Automatic Mining Research Articles

海底採掘ロボット用位置計測センサの研究

海底採掘ロボット用位置計測センサの研究

Editorial to "The best papers from the 32nd International Symposium on Automation and Robotics in Construction and Mining (ISARC 2015)"

Editorial to "The best papers from the 32nd International Symposium on Automation and Robotics in Construction and Mining (ISARC 2015)"

Prospects for application of robotic mechano-hydraulical excavation of gas-bearing coal layers at great depths

In the paper the scientific basis for robotic technology of excavation prone to gas- dynamic phenomena of a coal layer with high gas-bearing capacity at great depths is developed. The constructive scheme of automated remote-controlled mining robot, that fractures coal by high-pressure hydraulic jets in the gas polluted environment, is proposed.

Multi sensor data fusion for 6D pose estimation and 3D underground mine mapping using autonomous mobile robot

ABSTRACTSimultaneous localisation and mapping by using a robot is indeed a challenging and critically important problem for an accurate 3D underground mine mapping. Using 6D pose information of a robot (x, y and z coordinates and the yaw, pitch and roll angles), the robot vehicle can be tracked, which is very crucial for an accurate mine mapping. The estimation of 6D robot pose on the ground surface is easy and generally accomplished by either the Global Positioning System (GPS) or by putting some artificial visual landmarks. However, in the underground mining environment, the estimation of pose becomes difficult due to the unavailability of the GPS signal and the identification of landmarks (as surface wall of the underground mine is rough). In this paper, an attempt has been made to construct a 3D underground mine map using a prototype mine robot. For this purpose, a strategy for the underground mine robot pose estimation is devised with the help of multi-sensor data fusion techniques. A shaft-encoder (wheel odometry), Inertial Measurement Unit (IMU) and a rotated 2D Laser Scanner is used to improve and rectify the 6D robot pose as well as 3D mine map. An autonomous prototype robot is built up and allowed to navigate in a real underground mine gallery to validate our algorithm. Generated 3D map has been compared with the actual map available. The outputs of this study are highlighted in this paper.

Enhancing web search with queries of equivalent intents

Users often issue all kinds of queries to look for the same target due to the intrinsic ambiguity and flexibility of natural languages. Some previous work clusters queries based on co-clicks; however, the intents of queries in one cluster are not that similar but roughly related. It is desirable to conduct automatic mining of queries with equivalent intents from a large scale search logs. In this paper, we take account of similarities between query strings. There are two issues associated with such similarities: it is too costly to compare any pair of queries in large scale search logs, and two queries with a similar formulation, such as "SVN" (Apache Subversion) and support vector machine (SVM), are not necessarily similar in their intents. To address these issues, we propose using the similarities of query strings above the co-click based clustering results. Our method improves precision over the co-click based clustering method (lifting precision from 0.37 to 0.62), and outperforms a commercial search engine's query alteration (lifting $$F_1$$F1 measure from 0.42 to 0.56). As an application, we consider web document retrieval. We aggregate similar queries' click-throughs with the query's click-throughs and evaluate them on a large scale dataset. Experimental results indicate that our proposed method significantly outperforms the baseline method of using a query's own click-throughs in all metrics.

User session level diverse reranking of search results

Most Web search diversity approaches can be categorized as Document Level Diversification (DocLD), Topic Level Diversification (TopicLD) or Term Level Diversification (TermLD). DocLD selects the relevant documents with minimal content overlap to each other. It does not take the coverage of query subtopics into account. TopicLD solves this by modeling query subtopics explicitly. However, the automatic mining of query subtopics is difficult. TermLD tries to cover as many query topic terms as possible, which reduces the task of finding a query's subtopics into finding a set of representative topic terms. In this paper, we propose a novel User Session Level Diversification (UserLD) approach based on the observation that a query's subtopics are implicitly reflected by the search intents in different user sessions. Our approach consists of two phases: (I) Session Graph Construction and (II) Diversity Reranking. For a given query, phase (I) builds a Session Graph which considers relevant user sessions and preliminary retrieval results as nodes and the nodes' pairwise similarities as edge weights. Phase (II) reranks the preliminary retrieval results by minimizing a Session Graph based diversity loss function. Extensive experiments on two standard datasets of NACSIS Test Collections for IR (NTCIR) demonstrate the effectiveness of our approach. The advantage of our approach lies in its ability of avoiding mining the query subtopics in advance while achieving almost the same or better performances compared with previous approaches.

Education Web Information Retrieval and Classification with Big Data Analysis

This paper discusses the text mining method to obtain the education web information rules. The method can be applied to words and parts of speech in texts to record the two-tier structure of automatic mining. On the basis of the initial discovery of the labeling rules, we put forward the linguistic features based on words to expand the application of the approaches. The web information retrieval mechanism is proposed based on web content segmentation. In addition, we build a rule matching method to improve performance of rule utilization, in terms of information of interest to the user and the extent to the interesting part. In conclusion, the use of automatic labeling rules can make part of the tagging accuracy rate reach a new height.

