Search results for: ab initio coupled cluster methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16620

Search results for: ab initio coupled cluster methods

16500 Two-Photon Ionization of Silver Clusters

Authors: V. Paployan, K. Madoyan, A. Melikyan, H. Minassian

Abstract:

Resonant two-photon ionization (TPI) is a valuable technique for the study of clusters due to its ultrahigh sensitivity. The comparison of the observed TPI spectra with results of calculations allows to deduce important information on the shape, rotational and vibrational temperatures of the clusters with high accuracy. In this communication we calculate the TPI cross-section for pump-probe scheme in Ag neutral cluster. The pump photon energy is chosen to be close to the surface plasmon (SP) energy of cluster in dielectric media. Since the interband transition energy in Ag exceeds the SP resonance energy, the main contribution into the TPI comes from the latter. The calculations are performed by separating the coordinates of electrons corresponding to the collective oscillations and the individual motion that allows to take into account the resonance contribution of excited SP oscillations. It is shown that the ionization cross section increases by two orders of magnitude if the energy of the pump photon matches the surface plasmon energy in the cluster.

Keywords: resonance enhancement, silver clusters, surface plasmon, two-photon ionization

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16499 Chemometric Determination of the Geographical Origin of Milk Samples in Malaysia

Authors: Shima Behkami, Nor Shahirul Umirah Idris, Sharifuddin Md. Zain, Kah Hin Low, Mehrdad Gholami, Nima A. Behkami, Ahmad Firdaus Kamaruddin

Abstract:

In this work, Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Isotopic Ratio Mass Spectrometry (IRMS) and Ultrasound Milko Tester were used to study milk samples obtained from various geographical locations in Malaysia. ICP-MS was used to determine the concentration of trace elements in milk, water and soil samples obtained from seven dairy farms at different geographical locations in peninsular Malaysia. IRMS was used to analyze the milk samples for isotopic ratios of δ13C, 15N and 18O. Nutritional parameters in the milk samples were determined using an ultrasound milko tester. Data obtained from these measurements were evaluated by Principal Component Analysis (PCA) and Hierarchical Analysis (HA) as a preliminary step in determining geographical origin of these milk samples. It is observed that the isotopic ratios and a number of the nutritional parameters are responsible for the discrimination of the samples. It was also observed that it is possible to determine the geographical origin of these milk samples solely by the isotopic ratios of δ13C, 15N and 18O. The accuracy of the geographical discrimination is demonstrated when several milk samples from a milk factory taken from one of the regions under study were appropriately assigned to the correct PCA cluster.

Keywords: inductively coupled plasma mass spectroscopy ICP-MS, isotope ratio mass spectroscopy IRMS, ultrasound, principal component analysis, hierarchical analysis, geographical origin, milk

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16498 Estimation of Rare and Clustered Population Mean Using Two Auxiliary Variables in Adaptive Cluster Sampling

Authors: Muhammad Nouman Qureshi, Muhammad Hanif

Abstract:

Adaptive cluster sampling (ACS) is specifically developed for the estimation of highly clumped populations and applied to a wide range of situations like animals of rare and endangered species, uneven minerals, HIV patients and drug users. In this paper, we proposed a generalized semi-exponential estimator with two auxiliary variables under the framework of ACS design. The expressions of approximate bias and mean square error (MSE) of the proposed estimator are derived. Theoretical comparisons of the proposed estimator have been made with existing estimators. A numerical study is conducted on real and artificial populations to demonstrate and compare the efficiencies of the proposed estimator. The results indicate that the proposed generalized semi-exponential estimator performed considerably better than all the adaptive and non-adaptive estimators considered in this paper.

Keywords: auxiliary information, adaptive cluster sampling, clustered populations, Hansen-Hurwitz estimation

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16497 A Fuzzy Kernel K-Medoids Algorithm for Clustering Uncertain Data Objects

Authors: Behnam Tavakkol

Abstract:

Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters.

