Search results for: cluster based

Authors: Sofia Barbosa, Mariana Pinto, José António Almeida, Edgar Carvalho, Catarina Diamantino

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The aim of this work was to test a methodology able to generate spatial-temporal maps that can synthesize simultaneously the trends of distinct hydrochemical indicators in an old radium-uranium tailings dam deposit. Multidimensionality reduction derived from principal component analysis and subsequent data aggregation derived from clustering analysis allow to identify distinct hydrochemical behavioural profiles and to generate synthetic evolutionary hydrochemical maps.

Keywords: Contamination plume migration, K-means of PCA scores, groundwater and mine water monitoring, spatial-temporal hydrochemical trends

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Authors: Gaoyuan Wang, Tian Chen

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China’s emission peak and carbon neutrality strategies lead to the transformation of development patterns and call for new green urban design thinking. This paper begins by revealing the evolution of green urban design thinking during the periods of carbon enlightenment, carbon dependency, and carbon decoupling from the perspective of the energy transition. Combined with the current energy situation, national strengths, and technological trends, the emergence of green urban design towards carbon neutrality becomes inevitable. Based on the preliminary analysis of its connotation, the characteristics of the new type of green urban design are generalized as low-carbon orientation, carbon-related objects, carbon-reduction means, and carbon-control patterns. Its theory is briefly clarified in terms of the human-earth synergism, quality-energy interconnection, and form-flow interpromotion. Then, its mechanism is analyzed combined with the core tasks of carbon neutrality, and the scope of design issues is defined, including carbon flow mapping, carbon source regulation, carbon sink construction, and carbon emission management. Finally, a multi-scale spatial response system is proposed across the region, city, cluster, and neighborhood level. The discussion aims to provide support for the innovation of green urban design theories and methods in the context of peak neutrality.

Keywords: carbon neutrality, green urban design, energy transition, theoretical exploration

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Authors: Alireza Sohrabi, Hamid Mohammadi

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The pistachio fruit is a strategic product in Iran. One of the problems caused the reduction of pistachio proceeds is related to biennial- bearing or alternative bearing. Biennial- bearing is very important and is happened because of the fallen female bloom buds in vintage year. This test was done according to random blocks of 6 orchards in the type of Ahmad Aghaie with 4 iterations. Vegetative properties of branch are investigated. The results are shown that if the bunch numbers are increased, the possibility of falling is increased in bloom buds. The least possibility of falling of bloom buds is specified in trimming of one bunch and has significant difference with other trimming.

Keywords: alternate bearing, pistachio, cluster, bud

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Authors: Yolanda Ramirez, Angel Tejada, Agustin Baidez

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In recent years, the intellectual capital reporting in higher education institutions has been acquiring progressive importance worldwide. Intellectual capital approaches becomes critical at universities, mainly due to the fact that knowledge is the main output as well as input in these institutions. Universities produce knowledge, either through scientific and technical research (the results of investigation, publications, etc.) or through teaching (students trained and productive relationships with their stakeholders). The purpose of the present paper is to identify the intangible elements about which university stakeholders demand most information. The results of a study done at Spanish universities are used to see which groups of universities have stakeholders who are more proactive to the disclosure of intellectual capital.

Keywords: intellectual capital, universities, Spain, cluster analysis

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Authors: Sérgio J. Teixeira, João J. Ferreira

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Tourism frequently gets identified as one of the sectors with the greatest potential for expansion on a global scale and hence conveying the importance of attempting to better understand the regional factors of competitiveness prevailing in this sector. This study’s objective essentially strives to provide a mapping of the scientific publications and the intellectual knowledge therein contained while conveying past research trends and identifying potential future lines of research in the fields of regional competitiveness and tourism innovation. This correspondingly deploys a systematic review of the literature in keeping with the bibliometric approach based upon VOSviewer software, with a particular focus on drafting maps for visualising the underlying intellectual structure. This type of analysis encapsulates the number of articles published and their annual number of citations for the period between 1900 and 2016 as registered by the Web of Science database. The results demonstrate how the intellectual structure on regional competitiveness divides essentially into three major categories: regional competitiveness, tourism innovation, and tourism clusters. Thus, the main contribution of this study arises out of identifying the main research trends in this field and the respective shortcomings and specific needs for future scientific research in the field of regional competitiveness and innovation in tourism.