Research on Path Planning Method of Coal Mine Robot to Avoid Obstacle in Gas Distribution Area

As the explosion-proof safety level of a coal mine robot has not yet reached the level of intrinsic safety “ia” and it cannot work in a dangerous gas distribution area, therefore, path planning methods for coal mine robot to avoid the dangerous area of gas are necessary. In this paper, to avoid a secondary explosion when the coal mine robot passes through gas hazard zones, a path planning method is proposed with consideration of gas concentration distributions. First, with consideration of gas distribution area and obstacles, MAKLINK method is adopted to describe the working environment network diagram of the coal mine robot. Second, the initial working paths for the coal mine robot are obtained based on Dijkstra algorithm, and then the global optimal working path for the coal mine robot is obtained based on ant colony algorithm. Lastly, experiments are conducted in a roadway after an accident, and results by different path planning methods are compared, which verified the effectiveness of the proposed path planning method.

Robot miners of the briny deep

For decades, futurists have predicted that commercial miners would one day tap the unimaginable mineral wealth of the world's ocean floor. Soon, that subsea gold rush could finally begin: The world's first deepsea mining robots are poised to rip into rich deposits of copper, gold, and silver 1,600 meters down at the bottom of the Bismarck Sea, near Papua New Guinea. The massive machines, which are to be tested later this year, are part of a high-stakes gamble for the Toronto-based mining company Nautilus Minerals.

Gap size effect on the tribological characteristics of the roller for deep-sea mining robot

ABSTRACTTo design the deep-sea mining robot, it is essential to analyze the tribological characteristics of its roller. In this study, we introduced the dynamic simulation model to analyze the tribological characteristics of the roller for deep-sea mining robot, considering the temperature, viscosity, viscous damping force, and gap size between the inner and outer rib seals. Effective viscosity changes with gap size in micro/nanoscale while the effective viscosity is equal to the kinematic viscosity in macroscale. For the stable operation of the roller, the effective viscosity must be less than the critical viscosity. As the gap size decreases, the effective viscosity increases while the critical viscosity decreases. This study shows that the gap size between the inner and outer rib seals of roller is the most dominant factor in designing the roller for deep-sea mining robot to use at relatively low temperatures that are found in the deep-sea environments.

실해역 시험 데이터를 이용한 파일럿 채광로봇 엄빌리컬 케이블의 축진동 해석

실해역 시험 데이터를 이용한 파일럿 채광로봇 엄빌리컬 케이블의 축진동 해석

심해 장비용 압력보상유의 압축성 계수 측정을 위한 실험적 연구

In order to determine the appropriate volume of the a pressure compensator of deep seabed mining robots, this paper reports on an experimental test for oil volume change in an oil-filled box. At the design stage of underwater robots, it is crucial to determine the capacity of the hydraulic compensator which is replenished as much as the contracted oil volume of the robots. A pilot mining robot, MienRo was designed to work under 6,000 m in the deep sea. The hydraulic actuating oil and pressure compensating oil of MineRo may be exposed at a hydrostatic pressure environment of 600 bar. Although the oil can be assumed to be incompressible, its volume is actually changed under high pressure conditions due to air contained in the oil and oil contraction. To determine the capacity of the pressure compensator, the oil contraction rate should be verified through an experimental test using a hyperbaric chamber.

IJARCCE - Computer and Communication Engineering

Every software Industry requires the quality of code. Formal specifications can help with program testing, optimization, reface, documentation, and, great significance debugging and restore however, they are difficult to do manually, and automatic mining techniques suffer from 90-99% false positive rates. To address those problems this project proposes to temporal-property miner by incorporating code quality metrics. This measure code quality by extracting additional information from the software engineering process, and using this information from code that is more equal to be correct as well as code that is less equal to be correct. When used as a preliminary processing step for an existing specification miner, project technique identifies which input is most correct program, the same number of specifications using only 45% of their original input. As a novel inference technique, this approach has few false positives in practice (63% when balancing precision and recall, 3% when focused on precision), even though finding useful specifications (e.g. find many bugs) on over 1.5 million lines of code.

A formal method for rule analysis and validation in distributed data aggregation service

The usage of Cloud Serviced has increased rapidly in the last years. Data management systems, behind any Cloud Service, are a major concern when it comes to scalability, flexibility and reliability due to being implemented in a distributed way. A Distributed Data Aggregation Service relying on a storage system meets these demands and serves as a repository back-end for complex analysis and automatic mining of any type of data. In this paper we continue our previous work on data management in Cloud storage. We present a formal approach to express retrieval and aggregation rules with a compact, yet powerful tool called Rule Markup Language. Our extended solution proposes a standard form to schemes and uses the tool to match the rules to the XML form of the structured data in order to obtain the unstructured entries from BlobSeer data storage system. This allows the Distributed Data Aggregation Service (DDAS) to bypass several steps when processing a retrieval request. Our new architecture is more loosely-coupled with a separate module, the new tool, used for transforming the XML entries to standard XML files which represent the final result. We model the dynamic behavior of the system using this new standard to ensure a simpler and efficient representation of the operations performed by the client while maintaining the constraints imposed by a distributed system running in the Cloud. Furthermore we prove that this method correctly performs the translation between the storage model's unstructured view of data and the client's structured objects.