Keywords: clustering algorithm, fuzzy methods, kernel k-medoids, uncertain data

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16496 The Effect of Hypertrophy Strength Training Using Traditional Set vs. Cluster Set on Maximum Strength and Sprinting Speed

Authors: Bjornar Kjellstadli, Shaher A. I. Shalfawi

Abstract:

The aim of this study was to investigate the effect of strength training Cluster set-method compared to traditional set-method 30 m sprinting time and maximum strength in squats and bench-press. Thirteen Physical Education students, 7 males and 6 females between the age of 19-28 years old were recruited. The students were random divided in three groups. Traditional set group (TSG) consist of 2 males and 2 females aged (±SD) (22.3 ± 1.5 years), body mass (79.2 ± 15.4 kg) and height (177.5 ± 11.3 cm). Cluster set group (CSG) consist of 3 males and 2 females aged (22.4 ± 3.29 years), body mass (81.0 ± 24.0 kg) and height (179.2 ± 11.8 cm) and a control group (CG) consist of 2 males and 2 females aged (21.5 ± 2.4 years), body mass (82.1 ± 17.4 kg) and height (175.5 ± 6.7 cm). The intervention consisted of performing squat and bench press at 70% of 1RM (twice a week) for 8 weeks using 10 repetition and 4 sets. Two types of strength-training methods were used , cluster set (CS) where the participants (CSG) performed 2 reps 5 times with a 10 s recovery in between reps and 50 s recovery between sets, and traditional set (TS) where the participants (TSG) performed 10 reps each set with 90 s recovery in between sets. The pre-tests and post-tests conducted were 1 RM in both squats and bench press, and 10 and 30 m sprint time. The 1RM test were performed with Eleiko XF barbell (20 kg), Eleiko weight plates, rack and bench from Hammerstrength. The speed test was measured with the Brower speed trap II testing system (Brower Timing Systems, Utah, USA). The participants received an individualized training program based on the pre-test of the 1RM. In addition, a mid-term test of 1RM was carried out to adjust training intensity. Each training session were supervised by the researchers. Beast sensors (Milano, Italy) were also used to monitor and quantify the training load for the participants. All groups had a statistical significant improvement in bench press 1RM (TSG 1RM from 56.3 ± 28.9 to 66 ± 28.5 kg; CSG 1RM from 69.8 ± 33.5 to 77.2 ± 34.1 kg and CG 1RM from 67.8 ± 26.6 to 72.2 ± 29.1 kg), whereas only the TSG (1RM from 84.3 ± 26.8 to 114.3 ± 26.5 kg) and CSG (1RM from 100.4 ± 33.9 to 129 ± 35.1 kg) had a statistical significant improvement in Squats 1RM (P < 0.05). However, a between groups examination reveals that there were no marked differences in 1RM squat performance between TSG and CSG (P > 0.05) and both groups had a marked improvements compared to the CG (P < 0.05). On the other hand, no differences between groups were observed in Bench press 1RM. The within groups results indicate that none of the groups had any marked improvement in the distances from 0-10 m and 10-30 m except the CSG which had a notable improvement in the distance from 10-30 m (-0.07 s; P < 0.05). Furthermore, no differences in sprinting abilities were observed between groups. The results from this investigation indicate that traditional set strength training at 70% of 1RM gave close results compared to Cluster set strength training at the same intensity. However, the results indicate that the cluster set had an effect on flying time (10-30 m) indicating that the velocity at which those repetitions were performed could be the explanation factor of this this improvement.

Keywords: physical performance, 1RM, pushing velocity, velocity based training

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16495 Photoreflectance Anisotropy Spectroscopy of Coupled Quantum Wells

Authors: J. V. Gonzalez Fernandez, T. Mozume, S. Gozu, A. Lastras Martinez, L. F. Lastras Martinez, J. Ortega Gallegos, R. E. Balderas Navarro

Abstract:

We report on a theoretical-experimental study of photoreflectance anisotropy (PRA) spectroscopy of coupled double quantum wells. By probing the in-plane interfacial optical anisotropies, we demonstrate that PRA spectroscopy has the capacity to detect and distinguish layers with quantum dimensions. In order to account for the experimental PRA spectra, we have used a theoretical model at k=0 based on a linear electro-optic effect through a piezoelectric shear strain.

Keywords: coupled double quantum well (CDQW), linear electro-optic (LEO) effect, photoreflectance anisotropy (PRA), piezoelectric shear strain

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16494 Verification & Validation of Map Reduce Program Model for Parallel K-Mediod Algorithm on Hadoop Cluster

Authors: Trapti Sharma, Devesh Kumar Srivastava

Abstract:

This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

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16493 Analysing Industry Clustering to Develop Competitive Advantage for Wualai Silver Handicraft

Authors: Khanita Tumphasuwan

Abstract:

The Wualai community of Northern Thailand represents important intellectual and social capital and their silver handicraft products are desirable tourist souvenirs within Chiang Mai Province. This community has been in danger of losing this social and intellectual capital due to the application of an improper tool, the Scottish Enterprise model of clustering. This research aims to analyze and increase its competitive advantages for preventing the loss of social and intellectual capital. To improve the Wualai’s competitive advantage, analysis is undertaken using a Porterian cluster approach, including the diamond model, five forces model and cluster mapping. Research results suggest that utilizing the community’s Buddhist beliefs can foster collaboration between community members and is the only way to improve cluster effectiveness, increase competitive advantage, and in turn conserve the Wualai community.