Keywords: regional competitiveness, tourism cluster, bibliometric studies, tourism innovation, systematic review

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Authors: Hamidreza Fallah Lajimi, Elham Karami, Alireza Arab, Fatemeh Alinasab

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Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with Four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering, business engineering

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Authors: Justin Fu, Thomas Mazzuchi, Shahram Sarkani

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A key factor in technological immaturity in defense weapons acquisition is lack of understanding critical integrations at the subsystem and component level. To address this shortfall, recent research in integration readiness level (IRL) combines with technology readiness level (TRL) to form a system readiness level (SRL). SRL can be enriched with more robust quantitative methods to provide the program manager a useful tool prior to committing to major weapons acquisition programs. This research harnesses previous mathematical models based on graph theory, Petri nets, and tropical algebra and proposes a modification of the desirable SRL mathematical properties such that a tightly integrated (multitude of interfaces) subsystem can display a lower SRL than an inherently less coupled subsystem. The synthesis of these methods informs an improved decision tool for the program manager to commit to expensive technology development. This research ties the separately developed manufacturing readiness level (MRL) into the network representation of the system and addresses shortfalls in previous frameworks, including the lack of integration weighting and the over-importance of a single extremely immature component. Tropical algebra (based on the minimum of a set of TRLs or IRLs) allows one low IRL or TRL value to diminish the SRL of the entire system, which may not be reflective of actuality if that component is not critical or tightly coupled. Integration connections can be weighted according to importance and readiness levels are modified to be a cardinal scale (based on an analytic hierarchy process). Integration arcs’ importance are dependent on the connected nodes and the additional integrations arcs connected to those nodes. Lack of integration is not represented by zero, but by a perfect integration maturity value. Naturally, the importance (or weight) of such an arc would be zero. To further explore the impact of grouping subsystems, a multi-objective genetic algorithm is then used to find various clusters or communities that can be optimized for the most representative subsystem SRL. This novel calculation is then benchmarked through simulation and using past defense acquisition program data, focusing on the newly introduced Middle Tier of Acquisition (rapidly field prototypes). The model remains a relatively simple, accessible tool, but at higher fidelity and validated with past data for the program manager to decide major defense acquisition program milestones.

Keywords: readiness, maturity, system, integration

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Authors: Manoj K. Sharma, Neha Grover

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Dynamical cluster decay model (DCM) is applied to study the decay mechanism of 118Xe* nucleus in reference to recent data on 28Si + 90Zr → 118Xe* reaction, as an extension of our previous work on the dynamics of 112Xe* nucleus. It is relevant to mention here that DCM is based on collective clusterization approach, where emission probability of different decay paths such as evaporation residue (ER), intermediate mass fragments (IMF) and fission etc. is worked out on parallel scale. Calculations have been done over a wide range of center of mass energies with Ec.m. = 65 - 92 MeV. The evaporation residue (ER) cross-sections of 118Xe* compound nucleus are fitted in reference to available data, using spherical and quadrupole (β2) deformed choice of decaying fragments within the optimum orientations approach. It may be noted that our calculated cross-sections find decent agreement with experimental data and hence provide an opportunity to analyze the exclusive role of deformations in view of fragmentation behavior of 118Xe* nucleus. The possible contribution of IMF fragments is worked out and an extensive effort is being made to analyze the role of excitation energy, angular momentum, diffuseness parameter and level density parameter to have better understanding of the decay patterns governed in the dynamics of 28Si + 90Zr → 118Xe* reaction.

Keywords: cross-sections, deformations, fragmentation, angular momentum

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Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

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Authors: Adhithy Menon E., Biju C. A.

