lasted a total of 30 minutes, including 25 min of asanas and 5 minutes of savasana. RBAE lasted a total of 30 minutes with an intensity of 70-75% of the heart rate reserve method. When the results were examined, no change was observed in any parameters of the fHIT scores due to resting or exercise implementation. On the contrary, some changes were observed in CDP test results depending on the type of exercise. The post-RBAE somatosensory and visual systems values were higher than resting (p<0.05). The composite balance score derived after RBAE was found to be improved when compared to post-yoga and resting values (p<0.01). Lastly, the post-RBAE vestibular system score was found to be statistically significantly higher than the post-Yoga values. In addition, it was observed that body composition parameters, especially decreasing BW, LBM, PBF, MBF and TBW, were associated with improved postural stability values. According to the results, it can be stated that neither hatha yoga nor resistance-based aerobic exercise has an acute effect on functional vestibulo-ocular reflex. In addition, although there was no change in balance level after yoga, it was observed that RBAE performed at 70-75% of the heart rate reserve and for 30 minutes had positive acute effects on postural stability and balance.

Keywords: hatha yoga, resistance training, aerobic training, high intensity training, computerized dynamic posturography, functional head impulse test

Procedia PDF Downloads 54
4585 Finite Element Analysis of Connecting Rod

Authors: Mohammed Mohsin Ali H., Mohamed Haneef

Abstract:

The connecting rod transmits the piston load to the crank causing the latter to turn, thus converting the reciprocating motion of the piston into a rotary motion of the crankshaft. Connecting rods are subjected to forces generated by mass and fuel combustion. This study investigates and compares the fatigue behavior of forged steel, powder forged and ASTM a 514 steel cold quenched connecting rods. The objective is to suggest for a new material with reduced weight and cost with the increased fatigue life. This has entailed performing a detailed load analysis. Therefore, this study has dealt with two subjects: first, dynamic load and stress analysis of the connecting rod, and second, optimization for material, weight and cost. In the first part of the study, the loads acting on the connecting rod as a function of time were obtained. Based on the observations of the dynamic FEA, static FEA, and the load analysis results, the load for the optimization study was selected. It is the conclusion of this study that the connecting rod can be designed and optimized under a load range comprising tensile load and compressive load. Tensile load corresponds to 360o crank angle at the maximum engine speed. The compressive load is corresponding to the peak gas pressure. Furthermore, the existing connecting rod can be replaced with a new connecting rod made of ASTM a 514 steel cold quenched that is 12% lighter and 28% cheaper.

Keywords: connecting rod, ASTM a514 cold quenched material, static analysis, fatigue analysis, stress life approach

Procedia PDF Downloads 300
4584 Refined Edge Detection Network

Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

Abstract:

Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

Procedia PDF Downloads 102
4583 High Strain Rate Behavior of Harmonic Structure Designed Pure Nickel: Mechanical Characterization Microstructure Analysis and 3D Modelisation

Authors: D. Varadaradjou, H. Kebir, J. Mespoulet, D. Tingaud, S. Bouvier, P. Deconick, K. Ameyama, G. Dirras

Abstract:

The development of new architecture metallic alloys with controlled microstructures is one of the strategic ways for designing materials with high innovation potential and, particularly, with improved mechanical properties as required for structural materials. Indeed, unlike conventional counterparts, metallic materials having so-called harmonic structure displays strength and ductility synergy. The latter occurs due to a unique microstructure design: a coarse grain structure surrounded by a 3D continuous network of ultra-fine grain known as “core” and “shell,” respectively. In the present study, pure harmonic-structured (HS) Nickel samples were processed via controlled mechanical milling and followed by spark plasma sintering (SPS). The present work aims at characterizing the mechanical properties of HS pure Nickel under room temperature dynamic loading through a Split Hopkinson Pressure Bar (SHPB) test and the underlying microstructure evolution. A stopper ring was used to maintain the strain at a fixed value of about 20%. Five samples (named B1 to B5) were impacted using different striker bar velocities from 14 m/s to 28 m/s, yielding strain rate in the range 4000-7000 s-1. Results were considered until a 10% deformation value, which is the deformation threshold for the constant strain rate assumption. The non-deformed (INIT – post-SPS process) and post-SHPB microstructure (B1 to B5) were investigated by EBSD. It was observed that while the strain rate is increased, the average grain size within the core decreases. An in-depth analysis of grains and grain boundaries was made to highlight the thermal (such as dynamic recrystallization) or mechanical (such as grains fragmentation by dislocation) contribution within the “core” and “shell.” One of the most widely used methods for determining the dynamic behavior of materials is the SHPB technique developed by Kolsky. A 3D simulation of the SHPB test was created through ABAQUS in dynamic explicit. This 3D simulation allows taking into account all modes of vibration. An inverse approach was used to identify the material parameters from the equation of Johnson-Cook (JC) by minimizing the difference between the numerical and experimental data. The JC’s parameters were identified using B1 and B5 samples configurations. Predictively, identified parameters of JC’s equation shows good result for the other sample configuration. Furthermore, mean rise of temperature within the harmonic Nickel sample can be obtained through ABAQUS and show an elevation of about 35°C for all fives samples. At this temperature, a thermal mechanism cannot be activated. Therefore, grains fragmentation within the core is mainly due to mechanical phenomena for a fixed final strain of 20%.

Keywords: 3D simulation, fragmentation, harmonic structure, high strain rate, Johnson-cook model, microstructure

Procedia PDF Downloads 231
4582 A Holistic Approach of Cross-Cultural Management with Insight from Neuroscience

Authors: Mai Nguyen-Phuong-Mai

Abstract:

This paper incorporates insight from various models, studies and disciplines to construct a framework called the Inverted Pyramid Model. It is argued that such a framework has several advantages: (1) it reduces the shortcomings of the problem-focused approach that dominates the mainstream theories of cross-cultural management. With contributing insight from neuroscience, it suggests that training in business cross-cultural awareness should start with potential synergy emerged from differences instead of the traditional approach that focuses on the liability of foreigners and negative consequences of cultural distance. (2) The framework supports a dynamic and holistic way of analyzing cultural diversity by analyzing four major cultural units (global, national, organizational and group culture). (3) The framework emphasizes the role of individuals –an aspect of culture that is often ignored or regarded as a non-issue in the traditional approach. It is based on the notion that people don’t do business with a country, but work (in)directly with a unique person. And it is at this individual level that culture is made, personally, dynamically, and contextually. Insight from neuroscience provides significant evidence that a person can develop a multicultural mind, confirm and contradict, follow and reshape a culture, even when (s)he was previously an outsider to this culture. With this insight, the paper proposes a revision of the old adage (Think global – Act local) and change it into Think global – Plan local – Act individual.

Keywords: static–dynamic paradigm, cultural diversity, multicultural mind, neuroscience

Procedia PDF Downloads 129