Keywords: industry clustering, silver handicraft, competitive advantage, intellectual capital, social capital

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16492 A Clustering-Based Approach for Weblog Data Cleaning

Authors: Amine Ganibardi, Cherif Arab Ali

Abstract:

This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

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16491 Modeling of Hydrogen Production by Inductively Coupled Methane Plasma for Input Power Pin=700W

Authors: Abdelatif Gadoum, Djilali Benyoucef, Mouloudj Hadj, Alla Eddine Toubal Maamar, Mohamed Habib Allah Lahoual

Abstract:

Hydrogen occurs naturally in the form of chemical compounds, most often in water and hydrocarbons. The main objective of this study is 2D modeling of hydrogen production in inductively coupled plasma in methane at low pressure. In the present model, we include the motions and the collisions of both neutral and charged particles by considering 19 species (i.e in total ; neutrals, radicals, ions, and electrons), and more than 120 reactions (electron impact with methane, neutral-neutral, neutral-ions and surface reactions). The results show that the rate conversion of methane reach 90% and the hydrogen production is about 30%.

Keywords: hydrogen production, inductively coupled plasma, fluid model, methane plasma

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16490 Modeling of Large Elasto-Plastic Deformations by the Coupled FE-EFGM

Authors: Azher Jameel, Ghulam Ashraf Harmain

Abstract:

In the recent years, the enriched techniques like the extended finite element method, the element free Galerkin method, and the Coupled finite element-element free Galerkin method have found wide application in modeling different types of discontinuities produced by cracks, contact surfaces, and bi-material interfaces. The extended finite element method faces severe mesh distortion issues while modeling large deformation problems. The element free Galerkin method does not have mesh distortion issues, but it is computationally more demanding than the finite element method. The coupled FE-EFGM proves to be an efficient numerical tool for modeling large deformation problems as it exploits the advantages of both FEM and EFGM. The present paper employs the coupled FE-EFGM to model large elastoplastic deformations in bi-material engineering components. The large deformation occurring in the domain has been modeled by using the total Lagrangian approach. The non-linear elastoplastic behavior of the material has been represented by the Ramberg-Osgood model. The elastic predictor-plastic corrector algorithms are used for the evaluation stresses during large deformation. Finally, several numerical problems are solved by the coupled FE-EFGM to illustrate its applicability, efficiency and accuracy in modeling large elastoplastic deformations in bi-material samples. The results obtained by the proposed technique are compared with the results obtained by XFEM and EFGM. A remarkable agreement was observed between the results obtained by the three techniques.

Keywords: XFEM, EFGM, coupled FE-EFGM, level sets, large deformation

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16489 The Effects of Yield and Yield Components of Some Quality Increase Applications on Ismailoglu Grape Type in Turkey

Authors: Yaşar Önal, Aydın Akın

Abstract:

This study was conducted Ismailoglu grape type (Vitis vinifera L.) and its vine which was aged 15 was grown on its own root in a vegetation period of 2013 in Nevşehir province in Turkey. In this research, it was investigated whether the applications of Control (C), 1/3 cluster tip reduction (1/3 CTR), shoot tip reduction (STR), 1/3 CTR + STR, TKI-HUMAS (TKI-HM) (Soil) (S), TKI-HM (Foliar) (F), TKI-HM (S + F), 1/3 CTR + TKI-HM (S), 1/3 CTR + TKI-HM (F), 1/3 CTR + TKI-HM (S+F), STR + TKI-HM (S), STR + TKI-HM (F), STR + TKI-HM (S + F), 1/3 CTR + STR+TKI-HM (S), 1/3 CTR + STR + TKI-HM (F), 1/3 CTR + STR + TKI-HM (S + F) on yield and yield components of Ismailoglu grape type. The results were obtained as the highest fresh grape yield (16.15 kg/vine) with TKI-HM (S), as the highest cluster weight (652.39 g) with 1/3 CTR + STR, as the highest 100 berry weight (419.07 g) with 1/3 CTR + STR + TKI-HM (F), as the highest maturity index (44.06) with 1/3 CTR, as the highest must yield (810.00 ml) with STR + TKI-HM (F), as the highest intensity of L* color (42.04) with TKI-HM (S + F), as the highest intensity of a* color (2.60) with 1/3 CTR + TKI-HM (S), as the highest intensity of b* color (7.16) with 1/3 CTR + TKI-HM (S) applications. To increase the fresh grape yield of Ismailoglu grape type can be recommended TKI-HM (S) application.