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In the 1960s, the concept of preserving heritage monuments was first introduced. During the 1990s, the concept of cultural landscapes gained importance, highlighting the importance of culture and heritage. Throughout this paper, we examine the second category of the cultural landscape, which is an organically evolving landscape as it represents a web of tangible, intangible, and ecological heritage and the ways in which they can be rejuvenated. Cultural landscapes in various regions, such as the Chettinad Village clusters, are in serious decline, which is identified through the Heritage Passport program of this area (2007). For this reason, it is necessary to conduct a detailed analysis of the factors that contribute to this degradation to ensure its protection in the future. An analysis of the cultural landscape of the Chettinad Village clusters and its impact on the community is presented in this paper. The paper follows the first objective, which is to understand cultural landscapes and their different criteria and categories. It is preceded by the study of various methods for protecting cultural landscapes. To identify a core area of intervention based on the parameters of Cultural Landscapes and Community Based Tourism, a study and analysis of the regional context of Chettinad village clusters considering tourism development must first be conducted. Lastly, planning interventions for integrating community-based tourism in Chettinad villages for the purpose of rejuvenating the cultural landscapes of the villages as well as their communities. The major findings include the importance of the local community in protecting cultural landscapes. The parameters identified to have an impact on Chettinad Village clusters are a community (community well-being, local maintenance, and enhancement, demand, alternative income for community, public participation, awareness), tourism (location and physical access, journey time, tourist attractions), integrity (natural factors, natural disasters, demolition of structures, deterioration of materials) authenticity (sense of place, living elements, building techniques, artistic expression, religious context) disaster management (natural disasters) and environmental impact (pollution). This area can be restored to its former glory and preserved as part of the cultural landscape for future generations by focusing on and addressing these parameters within the identified core area of the Chettinad Villages cluster (Kanadukathan TP, Kothamangalam, Kottaiyur, Athangudi, Karikudi, and Palathur).

Keywords: Chettinad village clusters, community, cultural landscapes, organically evolved.

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Authors: Acheampong Addo, Emmanuel Odartei Armah, Seth Koranteng Agyakwah, Ruby Asmah, Emmanuel Tetteh-Doku Mensah, Rhoda Lims Diyie, Sena Amewu, Catherine Ragasa, Edward Kofi Abban, Mike Yaw Osei-Atweneboana

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The study investigated genetic variation and relationships among populations of Nile tilapia cultured in small-scale fish farms in selected regions of Ghana. A total of 700 samples were collected. All samples were screened with five microsatellite markers and results were analyzed using (Genetic Analysis in Excel), (Molecular and Evolutionary Genetic Analysis software, and Genpop on the web for Heterozygosity and Shannon diversity, (Analysis of Molecular Variance), and (Principal Coordinate Analysis). Fish from the 16 populations (made up of 14 farms and 2 selectively bred populations) clustered into three groups: 7 populations clustered with the GIFT-derived strain, 4 populations clustered with the Akosombo strain, and three populations were in a separate cluster. The clustering pattern indicated groups of different strains of Nile tilapia cultured. Mantel correlation test also showed low genetic variations among the 16 populations hence the need to boost seed quality in order to accelerate aquaculture production in Ghana.

Keywords: microsatellites, small- scale, Nile tilapia, akosombo strain, GIFT strain

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Authors: Ricky Munyaradzi Mukonza

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E-government literature continues to grow as scholars and practitioners endeavour to understand this phenomenon. There are many facets of e-government that have been written about including its definition, adoption, and implementation and so on. However, more still needs to be known particularly in relation to how e-government is being adopted in different contexts. There could be many context specific factors that have a bearing on e-government adoption and in this paper focus is on attitudes and perceptions. Association between usage of e-government services and various perceptions such as ease of use, transparency, security, ease of understanding, communication, reliability, relevancy, perceived usefulness and perceived trust is examined. Within the Zimbabwean context and in particular the country’s local government sphere, such a study has not been done. The main aim of the paper is therefore to establish perceptions and attitudes towards e-government services among residents in Zimbabwe’s two local authorities. In terms of research methodology the paper is based on a Mixed Methods Approach (MMA) to collect and analyse data giving the researcher a holistic picture of the phenomenon being investigated. A sample of 785 residents from the two local authorities was used and these were selected using a combination of cluster and purposive sampling methods. A key finding in this paper is that a majority of respondents who have had the opportunity to use e-government services perceive the services to be easy to use, transparent, secure, easy to understand, reliable, relevant, useful and trustworthy. The paper, therefore, makes an important contribution on the relationship between residents’ perceptions and attitudes and e-government usage within the chosen cases.