Automatic Mining of Numerical Classification Rules with Parliamentary Optimization Algorithm

Automatic Mining of Numerical Classification Rules with Parliamentary Optimization Algorithm

A study of the kinematic characteristic of a coupling device between the buffer system and the flexible pipe of a deep-seabed mining system

This paper concerns the kinematic characteristics of a coupling device in a deep-seabed mining system. This coupling device connects the buffer system and the flexible pipe. The motion of the buffer system, flexible pipe and mining robot are affected by the coupling device. So the coupling device should be considered as a major factor when this device is designed. Therefore, we find a stable kinematic device, and apply it to the design coupling device through this study. The kinematic characteristics of the coupling device are analyzed by multi-body dynamics simulation method, and finite element method. The dynamic analysis model was built in the commercial software DAFUL. The Fluid Structure Interaction (FSI) method is applied to build the deep-seabed environment. Hydrodynamic force and moment are applied in the dynamic model for the FSI method. The loads and deformation of flexible pipe are estimated for analysis results of the kinematic characteristics.

A Statistical Approach to Automatically Detect How Many Persons Appear in a Video

Face indexing is a very popular research topic and it has been investigated over the last 10 years. It can be used for a wide range of applications such as automatic video content analysis, data mining, video annotation and labeling, etc. In this work a statistical approach to address this challenging issue is presented: the number of persons that are present in a generic video (even having low resolution and/or taken from a mobile camera) is automatically detected and also the intervals of frames in which each person appears are extracted. The main contributions of the proposed work are that no initializations neither a priory knowledge about the scene contents are required. Moreover, this approach introduces a generalized version of the k-means method that, through different statistical indices, automatically determines the number of people in the scene.

Fuzzy Logic Control Based Navigation Research for Mine Rescue Robot in Unknown Environments

This paper proposes the research significance of mine rescue robot which can assist rescuers to enter into the disaster site, and can use its own merits to explore the environments and to reach the location of the trapped workers quickly. It reduces the danger of accidents, and improves aid efficiency. This paper summarizes the status of mine rescue robot, and compares with commonly used external sensors. Ultrasonic ranging sensors are selected as part of the ranging system. In addition, navigation research for mine robot is the key in this paper. According to the features of robots working environments which is unknown and uncertain, fuzzy logic control, a simple robustness navigation controlling algorithm with fault toleration, is selected to achieve navigation mission. The experimental results show that it achieves the desired effect.

직교 배열표를 이용한 심해저 채광로봇 미내로의 주행 특성 연구

KRISO(Korea Research Institute of Ships & Ocean Engineering) designed and manufactured a pilot mining robot called "MineRo" in 2012. MineRo is composed of four track modules. In general, much time and money are needed for deep-sea tests. Therefore, a numerical analysis to predict the dynamic behaviors has to be performed before a deep-sea test. In the numerical analysis, the information about the mining robot and soil properties are the most important factors to analyze the driving performance and dynamic response of MineRo. A terra-mechanics model of extremely cohesive soft soil is implemented in the form of the relationships between the normal pressure and sinkage, and between the shear stress and shear displacement. It is possible to acquire information about MineRo from the CAD model in the design phase. The Wong model is applied to the terra-mechanics model. This model is necessary to acquire many soil coefficients for a numerical analysis. However, in soil testing, the amount of soil property data obtained is limited. Moreover, it is difficult to analyze all of the cases for the many soil coefficients. In this paper, the dynamic behaviors of MineRo are analyzed according to the driving velocity, steering ratio, and variable extremely cohesive soft soil properties using a table of orthogonal arrays. The dynamic responses of MineRo are the turning radius, sinkage, and slip ratio. The relationships between the dynamic responses and variable soil properties are derived for MineRo.

Construction automatique d’un lexique de n-grammes pour la fouille d’opinion

Many automatic opinion mining methods make use of a lexicon in which each word is associated with a degree of polarity. The construction of such a kind of linguistic resources has become an important field of research in computational linguistics. Automatic techniques have been developed over the last decade and their effectiveness has been confirmed. This paper proposes to extend these techniques to the analysis of n-grams of words and to determine the potential benefits of this extension. An experiment based on a large corpus of movie reviews indicates that n-grams are more reliable indicators of polarity than words and that their combination with these words allows a better prediction of the polarity of texts. Highlighting the limitations of this study, the conclusion discuses some suggestions for future research