Keywords: 1/3 cluster tip reduction, shoot tip reduction, TKI-Humas application, yield and yield components

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16488 Evaluation of Yield and Yield Components of Malaysian Palm Oil Board-Senegal Oil Palm Germplasm Using Multivariate Tools

Authors: Khin Aye Myint, Mohd Rafii Yusop, Mohd Yusoff Abd Samad, Shairul Izan Ramlee, Mohd Din Amiruddin, Zulkifli Yaakub

Abstract:

The narrow base of genetic is the main obstacle of breeding and genetic improvement in oil palm industry. In order to broaden the genetic bases, the Malaysian Palm Oil Board has been extensively collected wild germplasm from its original area of 11 African countries which are Nigeria, Senegal, Gambia, Guinea, Sierra Leone, Ghana, Cameroon, Zaire, Angola, Madagascar, and Tanzania. The germplasm collections were established and maintained as a field gene bank in Malaysian Palm Oil Board (MPOB) Research Station in Kluang, Johor, Malaysia to conserve a wide range of oil palm genetic resources for genetic improvement of Malaysian oil palm industry. Therefore, assessing the performance and genetic diversity of the wild materials is very important for understanding the genetic structure of natural oil palm population and to explore genetic resources. Principal component analysis (PCA) and Cluster analysis are very efficient multivariate tools in the evaluation of genetic variation of germplasm and have been applied in many crops. In this study, eight populations of MPOB-Senegal oil palm germplasm were studied to explore the genetic variation pattern using PCA and cluster analysis. A total of 20 yield and yield component traits were used to analyze PCA and Ward’s clustering using SAS 9.4 version software. The first four principal components which have eigenvalue >1 accounted for 93% of total variation with the value of 44%, 19%, 18% and 12% respectively for each principal component. PC1 showed highest positive correlation with fresh fruit bunch (0.315), bunch number (0.321), oil yield (0.317), kernel yield (0.326), total economic product (0.324), and total oil (0.324) while PC 2 has the largest positive association with oil to wet mesocarp (0.397) and oil to fruit (0.458). The oil palm population were grouped into four distinct clusters based on 20 evaluated traits, this imply that high genetic variation existed in among the germplasm. Cluster 1 contains two populations which are SEN 12 and SEN 10, while cluster 2 has only one population of SEN 3. Cluster 3 consists of three populations which are SEN 4, SEN 6, and SEN 7 while SEN 2 and SEN 5 were grouped in cluster 4. Cluster 4 showed the highest mean value of fresh fruit bunch, bunch number, oil yield, kernel yield, total economic product, and total oil and Cluster 1 was characterized by high oil to wet mesocarp, and oil to fruit. The desired traits that have the largest positive correlation on extracted PCs could be utilized for the improvement of oil palm breeding program. The populations from different clusters with the highest cluster means could be used for hybridization. The information from this study can be utilized for effective conservation and selection of the MPOB-Senegal oil palm germplasm for the future breeding program.

Keywords: cluster analysis, genetic variability, germplasm, oil palm, principal component analysis

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16487 Aggregation of Fractal Aggregates Inside Fractal Cages in Irreversible Diffusion Limited Cluster Aggregation Binary Systems

Authors: Zakiya Shireen, Sujin B. Babu

Abstract:

Irreversible diffusion-limited cluster aggregation (DLCA) of binary sticky spheres was simulated by modifying the Brownian Cluster Dynamics (BCD). We randomly distribute N spheres in a 3D box of size L, the volume fraction is given by Φtot = (π/6)N/L³. We identify NA and NB number of spheres as species A and B in our system both having identical size. In these systems, both A and B particles undergo Brownian motion. Irreversible bond formation happens only between intra-species particles and inter-species interact only through hard-core repulsions. As we perform simulation using BCD we start to observe binary gels. In our study, we have observed that species B always percolate (cluster size equal to L) as expected for the monomeric case and species A does not percolate below a critical ratio which is different for different volume fractions. We will also show that the accessible volume of the system increases when compared to the monomeric case, which means that species A is aggregating inside the cage created by B. We have also observed that for moderate Φtot the system undergoes a transition from flocculation region to percolation region indicated by the change in fractal dimension from 1.8 to 2.5. For smaller ratio of A, it stays in the flocculation regime even though B have already crossed over to the percolation regime. Thus, we observe two fractal dimension in the same system.