Keywords: adoption, attitudes, e-government, perceptions

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Authors: Rabia Waseem, Low Kah Hin, Najihah Mohamed Hashim

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The variability in the chemical components of the Syzygium species essential oils has been evaluated. The leaves of Syzygium species have been collected from Perak, Malaysia. The essential oils extracted by using the conventional Hydro-distillation extraction procedure and analyzed by using Gas chromatography System attached with Mass Spectrometry (GCMS). Twenty-seven constituents were found in Syzygium species in which the major constituents include: α-Pinene (3.94%), α-Thujene (2.16%), α-Terpineol (2.95%), g-Elemene (2.89%) and D-Limonene (14.59%). The aim of this study was the comparison between the evaluated data and existing literature to fortify the major variability through statistical analysis.

Keywords: chemotaxonomy, cluster analysis, essential oil, medicinal plants, statistical analysis

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Authors: Shyam Shukla

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A brand is the identity of a specific product, service or business. A brand can take many forms, including a name, sign, symbol, color, combination or slogan. The word brand began simply as a way to tell one person's identity from another by means of a hot iron stamp. A legally protected brand name is called a trademark. The word brand has continued to evolve to encompass identity - it affects the personality of a product, company or service. A concept brand is a brand that is associated with an abstract concept, like AIDS awareness or environmentalism, rather than a specific product, service, or business. A commodity brand is a brand associated with a commodity1. In this paper, it is tried to explore the significance of an intellectual capital for the branding of an Institution.

Keywords: brand, commodity, consumer, cultural values, intellectual capital, zonal cluster

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Authors: Anderson S. Fonseca, Italo F. S. Da Silva, Robert D. A. Santos, Mayara G. Da Silva, Pedro H. C. Vieira, Antonio M. S. Sobrinho, Victor H. B. Lemos, Petterson S. Diniz, Anselmo C. Paiva, Eliana M. G. Monteiro

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In Brazil, the National Electric Energy Agency (ANEEL) establishes that electrical energy companies are responsible for measuring and billing their customers. Among these regulations, it’s defined that a company must bill your customers within 27-33 days. If a relocation or a change of period is required, the consumer must be notified in writing, in advance of a billing period. To make it easier to organize a workday’s measurements, these companies create a reading plan. These plans consist of grouping customers into reading groups, which are visited by an employee responsible for measuring consumption and billing. The creation process of a plan efficiently and optimally is a capacitated clustering problem with constraints related to homogeneity and compactness, that is, the employee’s working load and the geographical position of the consuming unit. This process is a work done manually by several experts who have experience in the geographic formation of the region, which takes a large number of days to complete the final planning, and because it’s human activity, there is no guarantee of finding the best optimization for planning. In this paper, the GBKMeans method presents a technique based on K-Means and genetic algorithms for creating a capacitated cluster that respects the constraints established in an efficient and balanced manner, that minimizes the cost of relocating consumer units and the time required for final planning creation. The results obtained by the presented method are compared with the current planning of a real city, showing an improvement of 54.71% in the standard deviation of working load and 11.97% in the compactness of the groups.

Keywords: capacitated clustering, k-means, genetic algorithm, districting problems

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Authors: Gaelle Candel, David Naccache

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t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embeddings. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n²) to O(n²=k), and the memory requirement from n² to 2(n=k)², which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution, and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning

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Authors: Waldir Roque, Gustavo Oliveira, Moises Santos, Tatiana Simoes

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Increasing the oil recovery factor of an oil reservoir has been a concern of the oil industry. Usually, the production placement zones are defined after some analysis of geological and petrophysical parameters, being the rock porosity, permeability and oil saturation of fundamental importance. In this context, the determination of hydraulic flow units (HFUs) renders an important step in the process of reservoir characterization since it may provide specific regions in the reservoir with similar petrophysical and fluid flow properties and, in particular, techniques supporting the placement of production zones that favour the tracing of directional wells. A HFU is defined as a representative volume of a total reservoir rock in which petrophysical and fluid flow properties are internally consistent and predictably distinct of other reservoir rocks. Technically, a HFU is characterized as a rock region that exhibit flow zone indicator (FZI) points lying on a straight line of the unit slope. The goal of this paper is to provide a trustful indication for oil production placement zones for the best-fit HFUs. The FZI cloud of points can be obtained from the reservoir quality index (RQI), a function of effective porosity and permeability. Considering log and core data the HFUs are identified and using the discrete rock type (DRT) classification, a set of connected cell clusters can be found and by means a graph centrality metric, the maximum closeness (MaxC) cell is obtained for each cluster. Considering the MaxC cells as production zones, an extensive analysis, based on several oil recovery factor and oil cumulative production simulations were done for the SPE Model 2 and the UNISIM-I-D synthetic fields, where the later was build up from public data available from the actual Namorado Field, Campos Basin, in Brazil. The results have shown that the MaxC is actually technically feasible and very reliable as high performance production placement zones.

