LIST OF APPROVED ARTICLES MININ 2010

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Nº	Name	Last Name	Position	Company	Country	Paper Nº	Presentation Title
1	Andrew	Richmond		Golder Associates	Australia	01	Stress Testing Mine Plans
2	Marcelo	Godoy		Golder Associates	Chile	01	Stress Testing Mine Plans
3	Reginaldo	Saboia de Paiva		Federal University of Pará	Brazil	02	Measurement and Optimization of the Productivity of Track- Type Tractors Applied and Sterile Deposits
4	Marinésio	Pinheiro Lima		Federal University of Pará	Brazil	02	Measurement and Optimization of the Productivity of Track- Type Tractors Applied and Sterile Deposits
5	Juary Raimundo	Pereira Silveira		Federal University of Pará/Vale	Brazil	02	Measurement and Optimization of the Productivity of Track- Type Tractors Applied and Sterile Deposits
6	Flavio	Barbosa Freitas		Vale	Brazil	02	Measurement and Optimization of the Productivity of Track- Type Tractors Applied and Sterile Deposits
7	Diogo	da Silva Menezes		Federal University of Pará	Brazil	02	Measurement and Optimization of the Productivity of Track- Type Tractors Applied and Sterile Deposits
8	Bob	McCarthy		Snowden Mining Industry Consultants	Canada	03	In-Pit Crushing and Conveying – Fitting a square peg in a round open pit
9	Alejandra	Alvarez		Mining Information Communications and Monitoring (MICOMO)	Chile	04	Online Mining Structures Deformation Monitoring Using BOTDR Technology
10	Gabriel	Arevalo		Mining Information Communications and Monitoring (MICOMO)	Chile	04	Online Mining Structures Deformation Monitoring Using BOTDR Technology
11	Joaqu	Fontbona		Universidad de Chile	Chile	04	Online Mining Structures Deformation Monitoring Using BOTDR Technology
12	Juan Pablo	Gonzalez		Mining Information Communications and Monitoring (MICOMO)	Chile	04	Online Mining Structures Deformation Monitoring Using BOTDR Technology
13	Leandro	Llanza		Mining Information Communications and Monitoring (MICOMO)	Chile	04	Online Mining Structures Deformation Monitoring Using BOTDR Technology
14	Ricardo	Moffat		Universidad de Chile	Chile	04	Online Mining Structures Deformation Monitoring Using BOTDR Technology
15	Luis Felipe	Mujica		Mining Information Communications and Monitoring (MICOMO)	Chile	04	Online Mining Structures Deformation Monitoring Using BOTDR Technology
16	Jacques	Deraisme		Geovariances	France	05	Sampling optimization of a volcano-sedimentary deposit using geostatistical simulations
17	Javier	Miranda		Geovariances	France	05	Sampling optimization of a volcano-sedimentary deposit using geostatistical simulations
18	Orlando	Rojas		Compañía Minera Doña Inés de Collahuasi	Chile	05	Sampling optimization of a volcano-sedimentary deposit using geostatistical simulations
19	Mauricio	Barraza		Codelco	Chile	06	Probabilistic Risk Analysis of Mine Production Plans
20	Jos	Castro		Codelco	Chile	06	Probabilistic Risk Analysis of Mine Production Plans
21	Arpita	Khanna		The Energy and Resources Institute (TERI)	India	07	Business Approach towards Integrated Mine Management
22	David	Machuca-Mory		University of Alberta	Canada	08	Comparison of Techniques for the 3D Volume Modelling of Deposits with Tabular Geometry
23	Simon	Mortimer		Atticus Associates	Peru	08	Comparison of Techniques for the 3D Volume Modelling of Deposits with Tabular Geometry
24	Miguel	Cuba		University of Alberta	Canada	08	Comparison of Techniques for the 3D Volume Modelling of Deposits with Tabular Geometry
25	Jhon	Espinoza		Compañía Minera Antamina S.A.	Peru	09	Ore Control in Antamina, a skarn with High Complexity
26	Cesar	Guerra		Compañía Minera Antamina S.A.	Peru	09	Ore Control in Antamina, a skarn with High Complexity
27	Alejandro	Cáceres		GeoInnova Consultores Ltda	Chile	10	Conditional cosimulation of copper grades and lithology at Río Blanco – Los Bronces copper deposit
28	Xavier	Emery		Universidad de Chile	Chile	10	Conditional cosimulation of copper grades and lithology at Río Blanco – Los Bronces copper deposit
29	Julio	Castillo		Codelco Norte	Chile	100	Asimetría en el Riesgo de la Planificación Minera bajo Volatilidad de los Precios de Venta