Keywords: BCD, fractals, percolation, sticky spheres

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16486 The Influence of Microsilica on the Cluster Cracks' Geometry of Cement Paste

Authors: Maciej Szeląg

Abstract:

The changing nature of environmental impacts, in which cement composites are operating, are causing in the structure of the material a number of phenomena, which result in volume deformation of the composite. These strains can cause composite cracking. Cracks are merging by propagation or intersect to form a characteristic structure of cracks known as the cluster cracks. This characteristic mesh of cracks is crucial to almost all building materials, which are working in service loads conditions. Particularly dangerous for a cement matrix is a sudden load of elevated temperature – the thermal shock. Resulting in a relatively short period of time a large value of a temperature gradient between the outer surface and the material’s interior can result in cracks formation on the surface and in the volume of the material. In the paper, in order to analyze the geometry of the cluster cracks of the cement pastes, the image analysis tools were used. Tested were 4 series of specimens made of two different Portland cement. In addition, two series include microsilica as a substitute for the 10% of the cement. Within each series, specimens were performed in three w/b indicators (water/binder): 0.4; 0.5; 0.6. The cluster cracks were created by sudden loading the samples by elevated temperature of 250°C. Images of the cracked surfaces were obtained via scanning at 2400 DPI. Digital processing and measurements were performed using ImageJ v. 1.46r software. To describe the structure of the cluster cracks three stereological parameters were proposed: the average cluster area - A ̅, the average length of cluster perimeter - L ̅, and the average opening width of a crack between clusters - I ̅. The aim of the study was to identify and evaluate the relationships between measured stereological parameters, and the compressive strength and the bulk density of the modified cement pastes. The tests of the mechanical and physical feature have been carried out in accordance with EN standards. The curves describing the relationships have been developed using the least squares method, and the quality of the curve fitting to the empirical data was evaluated using three diagnostic statistics: the coefficient of determination – R2, the standard error of estimation - Se, and the coefficient of random variation – W. The use of image analysis allowed for a quantitative description of the cluster cracks’ geometry. Based on the obtained results, it was found a strong correlation between the A ̅ and L ̅ – reflecting the fractal nature of the cluster cracks formation process. It was noted that the compressive strength and the bulk density of cement pastes decrease with an increase in the values of the stereological parameters. It was also found that the main factors, which impact on the cluster cracks’ geometry are the cement particles’ size and the general content of the binder in a volume of the material. The microsilica caused the reduction in the A ̅, L ̅ and I ̅ values compared to the values obtained by the classical cement paste’s samples, which is caused by the pozzolanic properties of the microsilica.

Keywords: cement paste, cluster cracks, elevated temperature, image analysis, microsilica, stereological parameters

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16485 2D CFD-PBM Coupled Model of Particle Growth in an Industrial Gas Phase Fluidized Bed Polymerization Reactor

Authors: H. Kazemi Esfeh, V. Akbari, M. Ehdaei, T. N. G. Borhani, A. Shamiri, M. Najafi

Abstract:

In an industrial fluidized bed polymerization reactor, particle size distribution (PSD) plays a significant role in the reactor efficiency evaluation. The computational fluid dynamic (CFD) models coupled with population balance equation (CFD-PBM) have been extensively employed to investigate the flow behavior in the poly-disperse multiphase fluidized bed reactors (FBRs) utilizing ANSYS Fluent code. In this study, an existing CFD-PBM/ DQMOM coupled modeling framework has been used to highlight its potential to analyze the industrial-scale gas phase polymerization reactor. The predicted results reveal an acceptable agreement with the observed industrial data in terms of pressure drop and bed height. The simulated results also indicate that the higher particle growth rate can be achieved for bigger particles. Hence, the 2D CFD-PBM/DQMOM coupled model can be used as a reliable tool for analyzing and improving the design and operation of the gas phase polymerization FBRs.

Keywords: computational fluid dynamics, population balance equation, fluidized bed polymerization reactor, direct quadrature method of moments

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16484 A Memetic Algorithm Approach to Clustering in Mobile Wireless Sensor Networks

Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

Abstract:

Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

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16483 A Coupled System of Caputo-Type Katugampola Fractional Differential Equations with Integral Boundary Conditions

Authors: Yacine Arioua

Abstract:

In this paper, we investigate the existence and uniqueness of solutions for a coupled system of nonlinear Caputo-type Katugampola fractional differential equations with integral boundary conditions. Based upon a contraction mapping principle, Schauders fixed point theorems, some new existence and uniqueness results of solutions for the given problems are obtained. For application, some examples are given to illustrate the usefulness of our main results.