Keywords: hydraulic flow unit, maximum closeness centrality, oil production simulation, production placement zone

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Authors: Hye Lin Yang, Clifton R. Emery

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Purpose: The purpose of this study is to examine the effects of intimate partner violence on child abuse, whether patriarchal attitude and informal social control moderate the relationship between intimate partner violence and child abuse. This study was conducted with data from The Seoul Families and Neighborhoods Study (SFNS). The SFNS is a representative random probability 3-stage cluster sample of 541 cohabiting couples in Seoul, South Korea collected in 2012. To verify research models, Random effect analysis were used. All analyses were performed using the Stata program. Results: Crucial findings are the following. First, intimate partner violence showed a significantly positive relationship with Child abuse. Second, there are significant moderating effects of informal social control on intimate partner violence - child abuse. Third, there are significant moderating effects of patriarchal attitude on intimate partner violence - child abuse. In other words, Patriarchal attitude is a significant risk factor of child abuse and informal social control is a significant Protection factor of child abuse. Based on results, the policy and practical implications for preventing child abuse, promoting informal social control were discussed.

Keywords: Intimate partner violence, child abuse, informal social control, patriarchal attitude

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Authors: K. Umbleja, M. Ichino

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Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

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Authors: Amirmohsen Behjat, Aleck Ostry, Christina Miewald, Bernie Pauly

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Substantial research has indicated that socioeconomic and demographic characteristics’ of neighborhoods are strong determinants of food security. The aim of this study was to develop a Food Insecurity Neighborhood Index (FINI) based on the associated socioeconomic and demographic variables to identify the areas at potential risk of food insecurity in rural British Columbia (BC). Principle Component Analysis (PCA) technique was used to calculate the FINI for each rural Dissemination Area (DA) using the food security determinant variables from Canadian Census data. Using ArcGIS, the neighborhoods with the top quartile FINI values were classified as food insecure. The results of this study indicated that the most food insecure neighborhood with the highest FINI value of 99.1 was in the Bulkley-Nechako (central BC) area whereas the lowest FINI with the value of 2.97 was for a rural neighborhood in the Cowichan Valley area. In total, 98.049 (19%) of the rural population of British Columbians reside in high food insecure areas. Moreover, the distribution of food insecure neighborhoods was found to be strongly dependent on the degree of rurality in BC. In conclusion, the cluster of food insecure neighbourhoods was more pronounced in Central Coast, Mount Wadington, Peace River, Kootenay Boundary, and the Alberni-Clayoqout Regional Districts.

Keywords: neighborhood food insecurity index, socioeconomic and demographic determinants, principal component analysis, Canada census, ArcGIS

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali

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The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several sub-networks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.

Keywords: wireless sensor networks, routing protocols, AD HOC topology, cluster, sub-network, WSN design requirements

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Authors: Liqin Zhang, Liang Yan

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This paper addresses the speed synchronization control problem for a network-based multi-motor system from the perspective of cluster consensus theory. Each motor is considered as a single agent connected through fixed and undirected network. This paper presents an improved control protocol from three aspects. First, for the purpose of improving both tracking and synchronization performance, this paper presents a distributed leader-following method. The improved control protocol takes the importance of each motor’s speed into consideration, and all motors are divided into different groups according to speed weights. Specifically, by using control parameters optimization, the synchronization error and tracking error can be regulated and decoupled to some extent. The simulation results demonstrate the effectiveness and superiority of the proposed strategy. In practical engineering, the simplified models are unrealistic, such as single-integrator and double-integrator. And previous algorithms require the acceleration information of the leader available to all followers if the leader has a varying velocity, which is also difficult to realize. Therefore, the method focuses on an observer-based variable structure algorithm for consensus tracking, which gets rid of the leader acceleration. The presented scheme optimizes synchronization performance, as well as provides satisfactory robustness. What’s more, the existing algorithms can obtain a stable synchronous system; however, the obtained stable system may encounter some disturbances that may destroy the synchronization. Focus on this challenging technological problem, a state-dependent-switching approach is introduced. In the presence of unmeasured angular speed and unknown failures, this paper investigates a distributed fault-tolerant consensus tracking algorithm for a group non-identical motors. The failures are modeled by nonlinear functions, and the sliding mode observer is designed to estimate the angular speed and nonlinear failures. The convergence and stability of the given multi-motor system are proved. Simulation results have shown that all followers asymptotically converge to a consistent state when one follower fails to follow the virtual leader during a large enough disturbance, which illustrates the good performance of synchronization control accuracy.