30	Enrique	Chacón		Codelco Norte	Chile	100	Asimetría en el Riesgo de la Planificación Minera bajo Volatilidad de los Precios de Venta
31	Rafael	Epstein		Universidad de Chile	Chile	100	Asimetría en el Riesgo de la Planificación Minera bajo Volatilidad de los Precios de Venta
32	Ernesto	Arancibia		Codelco	Chile	101	Planificación Minera con Altas Velocidades de Extracción
33	Marco	Cornejo		REDCO	Chile	101	Planificación Minera con Altas Velocidades de Extracción
34	Juan	Montes		Codelco	Chile	102	Modelo de Confiabilidad para Minería Subterránea
35	Gabriel	Pais		REDCO	Chile	102	Modelo de Confiabilidad para Minería Subterránea
36	Gustavo	Donoso		Universidad de Chile	Chile	103	Un Modelo Matemático para Planificación Bajo Incertidumbre Geológica
37	Nelson	Morales		DELPHOS	Chile	103	Un Modelo Matemático para Planificación Bajo Incertidumbre Geológica
38	Enrique	Rubio		DELPHOS	Chile	103	Un Modelo Matemático para Planificación Bajo Incertidumbre Geológica
39	Álvaro	Vergara		Universidad de Chile	Chile	103	Un Modelo Matemático para Planificación Bajo Incertidumbre Geológica
40	Rodrigo	Zúñiga		Universidad de Chile	Chile	103	Un Modelo Matemático para Planificación Bajo Incertidumbre Geológica
41	Roussos	Dimitrakopoulos		McGill University	Canada	104	Scheduling Optimization under Uncertainty
42	Marcelo	Godoy		Golder Associates	Chile	104	Scheduling Optimization under Uncertainty
43	Fernando	Peirano		DELPHOS	Chile	105	Riesgo Asociado a la Incorporación de Recursos Indicados e Inferidos en el Plan Minero
44	Marcelo	Vargas		DELPHOS	Chile	105	Riesgo Asociado a la Incorporación de Recursos Indicados e Inferidos en el Plan Minero
45	Eman	Widijanto		DELPHOS	Chile	105	Riesgo Asociado a la Incorporación de Recursos Indicados e Inferidos en el Plan Minero
46	Patricio	Prieto		Minera Spence	Chile	106	Cut-Off Optimisation Using Multidimensional Variables
47	Francisco	Rojas		Minera Spence	Chile	107	Hybrid Pit as Ultimate Pit Limits Definition
48	Miguel	Cuba		University of Alberta	Canada	108	Adding Flexibility to Support Vector Classification for Modeling Categorical Variables
49	Julián	Ortíz		Universidad de Chile	Chile	108	Adding Flexibility to Support Vector Classification for Modeling Categorical Variables
50	Oy	Leuangthong		University of Alberta	Canada	108	Adding Flexibility to Support Vector Classification for Modeling Categorical Variables
51	Patricio	Inostroza		Universidad de Chile	Chile	109	SOMI: A Standard Data Representation for Mining Industry
52	Juan Claudio	Navarro		Universidad de Chile	Chile	109	SOMI: A Standard Data Representation for Mining Industry
53	Andrea	Nieto		Universidad de Chile	Chile	109	SOMI: A Standard Data Representation for Mining Industry
54	Ana C.	Pezo		Universidad de Chile	Chile	109	SOMI: A Standard Data Representation for Mining Industry
55	Patrick	Rivera		Universidad de Chile	Chile	11	A Comparison of Three Geostatistical Approaches for Co-Simulating Mineral Grades
56	Xavier	Emery		Universidad de Chile	Chile	11	A Comparison of Three Geostatistical Approaches for Co-Simulating Mineral Grades
57	Eduardo	Magri		Universidad de Chile	Chile	11	A Comparison of Three Geostatistical Approaches for Co-Simulating Mineral Grades
58	Victor	Schweikart		Rio Tinto	Australia	110	Remote Operations: Managing the Challenge of Change
59	Enrique	Rubio		DELPHOS	Chile	111	Planning Caving Operations Using Underground Infrastructure Reliability Models, Andina Case Study
60	Gabriel	Pais		REDCO Mining Consultants	Chile	111	Planning Caving Operations Using Underground Infrastructure Reliability Models, Andina Case Study
61	Augusto	Aguayo		Codelco Chile	Chile	111	Planning Caving Operations Using Underground Infrastructure Reliability Models, Andina Case Study
62	Juan	Montes		Codelco Chile	Chile	111	Planning Caving Operations Using Underground Infrastructure Reliability Models, Andina Case Study
63	Nicolas	Spogis		Engineering Simulation and Scientific Software – ESSS	Chile	112	Numerical Coupling Between DEM (Discret Element Method) and FEM (Finite Element Method) – An Industrial Application
64	Daniel	Schiochet Nasato		Engineering Simulation and Scientific Software – ESSS	Chile	112	Numerical Coupling Between DEM (Discret Element Method) and FEM (Finite Element Method) – An Industrial Application