Keywords: fractional differential equations, coupled system, Caputo-Katugampola derivative, fixed point theorems, existence, uniqueness

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16482 Time-Domain Simulations of the Coupled Dynamics of Surface Riding Wave Energy Converter

Authors: Chungkuk Jin, Moo-Hyun Kim, HeonYong Kang

Abstract:

A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.

Keywords: computer simulation, electromagnetics fully-coupled dynamics, floater-mooring-magnet, optimization, performance evaluation, surface riding, WEC

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16481 First-Principles Density Functional Study of Nitrogen-Doped P-Type ZnO

Authors: Abdusalam Gsiea, Ramadan Al-habashi, Mohamed Atumi, Khaled Atmimi

Abstract:

We present a theoretical investigation on the structural, electronic properties and vibrational mode of nitrogen impurities in ZnO. The atomic structures, formation and transition energies and vibrational modes of (NO3)i interstitial or NO4 substituting on an oxygen site ZnO were computed using ab initio total energy methods. Based on Local density functional theory, our calculations are in agreement with one interpretation of bound-excition photoluminescence for N-doped ZnO. First-principles calculations show that (NO3)i defects interstitial or NO4 substituting on an Oxygen site in ZnO are important suitable impurity for p-type doping in ZnO. However, many experimental efforts have not resulted in reproducible p-type material with N2 and N2O doping. by means of first-principle pseudo-potential calculation we find that the use of NO or NO2 with O gas might help the experimental research to resolve the challenge of achieving p-type ZnO.

Keywords: DFF, nitrogen, p-type, ZnO

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16480 Cas9-Assisted Direct Cloning and Refactoring of a Silent Biosynthetic Gene Cluster

Authors: Peng Hou

Abstract:

Natural products produced from marine bacteria serve as an immense reservoir for anti-infective drugs and therapeutic agents. Nowadays, heterologous expression of gene clusters of interests has been widely adopted as an effective strategy for natural product discovery. Briefly, the heterologous expression flowchart would be: biosynthetic gene cluster identification, pathway construction and expression, and product detection. However, gene cluster capture using traditional Transformation-associated recombination (TAR) protocol is low-efficient (0.5% positive colony rate). To make things worse, most of these putative new natural products are only predicted by bioinformatics analysis such as antiSMASH, and their corresponding natural products biosynthetic pathways are either not expressed or expressed at very low levels under laboratory conditions. Those setbacks have inspired us to focus on seeking new technologies to efficiently edit and refractor of biosynthetic gene clusters. Recently, two cutting-edge techniques have attracted our attention - the CRISPR-Cas9 and Gibson Assembly. By now, we have tried to pretreat Brevibacillus laterosporus strain genomic DNA with CRISPR-Cas9 nucleases that specifically generated breaks near the gene cluster of interest. This trial resulted in an increase in the efficiency of gene cluster capture (9%). Moreover, using Gibson Assembly by adding/deleting certain operon and tailoring enzymes regardless of end compatibility, the silent construct (~80kb) has been successfully refactored into an active one, yielded a series of analogs expected. With the appearances of the novel molecular tools, we are confident to believe that development of a high throughput mature pipeline for DNA assembly, transformation, product isolation and identification would no longer be a daydream for marine natural product discovery.

Keywords: biosynthesis, CRISPR-Cas9, DNA assembly, refactor, TAR cloning

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16479 Off-Line Detection of "Pannon Wheat" Milling Fractions by Near-Infrared Spectroscopic Methods

Authors: E. Izsó, M. Bartalné-Berceli, Sz. Gergely, A. Salgó

Abstract:

The aims of this investigation is to elaborate near-infrared methods for testing and recognition of chemical components and quality in “Pannon wheat” allied (i.e. true to variety or variety identified) milling fractions as well as to develop spectroscopic methods following the milling processes and evaluate the stability of the milling technology by different types of milling products and according to sampling times, respectively. This wheat categories produced under industrial conditions where samples were collected versus sampling time and maximum or minimum yields. The changes of the main chemical components (such as starch, protein, lipid) and physical properties of fractions (particle size) were analysed by dispersive spectrophotometers using visible (VIS) and near-infrared (NIR) regions of the electromagnetic radiation. Close correlation were obtained between the data of spectroscopic measurement techniques processed by various chemometric methods (e.g. principal component analysis (PCA), cluster analysis (CA) and operation condition of milling technology. Its obvious that NIR methods are able to detect the deviation of the yield parameters and differences of the sampling times by a wide variety of fractions, respectively. NIR technology can be used in the sensitive monitoring of milling technology.