Keywords: consensus control, distributed follow, fault-tolerant control, multi-motor system, speed synchronization

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Authors: Josef Voracek, Jan Sima

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The main purpose of our study is to state the basic types of fitness customers. This paper aims to create a specific customer typology in today’s fitness centres in the region of Prague. Our suggested typology of Prague fitness centres customers is based on answers to the questions: What are the customers like, what are their preferences, and what kinds of services do they use more often in Prague fitness centres? These are the main aspects of the presented typology. A survey was conducted on a sample of 1004 respondents from 48 fitness centres, which ran during May 2012. We used questionnaires and latent class analysis for the assessment and interpretation of data. Gender was especially the main filter criterion. In the population, there were 522 males and 482 females. Data were analysed using the LCA method. We identified 6 segments of typical customers, of which three are male and three are female. Each segment is influenced primarily by the age of customers, from which we can develop further characteristics, such as education, income, marital status, etc. Male segments use the main workout area above all, whilst female segments use a much wider range of services offered, for example, group exercises, personal training, and cardio theatres. LCA method was found to be the most suitable tool, because cluster analysis is very limited in the forms and numbers of variables and indicators. Models of 3 latent classes for each gender are optimal, as it is demonstrated by entropy indices and matrices of the likelihood of the membership to the classes. A probable weak point of the survey is the selection of fitness centres, because of the market in Prague is really specific.

Keywords: customer, fitness, latent class analysis, typology

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Authors: Sergey A. Burikov, Tatiana A. Dolenko, Kirill A. Gushchin, Sergey A. Dolenko

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The paper presents the results of clusterization by Kohonen self-organizing maps (SOM) applied for analysis of array of Raman spectra of multi-component solutions of inorganic salts, for determination of types of salts present in the solution. It is demonstrated that use of SOM is a promising method for solution of clusterization and classification problems in spectroscopy of multi-component objects, as attributing a pattern to some cluster may be used for recognition of component composition of the object.

Keywords: Kohonen self-organizing maps, clusterization, multi-component solutions, Raman spectroscopy

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Authors: Hsiao-Lan Wang, Chun-Han Chiang, I-Chen Chen

Abstract:

In Chinese Mandarin, lexical tones play an important role to provide contrasts in word meaning. They are pitch patterns and can be quantified as the fundamental frequency (F0), expressed in Hertz (Hz). In this study, we aim to investigate the influence of frequency discrimination on Chinese children’s performance of reading abilities. Fifty participants from 3rd to 4th grades, including 24 children with reading difficulties and 26 age-matched children, were examined. A serial of cognitive, language, reading and psychoacoustic tests were administrated. Magnetoencephalography (MEG) was also employed to study children’s auditory sensitivity. In the present study, auditory frequency was measured through slide-up pitch, slide-down pitch and frequency-modulated tone. The results showed that children with Chinese reading difficulties were significantly poor at phonological awareness and auditory discrimination for the identification of frequency-modulated tone. Chinese children’s character reading performance was significantly related to lexical tone awareness and auditory perception of frequency-modulated tone. In our MEG measure, we compared the mismatch negativity (MMNm), from 100 to 200 ms, in two groups. There were no significant differences between groups during the perceptual discrimination of standard sounds, fast-up and fast-down frequencies. However, the data revealed significant cluster differences between groups in the slow-up and slow-down frequencies discrimination. In the slow-up stimulus, the cluster demonstrated an upward field map at 106-151 ms (p < .001) with a strong peak time at 127ms. The source analyses of two dipole model and localization resolution model (CLARA) from 100 to 200 ms both indicated a strong source from the left temporal area with 45.845% residual variance. Similar results were found in the slow-down stimulus with a larger upward current at 110-142 ms (p < 0.05) and a peak time at 117 ms in the left temporal area (47.857% residual variance). In short, we found a significant group difference in the MMNm while children processed frequency-modulated tones with slow temporal changes. The findings may imply that perception of sound frequency signals with slower temporal modulations was related to reading and language development in Chinese. Our study may also support the recent hypothesis of underlying non-verbal auditory temporal deficits accounting for the difficulties in literacy development seen developmental dyslexia.