65	Andrés	González		Engineering Simulation and Scientific Software – ESSS	Chile	112	Numerical Coupling Between DEM (Discret Element Method) and FEM (Finite Element Method) – An Industrial Application
66	Rafael Angelo	Tozzo		Vale – Southeast Iron Department – DIFS	Brazil	112	Numerical Coupling Between DEM (Discret Element Method) and FEM (Finite Element Method) – An Industrial Application
67	Laurence	Costa		Vale – Southeast Iron Department – DIFS	Brazil	112	Numerical Coupling Between DEM (Discret Element Method) and FEM (Finite Element Method) – An Industrial Application
68	Idevaldo	Pinali		Vale – Southeast Iron Department – DIFS	Brazil	112	Numerical Coupling Between DEM (Discret Element Method) and FEM (Finite Element Method) – An Industrial Application
69	José Roberto	Nunhez		State University of Campinas - UNICAMP	Brazil	112	Numerical Coupling Between DEM (Discret Element Method) and FEM (Finite Element Method) – An Industrial Application
70	Marcio	Zerwes		Martin Engineering – Brazil	Brazil	113	Chute Transfer Optimization Through Discrete Element Simulation
71	Romualdo	Oliveira		Martin Engineering – Brazil	Brazil	113	Chute Transfer Optimization Through Discrete Element Simulation
72	Nicolas	Spogis		Martin Engineering – Brazil	Brazil	113	Chute Transfer Optimization Through Discrete Element Simulation
73	Daniel	Schiochet Nasato		Engineering Simulation and Scientific Software – ESSS	Chile	113	Chute Transfer Optimization Through Discrete Element Simulation
74	Victor Manuel	Sandoval Sanzana		Engineering Simulation and Scientific Software – ESSS	Chile	113	Chute Transfer Optimization Through Discrete Element Simulation
75	Roberto	Urzúa		Modular Mining Systems	Chile	114	ProVision® System Implementation in Compañia Minera Huasco SA
76	Federico	Arboleda		AcQuire Technology Solutions Pty.	Chile	12	Reducing Costs in Resource Development. Can Geologists Learn from Manufacturers?
77	Craig	Bradley		AcQuire Technology Solutions Pty.		12	Reducing Costs in Resource Development. Can Geologists Learn from Manufacturers?
78	Macgregor	Denton		AcQuire Technology Solutions Pty.		12	Reducing Costs in Resource Development. Can Geologists Learn from Manufacturers?
79	Stephen	Mundell		AcQuire Technology Solutions Pty.		12	Reducing Costs in Resource Development. Can Geologists Learn from Manufacturers?
80	Marianne	Broadgate		AcQuire Technology Solutions Pty.		12	Reducing Costs in Resource Development. Can Geologists Learn from Manufacturers?
81	Mark	Rheinlander		AcQuire Technology Solutions Pty.		12	Reducing Costs in Resource Development. Can Geologists Learn from Manufacturers?
82	Mircea	Georgescu		University of Petrosani	Romania	13	Development Strategy of the Mining Sector in Romania until 2020
83	Maria	Lazar		University of Petrosani	Romania	13	Development Strategy of the Mining Sector in Romania until 2020
84	Mihai	Sorin Gaman		Ministry of Economy	Romania	13	Development Strategy of the Mining Sector in Romania until 2020
85	José Ignacio	Valdivia		Universidad de los Andes	Chile	14	Ultimate Pit Limit Determination Under Price Uncertainty
86	Juan Ignacio	Guzm		Universidad de los Andes	Chile	14	Ultimate Pit Limit Determination Under Price Uncertainty
87	Ben	Groeneveld		Curtin University	Australia	15	Robust open pit mine design under uncertainty
88	Erkan	Topal		Curtin University	Australia	15	Robust open pit mine design under uncertainty
89	Simon	Mortimer		Atticus & Associates	Peru	16	Implicit 3D Modeling – A new era in geological evaluation
90	George	McIsaac		G-MEC S.p.A.	Chile	17	The Master Plan:Get more out of your mine
91	Francisco	Chueco		Sinclair Knight Merz Chile	Chile	18	Cost-effectiveness comparison among grid extension, diesel engines and solar photovoltaic for pumping systems in nothern Chile
92	Fernando	Reyes		Sinclair Knight Merz Chile	Chile	19	Innovative Technologies for Sustainable Mining – the El Teniente Experience
93	Jorge	Revuelta		Codelco Chile	Chile	19	Innovative Technologies for Sustainable Mining – the El Teniente Experience
94	José	Castro		Sinclair Knight Merz	Chile	20	Slurry pipeline energy recovery study