Keywords: near infrared spectroscopy, wheat categories, milling process, monitoring

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16478 Vibration Absorption Strategy for Multi-Frequency Excitation

Authors: Der Chyan Lin

Abstract:

Since the early introduction by Ormondroyd and Den Hartog, vibration absorber (VA) has become one of the most commonly used vibration mitigation strategies. The strategy is most effective for a primary plant subjected to a single frequency excitation. For continuous systems, notable advances in vibration absorption in the multi-frequency system were made. However, the efficacy of the VA strategy for systems under multi-frequency excitation is not well understood. For example, for an N degrees-of-freedom (DOF) primary-absorber system, there are N 'peak' frequencies of large amplitude vibration per every new excitation frequency. In general, the usable range for vibration absorption can be greatly reduced as a result. Frequency modulated harmonic excitation is a commonly seen multi-frequency excitation example: f(t) = cos(ϖ(t)t) where ϖ(t)=ω(1+α sin⁡(δt)). It is known that f(t) has a series expansion given by the Bessel function of the first kind, which implies an infinity of forcing frequencies in the frequency modulated harmonic excitation. For an SDOF system of natural frequency ωₙ subjected to f(t), it can be shown that amplitude peaks emerge at ω₍ₚ,ₖ₎=(ωₙ ± 2kδ)/(α ∓ 1),k∈Z; i.e., there is an infinity of resonant frequencies ω₍ₚ,ₖ₎, k∈Z, making the use of VA strategy ineffective. In this work, we propose an absorber frequency placement strategy for SDOF vibration systems subjected to frequency-modulated excitation. An SDOF linear mass-spring system coupled to lateral absorber systems is used to demonstrate the ideas. Although the mechanical components are linear, the governing equations for the coupled system are nonlinear. We show using N identical absorbers, for N ≫ 1, that (a) there is a cluster of N+1 natural frequencies around every natural absorber frequency, and (b) the absorber frequencies can be moved away from the plant's resonance frequency (ω₀) as N increases. Moreover, we also show the bandwidth of the VA performance increases with N. The derivations of the clustering and bandwidth widening effect will be given, and the superiority of the proposed strategy will be demonstrated via numerical experiments.

Keywords: Bessel function, bandwidth, frequency modulated excitation, vibration absorber

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16477 Rural Development as a Strategy to Deter Migration in India - Re-Examining the Ideology of Cluster Development

Authors: Nandini Mohan, Thiruvengadam R. B.

Abstract:

Mahatma Gandhi advocated that the true indicator of modern India lay in the development of its villages. This has been proven with the recent outbreak of the Coronavirus pandemic and the surfacing predicament of our urban centers. Developed on the Industrialization model, the current state of the metropolis is of rampant overcrowding, high rates of unemployment, inadequate infrastructure, and resources to cater to the growing population. A majority of each city’s strength composes of the migrant population, demonstrated through the migrant crisis, a direct repercussion of COVID-19. This paper explores the ideology of how rural development can act as a tactic to counter the high rates of rural-urban migration. It establishes the need for a rural push, as India is predominantly an agrarian economy, with a vast disparity between the urban and rural centers due to its urban bias. It seeks to define development in holistic terms. It studies the models of ‘cluster’ as conceptualized by V.K.R.V. Rao, and detailed by Architect Charles Correa in his book, The New Landscape. The paper reexamines the theory of cluster development through existing models proposed by the government of India. Namely, PURA (Provision of Urban Amenities in Rural Areas), DRI (Deendayal Research Institute), and Rurban under Shyama Prasad Mukharjee Rurban Mission. It analyses the models, their strengths, weaknesses, and reasons for their failure and success to derive parameters for the ideation of an archetype model. A model of rural development that talks of the simultaneous development of existing adjacent villages, by the introduction of set unique functions, that may turn into self-sustaining clusters or agglomerations in the future, which could serve as the next step for Indian village development based on the cluster ideology.

Keywords: counter migration, models of rural development, cluster development theory, India

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16476 Genetic Diversity and Discovery of Unique SNPs in Five Country Cultivars of Sesamum indicum by Next-Generation Sequencing

Authors: Nam-Kuk Kim, Jin Kim, Soomin Park, Changhee Lee, Mijin Chu, Seong-Hun Lee

Abstract:

In this study, we conducted whole genome re-sequencing of 10 cultivars originated from five countries including Korea, China, India, Pakistan and Ethiopia with Sesamum indicum (Zhongzho No. 13) genome as a reference. Almost 80% of the whole genome sequences of the reference genome could be covered by sequenced reads. Numerous SNP and InDel were detected by bioinformatic analysis. Among these variants, 266,051 SNPs were identified as unique to countries. Pakistan and Ethiopia had high densities of SNPs compared to other countries. Three main clusters (cluster 1: Korea, cluster 2: Pakistan and India, cluster 3: Ethiopia and China) were recovered by neighbor-joining analysis using all variants. Interestingly, some variants were detected in DGAT1 (diacylglycerol O-acyltransferase 1) and FADS (fatty acid desaturase) genes, which are known to be related with fatty acid synthesis and metabolism. These results can provide useful information to understand the regional characteristics and develop DNA markers for origin discrimination of sesame.