Keywords: Chinese Mandarin, frequency modulation sweeps, magnetoencephalography, mismatch negativity, reading difficulties

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Authors: F. Pari, E. Fathiazar, T. Hashemi, M. Pari

Abstract:

The present study aimed to examine the role of self-efficacy and school belonging in the academic achievement of Tabriz high school students in grade 11. Therefore, using a random cluster method, 377 subjects were selected from the whole students of Tabriz high schools. They filled in the School Belonging Questionnaire (SBQ) and General Self-Efficacy Scale. Data were analyzed using correlational as well as multiple regression methods. Findings demonstrate self-efficacy and school belonging have significant roles in the prediction of academic achievement. On the other hand, the results suggest that considering the gender variable there is no significant difference between self-efficacy and school belonging. On the whole, cognitive approaches could be effective in the explanation of academic achievement.

Keywords: school belonging, self-efficacy, academic achievement, high school

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Authors: Tamanna Jethava, Rahul Joshi

Abstract:

Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

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Authors: Min Woo Lee, Kyoung Seok Kim

Abstract:

We made an effort to resolve a research question, which is about the relationship between employees’ corporate social responsibility (CSR) participation and their organizational citizenship behavior (OCB), and an effect of profiles of job characteristics. To test the question, we divided sample into two groups that have the profiles of each job characteristic. One group had high level on the five dimensions of job characteristic (D group), whereas another group had low level on the dimensions (R group). As a result, regression analyses showed that the relationship between CSR participation and OCB is positive in the D group, but the relationship is not significant in the R group. The results raise a question to the argument of recent studies showing that there is positive relationship between the CSR and the OCB. Implications and limitations are demonstrated in the conclusion.

Keywords: CSR, OCB, job characteristics, cluster analysis

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Authors: Aschenaki Zerihun Kea, Bernt Lindtjorn, Achamyelesh Gebretsadik, Sven Gudmund Hinderaker

Abstract:

Introduction: Maternal mortality studies conducted at the national level do not provide the information needed for planning and monitoring health programs at lower administrative levels. The aim of this study was to measure maternal mortality, identify risk factors and district-level variations in Sidama National Regional State, southern Ethiopia. Methods: A cross sectional population-based survey was carried out in households where women reported pregnancy and birth outcomes in the past five years. The study was conducted in the Sidama National Regional State, southern Ethiopia, from July 2019 to May 2020. Multi-stage cluster sampling technique was employed. The outcome variable of the study was maternal mortality. Complex sample logistic regression analysis was applied to assess variables independently associated with maternal mortality. Results: We registered 10602 live births (LB) and 48 maternal deaths, yielding an overall maternal mortality ratio (MMR) of 419; 95% CI: 260-577 per 100,000 LB. Aroresa district had the highest MMR with 1142 (95% CI: 693-1591) per 100,000 LB. Leading causes of death were haemorrhage 21 (41%) and eclampsia 10 (27%). Thirty (59%) mothers died during labour, or within 24 hours after delivery, 25 (47%) died at home and 17 (38%) at a health facility. Mothers who did not have formal education had a higher risk of maternal death (AOR: 4.4; 95% CI: 1.7 – 11.0). The risk of maternal death was higher in districts with a low midwife-to-population ratio (AOR: 2.9; 95% CI: 1.0-8.9). Conclusion: The high maternal mortality with district-level variations in Sidama Region highlights the importance of improving obstetric care and employing targeted interventions in areas with high mortality rates. Due attention should be given to improving access to female education. Additional midwives have to be trained and deployed to improve maternal health services and consequently save the lives of mothers.

Keywords: maternal mortality variation, maternal death, Sidama, Ethiopia

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