95	Jeff	Bremer		Sinclair Knight Merz	Chile	20	Slurry pipeline energy recovery study
96	Hern	Loyza		Anglo American Chile	Chile	20	Slurry pipeline energy recovery study
97	Carlos	Corral		Universidad de Chile	Chile	21	Modeling equivalent grades in polymetallic deposits
98	Xavier	Emery		Universidad de Chile	Chile	21	Modeling equivalent grades in polymetallic deposits
99	Rodrigo	Zúñiga		Universidad de Chile	Chile	22	Evaluating mineral resources in a narrow vein-type deposit
100	Xavier	Emery		Universidad de Chile	Chile	22	Evaluating mineral resources in a narrow vein-type deposit
101	Pan	Weidong		China University of Mining & Technology in Beijing	China	23	Numerical Modeling in Coal Roof Fracture Mechanics in Fully Mechanized Top Coal Caving Technology
102	Dimitre	Antonov		Curtin Unversity	Australia	23	Numerical Modeling in Coal Roof Fracture Mechanics in Fully Mechanized Top Coal Caving Technology
103	Douglas	Chapman		AMEC International (Chile)	Chile	24	Optimizing Fragmentation for Productivity & Cost
104	Bryan	Maybee		Laurentian University	Canada	25	Optimization of construction and production in a Block Cave operation
105	Anthony	Finch		Snowden Mining Industry Consultants	Canada	26	Maximising Share Holder Value in the Peruvian Andes
106	Alejandro	Cáceres		GeoInnova Consultores Ltda	Chile	27	Speeding up conditional simulation: A memory-hungry approach using sequential Gaussian simulation with residual substitution (SGS-RS)
107	Xavier	Emery		Universidad de Chile	Chile	27	Speeding up conditional simulation: A memory-hungry approach using sequential Gaussian simulation with residual substitution (SGS-RS)
108	Marcelo	Godoy		Golder Associates	Chile	27	Speeding up conditional simulation: A memory-hungry approach using sequential Gaussian simulation with residual substitution (SGS-RS)
109	Alejandro	Cáceres		GeoInnova Consultores Ltda	Chile	28	Truncated Gaussian kriging as an alternative to indicator kriging
110	Xavier	Emery		Universidad de Chile	Chile	28	Truncated Gaussian kriging as an alternative to indicator kriging
111	Rodrigo	Riquelme		GeoInnova Consultores Ltda	Chile	28	Truncated Gaussian kriging as an alternative to indicator kriging
112	Rodrigo Alejandro	Díaz Bórquez		Minera Esperanza	Chile	29	Truck Driver Training at Esperanza Project
113	Donald	Brisebois		Rocmec Mining	Canada	30	Thermal Fragmentation: Reducing mining width when extracting narrow precious metal veins
114	Raymond	Sogna Suglo		University of Mines and Technology	Ghana	31	Computer Simulation – An Aid to Determining Fleet Sizes
115	José M	Garc		GHD Australia	Australia	32	Creating Competitive Advantage in Mining: an illustrative comparison with the Oil Industry. The concept of value in mining
116	Juan	Camus		University of Queensland	Australia	32	Creating Competitive Advantage in Mining: an illustrative comparison with the Oil Industry. The concept of value in mining
117	Peter	Knights		University of Queensland	Australia	32	Creating Competitive Advantage in Mining: an illustrative comparison with the Oil Industry. The concept of value in mining
118	Rolando James	Amasifuen Huam		Mine Ventilation Institute (IVEM)	Peru	33	Proper Application of Axial Fans
119	Carlos	Gardini		Universidad Nacional de San Luis	Argentina	34	Using Geologic Models to Support Resource and Reserve Estimation of Marble Deposits in Complex Settings
120	Mario	Rossi		GeoSystems International, Inc.	USA	34	Using Geologic Models to Support Resource and Reserve Estimation of Marble Deposits in Complex Settings
121	Mario	Baudino		Cementos Avellaneda S.A.	Argentina	34	Using Geologic Models to Support Resource and Reserve Estimation of Marble Deposits in Complex Settings
122	Colin	Badenhorst		BHP Billiton	Australia	35	Collocated Cosimulation with Multivariate Bayesian Updating: a Case Study on the Olympic Dam Deposit
123	Anthony	Bottrill		BHP Billiton	Australia	35	Collocated Cosimulation with Multivariate Bayesian Updating: a Case Study on the Olympic Dam Deposit
124	Shane	O'Connell		BHP Billiton	Australia	35	Collocated Cosimulation with Multivariate Bayesian Updating: a Case Study on the Olympic Dam Deposit
125	Mario	Rossi		GeoSystems International, Inc.	USA	35	Collocated Cosimulation with Multivariate Bayesian Updating: a Case Study on the Olympic Dam Deposit
