Search results for: underground mining
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 669

Search results for: underground mining

249 Utilizing 5G Mobile Connection as a Node in Layer 1 Proof of Authority Blockchain Used for Microtransaction

Authors: Frode van der Laak

Abstract:

The paper contributes to the feasibility of using a 5G mobile connection as a node for a Proof of Authority (PoA) blockchain, which is used for microtransactions at the same time. It uses the phone number identity of the users that are linked to the crypto wallet address. It also proposed a consensus protocol based on PoA blockchain; PoA is a permission blockchain where consensus is achieved through a set of designated authority rather than through mining, as is the case with a Proof of Work (PoW) blockchain. This report will first explain the concept of a PoA blockchain and how it works. It will then discuss the potential benefits and challenges of using a 5G mobile connection as a node in such a blockchain, and finally, the main open problem statement and proposed solutions with the requirements.

Keywords: 5G, mobile, connection, node, PoA, blockchain, microtransaction.

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248 Distributed Automation System Based Remote Monitoring of Power Quality Disturbance on LV Network

Authors: Emmanuel D. Buedi, K. O. Boateng, Griffith S. Klogo

Abstract:

Electrical distribution networks are prone to power quality disturbances originating from the complexity of the distribution network, mode of distribution (overhead or underground) and types of loads used by customers. Data on the types of disturbances present and frequency of occurrence is needed for economic evaluation and hence finding solution to the problem. Utility companies have resorted to using secondary power quality devices such as smart meters to help gather the required data. Even though this approach is easier to adopt, data gathered from these devices may not serve the required purpose, since the installation of these devices in the electrical network usually does not conform to available PQM placement methods. This paper presents a design of a PQM that is capable of integrating into an existing DAS infrastructure to take advantage of available placement methodologies. The monitoring component of the design is implemented and installed to monitor an existing LV network. Data from the monitor is analyzed and presented. A portion of the LV network of the Electricity Company of Ghana is modeled in MATLAB-Simulink and analyzed under various earth fault conditions. The results presented show the ability of the PQM to detect and analyze PQ disturbance such as voltage sag and overvoltage. By adopting a placement methodology and installing these nodes, utilities are assured of accurate and reliable information with respect to the quality of power delivered to consumers.

Keywords: Power quality, remote monitoring, distributed automation system, economic evaluation, LV network.

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247 Representing Data without Lost Compression Properties in Time Series: A Review

Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

Abstract:

Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.

Keywords: Compression properties, uncertainty, uncertain time series, mining technique, weather prediction.

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246 Investigating the Precipitation and Temperature Change Procedure in Zayanderood Watershed

Authors: Amir Gandomkar

Abstract:

Global warming and continental changes have been one of the people's issues in the recent years and its consequences have appeared in the most parts of the earth planet or will appear in the future. Temperature and Precipitation are two main parameters in climatology. Any changes in these two parameters in this region cause widespread changes in the ecosystem and its natural and humanistic structure. One of the important consequences of this procedure is change in surface and underground water resources. Zayanderood watershed basin which is the main central river in Iran has faced water shortage in the recent years and also it has resulted in drought in Gavkhuni swamp and the river itself. Managers and experts in provinces which are the Zayanderood water consumers believe that global warming; raining decrease and continental changes are the main reason of water decrease. By statistical investigation of annual Precipitation and 46 years temperature of internal and external areas of Zayanderood watershed basin's stations and by using Kendal-man method, Precipitation and temperature procedure changes have been analyzed in this basin. According to obtained results, there was not any noticeable decrease or increase procedure in Precipitation and annual temperature in the basin during this period. However, regarding to Precipitation, a noticeable decrease and increase have been observed in small part of western and some parts of eastern and southern basin, respectively. Furthermore, the investigation of annual temperature procedure has shown that a noticeable increase has been observed in some parts of western and eastern basin, and also a noticeable increasing procedure of temperature in the central parts of metropolitan Esfahan can be observed.

Keywords: Zayanderood, Man_Kendal, Climate Change

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245 Experience Modularization for New Value of Evanescent Cultural Communities: Developing Creative Tourism Services in Bangkok

Authors: Wuttigrai Ngamsirijit

Abstract:

Creative tourism is an ongoing development in many countries as an attempt to moving away from serial reproduction of culture and reviving the culture. Despite, in the destinations with diverse and potential cultural resources, creating new tourism services can be vague. This paper presents how tourism experiences are modularized and consolidated in order to form new creative tourism service offerings in evanescent cultural communities of Bangkok, Thailand. The benefits from data mining in accommodating value co-creation are discussed, and implication of experience modularization to national creative tourism policy is addressed.

Keywords: Co-creation, Creative tourism, New Service Design

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244 MCOKE: Multi-Cluster Overlapping K-Means Extension Algorithm

Authors: Said Baadel, Fadi Thabtah, Joan Lu

Abstract:

Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold be defined a priori which can be difficult to determine by novice users.