Keywords: Sesamum indicum, NGS, SNP, DNA marker

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16475 InP Nanocrystals Core and Surface Electronic Structure from Ab Initio Calculations

Authors: Hamad R. Jappor, Zeyad Adnan Saleh, Mudar A. Abdulsattar

Abstract:

The ab initio restricted Hartree-Fock method is used to simulate the electronic structure of indium phosphide (InP) nanocrystals (NCs) (216-738 atoms) with sizes ranging up to about 2.5 nm in diameter. The calculations are divided into two parts, surface, and core. The oxygenated (001)-(1×1) facet that expands with larger sizes of nanocrystals is investigated to determine the rule of the surface in nanocrystals electronic structure. Results show that lattice constant and ionicity of the core part show decreasing order as nanocrystals grow up in size. The smallest investigated nanocrystal is 1.6% larger in lattice constant and 131.05% larger in ionicity than the converged value of largest investigated nanocrystal. Increasing nanocrystals size also resulted in an increase of core cohesive energy (absolute value), increase of core energy gap, and increase of core valence. The surface states are found mostly non-degenerated because of the effect of surface discontinuity and oxygen atoms. Valence bandwidth is wider on the surface due to splitting and oxygen atoms. The method also shows fluctuations in the converged energy gap, valence bandwidth and cohesive energy of core part of nanocrystals duo to shape variation. The present work suggests the addition of ionicity and lattice constant to the quantities that are affected by quantum confinement phenomenon. The method of the present model has threefold results; it can be used to approach the electronic structure of crystals bulk, surface, and nanocrystals.

Keywords: InP, nanocrystals core, ionicity, Hartree-Fock method, large unit cell

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16474 An AI-Based Dynamical Resource Allocation Calculation Algorithm for Unmanned Aerial Vehicle

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

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16473 Low Overhead Dynamic Channel Selection with Cluster-Based Spatial-Temporal Station Reporting in Wireless Networks

Authors: Zeyad Abdelmageid, Xianbin Wang

Abstract:

Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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16472 Analysis Customer Loyalty Characteristic and Segmentation Analysis in Mobile Phone Category in Indonesia

Authors: A. B. Robert, Adam Pramadia, Calvin Andika

Abstract:

The main purpose of this study is to explore consumer loyalty characteristic of mobile phone category in Indonesia. Second, this research attempts to identify consumer segment and to explore their profile in each segment as the basis of marketing strategy formulation. This study used some tools of multivariate analysis such as discriminant analysis and cluster analysis. Discriminate analysis used to discriminate consumer loyal and not loyal by using particular variables. Cluster analysis used to reveal various segment in mobile phone category. In addition to having better customer understanding in each segment, this study used descriptive analysis and cross tab analysis in each segment defined by cluster analysis. This study expected several findings. First, consumer can be divided into two large group of loyal versus not loyal by set of variables. Second, this study identifies customer segment in mobile phone category. Third, exploring customer profile in each segment that has been identified. This study answer a call for additional empirical research into different product categories. Therefore, a replication research is advisable. By knowing the customer loyalty characteristic, and deep analysis of their consumption behavior and profile for each segment, this study is very advisable for high impact marketing strategy development. This study contributes body of knowledge by adding empirical study of consumer loyalty, segmentation analysis in mobile phone category by multiple brand analysis.

Keywords: customer loyalty, segmentation, marketing strategy, discriminant analysis, cluster analysis, mobile phone

Procedia PDF Downloads 563
16471 Performance Evaluation of GPS/INS Main Integration Approach

Authors: Othman Maklouf, Ahmed Adwaib

Abstract:

This paper introduces a comparative study between the main GPS/INS coupling schemes, this will include the loosely coupled and tightly coupled configurations, several types of situations and operational conditions, in which the data fusion process is done using Kalman filtering. This will include the importance of sensors calibration as well as the alignment of the strap down inertial navigation system. The limitations of the inertial navigation systems are investigated.

Keywords: GPS, INS, Kalman filter, sensor calibration, navigation system

Procedia PDF Downloads 556