126	Saeed	Dehghan		Islamic Azad University	Iran	36	Calculation of pillar stress in room and rib pillar mine during the ore exploitation
127	Kamran	Goshtasbi		Tarbiat Modares University	Iran	36	Calculation of pillar stress in room and rib pillar mine during the ore exploitation
128	Parviz	Maarefvand		Amir Kabir University	Iran	36	Calculation of pillar stress in room and rib pillar mine during the ore exploitation
129	Kourosh	Shahriar		Islamic Azad University	Iran	36	Calculation of pillar stress in room and rib pillar mine during the ore exploitation
130	Rodrigo	Riquelme		GeoInnova Consultores Ltda	Chile	37	Application of probabilistic models for construction (indicator cokriging) and validation (Conditional Cosimulation) of resource estimation models in early stages of a project: Quetena case study
131	Carlos	Cisterna		Codelco Norte	Chile	37	Application of probabilistic models for construction (indicator cokriging) and validation (Conditional Cosimulation) of resource estimation models in early stages of a project: Quetena case study
132	Luis	Machuca		CRC Mining / WA School of Mines, Western Australia	Australia	38	In-situ stress measurements below large open pits
133	Ernesto	Villaescusa		CRC Mining / WA School of Mines, Western Australia	Australia	38	In-situ stress measurements below large open pits
134	Chris	Windsor		CRC Mining / WA School of Mines, Western Australia	Australia	38	In-situ stress measurements below large open pits
135	Álvaro	Egaña		Universidad de Chile	Chile	39	Image Segmentation for Mineral Identification in an Oxide Copper Deposit
136	Juli	Ort		Universidad de Chile	Chile	39	Image Segmentation for Mineral Identification in an Oxide Copper Deposit
137	Yang	Xiaocong		Beijing General Research Institute of Mining & Metallurgy	China	40	An Experimental Study on Basic Mechanics of Cemented Rock-Tailings Fill
138	Guo	Lijie		Beijing General Research Institute of Mining & Metallurgy	China	40	An Experimental Study on Basic Mechanics of Cemented Rock-Tailings Fill
139	Vladimir	Malencovi?		HTZ, I.P., d.o.o.	Slovenia	41	Coalmining Enterprises Restructuring Procedures in Slovenia
140	Milan	Medved		Premogovnik Velenje, d.d.	Slovenia	41	Coalmining Enterprises Restructuring Procedures in Slovenia
141	Evgen	Dervari?		University of Ljubljana	Slovenia	41	Coalmining Enterprises Restructuring Procedures in Slovenia
142	Alan	Thompson				42	Rock Reinforcement Terminology and Classification ? An Update
143	Chris	Windsor		CRC Mining/Western Australian School of Mines, Curtin University of Technology	Australia	42	Rock Reinforcement Terminology and Classification ? An Update
144	Ernesto	Villaescusa		CRC Mining/Western Australian School of Mines, Curtin University of Technology	Australia	42	Rock Reinforcement Terminology and Classification ? An Update
145	Rodrigo	Riquelme	GeoInnova Consultores Ltda		Chile	43	Economic ranking of copper mining projects at exploration and early engineering stages. An experimental retrospective-prospective approach.
146	Roberto	Fréraut	Codelco Norte		Chile	43	Economic ranking of copper mining projects at exploration and early engineering stages. An experimental retrospective-prospective approach.
147	Álvaro	Parra	Universidad de Chile		Chile	44	Multi-Point Conditional Unilateral Simulation for Categorical Variables
148	Juli	Ortiz	Universidad de Chile		Chile	44	Multi-Point Conditional Unilateral Simulation for Categorical Variables
149	Sebastián	Hurtado	Universidad de Chile		Chile	45	Quantifying uncertainty in resources tonnage using multiple point geostatistical simulation
150	Julián	Ortiz	Universidad de Chile		Chile	45	Quantifying uncertainty in resources tonnage using multiple point geostatistical simulation
151	Cedomir	Marangunic	Geoestudios Ltda.		Chile	46	Glaciers in High Mountain Mine Explorations and Project Planning
152	Manuel	Rapiman	Minera Escondida		Chile	47	Is Geotechnics a Hindrance or Opportunity in the Development of a Mine Project?
153	José Manuel	Valenzuela	Minera Escondida		Chile	47	Is Geotechnics a Hindrance or Opportunity in the Development of a Mine Project?
