The Experts below are selected from a list of 15417 Experts worldwide ranked by ideXlab platform
Kristiena Matis - One of the best experts on this subject based on the ideXlab platform.
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scholastic talent Indicator Matrix
Workshop in Primary and Secondary Computing Education, 2019Co-Authors: Matthias Matzner, Claudia Hildebrandt, Kerstin Honer, Kristiena MatisAbstract:The compatibilities and discrepancies of various school subjects regarding Indicators for talented students are taking as a starting point to combine and categorize general Indicators. The scholastic talent Indicator Matrix combines talent Indicators from various school subjects into general talent Indicators.
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WiPSCE - Scholastic Talent Indicator Matrix
Proceedings of the 14th Workshop in Primary and Secondary Computing Education on - WiPSCE'19, 2019Co-Authors: Matthias Matzner, Claudia Hildebrandt, Kerstin Honer, Kristiena MatisAbstract:The compatibilities and discrepancies of various school subjects regarding Indicators for talented students are taking as a starting point to combine and categorize general Indicators. The scholastic talent Indicator Matrix combines talent Indicators from various school subjects into general talent Indicators.
Jan Rosenkranz - One of the best experts on this subject based on the ideXlab platform.
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Textural Quantification and Classification of Drill Cores for Geometallurgy: Moving Toward 3D with X-ray Microcomputed Tomography (µCT)
Natural Resources Research, 2020Co-Authors: Pratama Istiadi Guntoro, Yousef Ghorbani, Alan R. Butcher, Jukka Kuva, Jan RosenkranzAbstract:Texture is one of the critical parameters that affect the process behavior of ore minerals. Traditionally, texture has been described qualitatively, but recent works have shown the possibility to quantify mineral textures with the help of computer vision and digital image analysis. Most of these studies utilized 2D computer vision to evaluate mineral textures, which is limited by stereological error. On the other hand, the rapid development of X-ray microcomputed tomography (µCT) has opened up new possibilities for 3D texture analysis of ore samples. This study extends some of the 2D texture analysis methods, such as association Indicator Matrix (AIM) and local binary pattern (LBP) into 3D to get quantitative textural descriptors of drill core samples. The sensitivity of the methods to textural differences between drill cores is evaluated by classifying the drill cores into three textural classes using methods of machine learning classification, such as support vector machines and random forest. The study suggested that both AIM and LBP textural descriptors could be used for drill core classification with overall classification accuracy of 84–88%.
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Ore texture breakage characterization and fragmentation into multiphase particles
Powder Technology, 2018Co-Authors: Mehdi Parian, Abdul Mwanga, Pertti Lamberg, Jan RosenkranzAbstract:The ore texture and the progeny particles after a breakage in the comminution have been a subject of interest in mineral liberation studies and are the missing link between geology and mineral processing in the concept of geometallurgy. A new method called Association Indicator Matrix (AIM) established based on co-occurrence Matrix was introduced to quantify the mineral association of ore texture and its progeny particles. The Association Indicator Matrix can be used as a criterion for classifying ore texture as well as analyzing breakage behavior of ore texture. Within the study, the outcome of breakage analysis with Association Indicator Matrix was used to forecast particle population of iron ore texture after crushing. The particle size of forecasted particles was taken from experimental and frequency of breakage in phases was defined based on Association Indicator and liberation of minerals. Comparison of liberation distribution of iron oxide minerals from experimental and forecasted population shows a satisfactory agreement.
B Fourestie - One of the best experts on this subject based on the ideXlab platform.
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umts design strategies based on Indicator Matrix approach
International Conference on Communications, 2004Co-Authors: Sana Ben Jamaa, S Altman, A Ortega, B FourestieAbstract:This paper presents Indicator matrices for assessing the quality of UMTS networks, the interference and the macrodiversity matrices. A design methodology based on these Indicators is developed to guide the network designer in complex design tasks. The Indicator matrices are of particular interest for both assessing of network performance and for design purposes since they allow one to identify the interaction between any couple of stations in the network. Hence, the identification of problematic sectors as well as possible curative solutions is made much simpler. An example of network design illustrates the effectiveness of the Indicator Matrix approach.
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ICC - UMTS design strategies based on Indicator Matrix approach
2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577), 2004Co-Authors: Sana Ben Jamaa, S Altman, A Ortega, B FourestieAbstract:This paper presents Indicator matrices for assessing the quality of UMTS networks, the interference and the macrodiversity matrices. A design methodology based on these Indicators is developed to guide the network designer in complex design tasks. The Indicator matrices are of particular interest for both assessing of network performance and for design purposes since they allow one to identify the interaction between any couple of stations in the network. Hence, the identification of problematic sectors as well as possible curative solutions is made much simpler. An example of network design illustrates the effectiveness of the Indicator Matrix approach.