154	Julio	Beniscelli	Codelco		Chile	48	Probabilistic Stability Analysis of Mine Waste Slopes
155	Alfredo	Urzua	Prototype Engineering, Inc.		USA	48	Probabilistic Stability Analysis of Mine Waste Slopes
156	John	Christian	Prototype Engineering, Inc.		USA	48	Probabilistic Stability Analysis of Mine Waste Slopes
157	Exequiel	Sepúlveda	Universidad de Chile		Chile	49	Distributed-Multiprocess Implementation of Kriging for the Estimation of Mineral Resources
158	Eduardo	Magri	Universidad de Chile		Chile	49	Distributed-Multiprocess Implementation of Kriging for the Estimation of Mineral Resources
159	Julián	Ortiz	Universidad de Chile		Chile	49	Distributed-Multiprocess Implementation of Kriging for the Estimation of Mineral Resources
160	Rodrigo	Contreras	Universidad de Chile		Chile	50	Mine Planning considering Uncertainty in Grades and Work Index
161	Julián	Ortiz	Universidad de Chile		Chile	50	Mine Planning considering Uncertainty in Grades and Work Index
162	Darko	Danicic	Kolubara Metal d.o.o.		Serbia	51	Optimisation and sustainable development of open cast mining production process in Serbia
163	Vladimir	Pavlovic	Mining faculty Belgrade		Serbia	51	Optimisation and sustainable development of open cast mining production process in Serbia
164	Slobodan	Mitrovic	Electric Power of Serbia		Serbia	51	Optimisation and sustainable development of open cast mining production process in Serbia
165	Sava	Kovacev	Kolubara Metal d.o.o.		Serbia	51	Optimisation and sustainable development of open cast mining production process in Serbia
166	Viviana	Fernández	PUC		Chile	52	Forecasting energy spot prices
167	Francesco	Bressi	CODELCO		Chile	53	Financing Minerals Exploration in Chile: The Corporate Governance Mechanism in Venture Capital Funds
168	Emmanuel	Henry	Amec		Chile	54	Demonstrating Reasonable Prospect of Economic Extraction when Classifying Mineral Resources
169	Alfonso	Ovalle	Amec		Chile	55	Automatic mass caving sequencing using benefit cut-offs
170	Manuel	Aros	Amec		Chile	55	Automatic mass caving sequencing using benefit cut-offs
171	Juan Pablo	Asalgado	Amec		Chile	55	Automatic mass caving sequencing using benefit cut-offs
172	Peter	Bodon	TSG Consulting		Australia	56	Combining optimisation and simulation to model a supply chain all the way from pit to port
173	Chris	Fricke	TSG Consulting		Australia	56	Combining optimisation and simulation to model a supply chain all the way from pit to port
174	Tom	Sandeman	TSG Consulting		Australia	56	Combining optimisation and simulation to model a supply chain all the way from pit to port
175	Chris	Stanford	PT Kaltim Prima Coal		Indonesia	56	Combining optimisation and simulation to model a supply chain all the way from pit to port
176	Hooman	Askari-Nasab	University of Alberta		Canada	57	Fuzzy C-Means Clustering Algorithm for Block Aggregation in Open Pit Mines
177	Ernesto	Arancibia	Universidad de Chile		Chile	58	A review of controlled recirculation for deep underground block caving mines
178	Raúl	Castro	Universidad de Chile		Chile	58	A review of controlled recirculation for deep underground block caving mines
179	Claudio	Gutiérrez	Universidad de Chile		Chile	58	A review of controlled recirculation for deep underground block caving mines
180	Roberto	León	Arcadis Geotécnica		Chile	59	Collapsible behaviour of the ore in heap leach pads implications for the design
181	Edgar	Bard	Arcadis Geotécnica		Chile	59	Collapsible behaviour of the ore in heap leach pads implications for the design
182	José	Campaña	Arcadis Geotécnica		Chile	59	Collapsible behaviour of the ore in heap leach pads implications for the design
183	Victor	Cordoba	CRU Strategies Chile		Chile	60	Simulation of mining operations
184	Mauricio	Contreras	CRU Strategies Chile		Chile	60	Simulation of mining operations
185	Rolando	Iay	CRU Strategies Chile		Chile	60	Simulation of mining operations
186	Juan Pablo	Asalgado	Amec		Chile	61	“Rapid Assessment of the Underground Potential of a Mineral Deposit”
187	Emmanuel	Henry	Amec		Chile	61	“Rapid Assessment of the Underground Potential of a Mineral Deposit”
188	Francisco	Albor Consuegra	McGill University		Canada	63	Quantifying Multi-Element and Volumetric Uncertainty for Mining Method Selection, Coleman McCreedy Deposit, Ontario, Canada
189	Roussos	Dimitrakopoulos	McGill University		Canada	63	Quantifying Multi-Element and Volumetric Uncertainty for Mining Method Selection, Coleman McCreedy Deposit, Ontario, Canada
190	Ryan	Goodfellow	McGill University		Canada	63	Quantifying Multi-Element and Volumetric Uncertainty for Mining Method Selection, Coleman McCreedy Deposit, Ontario, Canada
191	Timothy	Lloyd	Vale Inco		Canada	63	Quantifying Multi-Element and Volumetric Uncertainty for Mining Method Selection, Coleman McCreedy Deposit, Ontario, Canada
192	Karin	Olson Hoal	Colorado School of Mines		USA	64	The Business Case for Effective, Integrated Materials Characterization in Mining Projects
193	Jane	Stammer	Colorado School of Mines		USA	64	The Business Case for Effective, Integrated Materials Characterization in Mining Projects
194	Jocelyn K.	Ross	Colorado School of Mines		USA	64	The Business Case for Effective, Integrated Materials Characterization in Mining Projects
195	Conor	Meagher	McGill University		Canada	65	Open Pit Mine Design with a Minimum Cut Algorithm under Jointly Uncertain Ore Supply and Metal Demand
196	Roussos	Dimitrakopoulos	McGill University		Canada	65	Open Pit Mine Design with a Minimum Cut Algorithm under Jointly Uncertain Ore Supply and Metal Demand
197	David	Avis	McGill University		Canada	65	Open Pit Mine Design with a Minimum Cut Algorithm under Jointly Uncertain Ore Supply and Metal Demand
198	Roussos	Dimitrakopoulos	McGill University		Canada	66	Stochastic Mine Planning Optimization: New concepts, applications and monetary value in an ever uncertain market
199	Luis	Montiel	McGill University		Canada	67	Stochastic mine production schedulling and optimal production rates
200	Roussos	Dimitrakopoulos	McGill University		Canada	67	Stochastic mine production schedulling and optimal production rates
201	Hussein	Mustapha	McGill University		Canada	68	Simulation of Geologically Complex Mineral Deposits: New High-Order Models through Spatial Cumulants
202	Roussos	Dimitrakopoulos	McGill University		Canada	68	Simulation of Geologically Complex Mineral Deposits: New High-Order Models through Spatial Cumulants
203	Sabry	Abdel Sabour	McGill University		Canada	69	Mine Design under Geologic and Market Uncertainties
204	Roussos	Dimitrakopoulos	McGill University		Canada	69	Mine Design under Geologic and Market Uncertainties
205	Snehamoy	Chatterjee	McGill University		Canada	70	A Two-phase Heuristic Method for Constrained Pushback Design
206	Amina	Lamghari	McGill University		Canada	70	A Two-phase Heuristic Method for Constrained Pushback Design
207	Roussos	Dimitrakopoulos	McGill University		Canada	70	A Two-phase Heuristic Method for Constrained Pushback Design
208	Karim	Batallanos	BHP Billiton		Chile	71	Geometallurgical model: the new status for leaching bussiness of clays in CMCC
209	Gonzalo	Mendoza	BHP Billiton		Chile	71	Geometallurgical model: the new status for leaching bussiness of clays in CMCC
210	Eduardo	Patiño	BHP Billiton		Chile	71	Geometallurgical model: the new status for leaching bussiness of clays in CMCC
211	Jorge	Picarte	BHP Billiton		Chile	71	Geometallurgical model: the new status for leaching bussiness of clays in CMCC
212	Huan	Xu	BHP Billiton		Chile	72	Robust Mine Scheduling with Parametric Regret Minimization: Method and Example
213	Roussos	Dimitrakopoulos	McGill University		Canada	72	Robust Mine Scheduling with Parametric Regret Minimization: Method and Example
214	Putra	Manggala	McGill University		Canada	72	Robust Mine Scheduling with Parametric Regret Minimization: Method and Example
215	Neal	Harries	GroundProbe Pty. Ltd.		Australia	73	Slope stability radar (ssr) use in South American open?cut mining operations
216	Albert	Cornejo	GroundProbe Pty. Ltd.		Australia	73	Slope stability radar (ssr) use in South American open?cut mining operations
217	Rodrigo	Oyab	GroundProbe South America			73	Slope stability radar (ssr) use in South American open?cut mining operations
218	Victor	Vidal	McGill University		Canada	74	Meeting Mill Capacity using Dynamic Cut-off Grade Optimization: Application at the Escondida copper mine, Chile
219	Roussos	Dimitrakopoulos	McGill University		Canada	74	Meeting Mill Capacity using Dynamic Cut-off Grade Optimization: Application at the Escondida copper mine, Chile