Sana Ben Jamaa - One of the best experts on this subject based on the ideXlab platform.
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Quality Indicator matrices and their contribution to WCDMA network design
IEEE Transactions on Vehicular Technology, 2005Co-Authors: Sana Ben Jamaa, H. Dubreil, Zwi Altman, A OrtegaAbstract:A known characteristic of wide-band code-division multiple-access (WCDMA) networks is the interdependence or coupling between network parameters, namely, a change of one parameter in a given base station can impact the performance of several other base stations. The assessment of the coupling between couple of base stations can be useful for both quality evaluation and for efficient design processes. This paper presents Indicator matrices that characterize the interaction between any couple of base stations in terms of interference and macrodiversity. Three applications based on the Indicator matrices are developed: a design heuristic for optimizing the network performance; the computation of a set of base stations, denoted as influence set, which are most coupled with a given base station; and a systematic methodology for partitioning the network into disjoint groups of base stations using a clustering approach. Detailed examples illustrate the effectiveness of the Indicator Matrix approach.
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umts design strategies based on Indicator Matrix approach
International Conference on Communications, 2004Co-Authors: Sana Ben Jamaa, S Altman, A Ortega, B FourestieAbstract:This paper presents Indicator matrices for assessing the quality of UMTS networks, the interference and the macrodiversity matrices. A design methodology based on these Indicators is developed to guide the network designer in complex design tasks. The Indicator matrices are of particular interest for both assessing of network performance and for design purposes since they allow one to identify the interaction between any couple of stations in the network. Hence, the identification of problematic sectors as well as possible curative solutions is made much simpler. An example of network design illustrates the effectiveness of the Indicator Matrix approach.
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ICC - UMTS design strategies based on Indicator Matrix approach
2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577), 2004Co-Authors: Sana Ben Jamaa, S Altman, A Ortega, B FourestieAbstract:This paper presents Indicator matrices for assessing the quality of UMTS networks, the interference and the macrodiversity matrices. A design methodology based on these Indicators is developed to guide the network designer in complex design tasks. The Indicator matrices are of particular interest for both assessing of network performance and for design purposes since they allow one to identify the interaction between any couple of stations in the network. Hence, the identification of problematic sectors as well as possible curative solutions is made much simpler. An example of network design illustrates the effectiveness of the Indicator Matrix approach.
Yan Heng Liu - One of the best experts on this subject based on the ideXlab platform.
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Assessment of the Survivability of Networked System Based on Improved TOPSIS
Communications in Computer and Information Science, 2011Co-Authors: Cheng Li Zhao, Yan Heng LiuAbstract:Survivability has been one of the active fields in network security recently. In order to evaluate the survivability of networked system effectively, this paper proposes a method of combining improved TOPSIS and grey relation analysis for quantitative assessment. Firstly, it normalizes Indicator Matrix according to traditional TOPSIS method and determines the positive and negative ideal solutions. Secondly, it calculates relation degree of every critical service in terms of grey relation analysis, according to which it gets the optimal dependency degree. Then it evaluates the whole survivability of networked system depending on the survivable function. At last a case study is given to show the availability and effectiveness of the method.
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Combining Grey Relation Analysis and TOPSIS for Evaluating the Survivability of Networked Information System
Advanced Materials Research, 2011Co-Authors: Cheng Li Zhao, Yan Heng LiuAbstract:In order to evaluate the survivability of networked information system effectively, this paper presents a method of combining grey relation analysis and TOPSIS for quantitative assessment. Firstly, a hierarchical model of information system is constructed. Then it normalizes Indicator Matrix according to traditional TOPSIS method, determines the positive and negative ideal solutions, calculates the optimal dependency degree of critical services in terms of grey relation analysis, and evaluates the whole networked information system depending on the survivable function. At last this paper gives an example to show the availability and the value of the method.
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Evaluation for Survivable Networked System Based on Grey Correlation and Improved TOPSIS
Journal of Networks, 2011Co-Authors: Cheng Li Zhao, Yan Heng LiuAbstract:Survivability has been one of the active fields in network security recently. In order to evaluate the survivability of networked system effectively, this paper proposes a method of combining grey correlation analysis and improved TOPSIS for quantitative assessment. Firstly, it normalizes Indicator Matrix according to improved TOPSIS method and determines the positive and negative ideal solutions. Secondly, it calculates correlation degree of every essential service in terms of grey correlation analysis, according to which with weight Matrix, it gets the optimal dependency degree. Then it evaluates the whole survivability of networked system depending on the survivable function. At last the simulation and experimental results show the method is reasonable and effective.