220	Pablo	Morales Leiva	Deloitte		Chile	75	An adapted innovation & knowledge management process for mining companies
221	Fernando	Acosta	Universiad de Chile		Chile	76	Impact of macroeconomic variables in the cycle of mineral commodity prices
222	JÖrg	Benndorf	MIBRAG		Germany	77	Investigating the variability of key coal quality parameters in continuous mining operations as function of the operating mode
223	Sebastián	Carmona	Universidad de Chile		Chile	78	Geological Modeling and Metallurgical Prediction Supported by Linear and Non Linear Statistics
224	Julián	Ortiz	Universidad de Chile		Chile	78	Geological Modeling and Metallurgical Prediction Supported by Linear and Non Linear Statistics
225	David	Morrison	Sinclair Knight Merz		Australia	80	Developing the Fully Truckless Mine
226	Joanne	Gardiner	Sinclair Knight Merz		Australia	80	Developing the Fully Truckless Mine
227	David	Morrison	Sinclair Knight Merz		Australia	81	Handling High Grade Ore, Low Grade Ore and Waste Simultaneously in a Truckless Mining Operation
228	David	Rea	Sinclair Knight Merz		Australia	81	Handling High Grade Ore, Low Grade Ore and Waste Simultaneously in a Truckless Mining Operation
229	Ivy	Lourel	Sinclair Knight Merz		Australia	82	Economic Assessment of Truckless Mining Arrangements
230	David	Morrison	Sinclair Knight Merz		Australia	82	Economic Assessment of Truckless Mining Arrangements
231	Joanne	Gardiner	Sinclair Knight Merz		Australia	82	Economic Assessment of Truckless Mining Arrangements
232	Enrique	Acuña	Laurentian University		Canada	83	Justification for the use of regulators by the use of GAs in free splitting and semi controlled network optimization
233	Stephen	Hall	Laurentian University		Canada	83	Justification for the use of regulators by the use of GAs in free splitting and semi controlled network optimization
234	Brett	King	STOPS		Australia	84	Optimal Mining Principles II
235	Cheryl	Allen	Vale Inco		Canada	85	Variable Frequency Drives as Applied to Ventilation Systems
236	Robert	DaPrat	Rockwell Automation		Canada	85	Variable Frequency Drives as Applied to Ventilation Systems
237	Martin	Smith	Pty Ltd		Australia	86	Strategy Optimisation for the Prominent Hill Mining Complex
238	Diniz	Tamantini Ribeiro	Vale		Brazil	87	An indicator geostatistical approach to support mineral resource classification
239	Debora	Rold	Vale		Brazil	87	An indicator geostatistical approach to support mineral resource classification
240	Marcelo	Vidigal	Vale		Brazil	87	An indicator geostatistical approach to support mineral resource classification
241	Cid	Monteiro	Vale		Brazil	87	An indicator geostatistical approach to support mineral resource classification
242	Alexandre	Boucher	Stanford University		USA	88	Multivariate simulation on block scale: an open source implementation on SGeMS
243	Christoph	MÜller	IREDES International		Germany	89	IREDES: Architecture of the IT Standard for Mining Process Optimization
244	Guangxi	Chen	IREDES International		Germany	89	IREDES: Architecture of the IT Standard for Mining Process Optimization
245	Christoph	MÜller	IREDES International		Germany	90	Efficiency in mining production by process optimization: Status and preconditions
246	JÖrgen	Appelgren	Atlas Copco Rock Drills AB		Sweden	91	Applications of the IREDES standard in surface and underground drilling
247	Rolf	Elsrud	Atlas Copco Rock Drills AB		Sweden	91	Applications of the IREDES standard in surface and underground drilling
248	Lars	Eriksson	Atlas Copco Rock Drills AB		Sweden	91	Applications of the IREDES standard in surface and underground drilling
249	Marco	Cornejo		REDCO	Chile	95	Modelo de Confiabilidad Operacional Mina Chuquicamata
250	Galo	Muñoz		Codelco Norte	Chile	95	Modelo de Confiabilidad Operacional Mina Chuquicamata
251	David	Beck		Beck Arndt Engineering	Australia	96	Simulation Aided Engineering: integration of monitoring, modelling and planning
252	Dylan	Webb		Datamine Corporate Limited	UK	97	Integrated Mine Planning- The Future is Now
253	Gavin	Ferguson		Seltrust Associates Ltd.	Scotland	98	Developing realistic mine plans applying risk management protocols
254	Richard	Gawthorpe		ATD	South Africa	99	Geological Risk Assessment applied to Strategic Mine Planning