Keywords: Data mining, k-means, MCOKE, overlapping.

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243 Decontamination of Chromium Containing Ground Water by Adsorption Using Chemically Modified Activated Carbon Fabric

Authors: J. R. Mudakavi, K. Puttanna

Abstract:

Chromium in the environment is considered as one of the most toxic elements probably next only to mercury and arsenic. It is acutely toxic, mutagenic and carcinogenic in the environment. Chromium contamination of soil and underground water due to industrial activities is a very serious problem in several parts of India covering Karnataka, Tamil Nadu, Andhra Pradesh etc. Functionally modified Activated Carbon Fabrics (ACF) offer targeted chromium removal from drinking water and industrial effluents. Activated carbon fabric is a light weight adsorbing material with high surface area and low resistance to fluid flow. We have investigated surface modification of ACF using various acids in the laboratory through batch as well as through continuous flow column experiments with a view to develop the optimum conditions for chromium removal. Among the various acids investigated, phosphoric acid modified ACF gave best results with a removal efficiency of 95% under optimum conditions. Optimum pH was around 2 – 4 with 2 hours contact time. Continuous column experiments with an effective bed contact time (EBCT) of 5 minutes indicated that breakthrough occurred after 300 bed volumes. Adsorption data followed a Freundlich isotherm pattern. Nickel adsorbs preferentially and sulphate reduces chromium adsorption by 50%. The ACF could be regenerated up to 52.3% using 3 M NaOH under optimal conditions. The process is simple, economical, energy efficient and applicable to industrial effluents and drinking water.

Keywords: Activated carbon fabric, adsorption, drinking water, hexavalent chromium.

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242 Advanced Numerical and Analytical Methods for Assessing Concrete Sewers and Their Remaining Service Life

Authors: Amir Alani, Mojtaba Mahmoodian, Anna Romanova, Asaad Faramarzi

Abstract:

Pipelines are extensively used engineering structures which convey fluid from one place to another. Most of the time, pipelines are placed underground and are encumbered by soil weight and traffic loads. Corrosion of pipe material is the most common form of pipeline deterioration and should be considered in both the strength and serviceability analysis of pipes. The study in this research focuses on concrete pipes in sewage systems (concrete sewers). This research firstly investigates how to involve the effect of corrosion as a time dependent process of deterioration in the structural and failure analysis of this type of pipe. Then three probabilistic time dependent reliability analysis methods including the first passage probability theory, the gamma distributed degradation model and the Monte Carlo simulation technique are discussed and developed. Sensitivity analysis indexes which can be used to identify the most important parameters that affect pipe failure are also discussed. The reliability analysis methods developed in this paper contribute as rational tools for decision makers with regard to the strengthening and rehabilitation of existing pipelines. The results can be used to obtain a cost-effective strategy for the management of the sewer system.

Keywords: Reliability analysis, service life prediction, Monte Carlo simulation method, first passage probability theory, gamma distributed degradation model.

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241 Reasons for Non-Applicability of Software Entropy Metrics for Bug Prediction in Android

Authors: Arvinder Kaur, Deepti Chopra

Abstract:

Software Entropy Metrics for bug prediction have been validated on various software systems by different researchers. In our previous research, we have validated that Software Entropy Metrics calculated for Mozilla subsystem’s predict the future bugs reasonably well. In this study, the Software Entropy metrics are calculated for a subsystem of Android and it is noticed that these metrics are not suitable for bug prediction. The results are compared with a subsystem of Mozilla and a comparison is made between the two software systems to determine the reasons why Software Entropy metrics are not applicable for Android.

Keywords: Android, bug prediction, mining software repositories, Software Entropy.

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240 Effect of Cavities on the Behaviour of Strip Footing Subjected to Inclined Load

Authors: Ali A. Al-Jazaairry, Tahsin T. Sabbagh

Abstract:

One of the important concerns within the field of geotechnical engineering is the presence of cavities in soils. This present work is an attempt to understand the behaviour of strip footing subjected to inclined load and constructed on cavitied soil. The failure mechanism of strip footing located above such soils was studied analytically. The capability of analytical model to correctly expect the system behaviour is assessed by carrying out verification analysis on available studies. The study was prepared by finite element software (PLAXIS) in which an elastic-perfectly plastic soil model was used. It was indicated, from the results of the study, that the load carrying capacity of foundation constructed on cavity can be analysed well using such analysis. The research covered many foundation cases, and in each foundation case, there occurs a critical depth under which the presence of cavities has shown minimum impact on the foundation performance. When cavities are found above this critical depth, the load carrying capacity of the foundation differs with many influences, such as the location and size of the cavity and footing depth. Figures involving the load carrying capacity with the affecting factors studied are presented. These figures offer information beneficial for the design of strip footings rested on underground cavities. Moreover, the results might be used to design a shallow foundation constructed on cavitied soil, whereas the obtained failure mechanisms may be employed to improve numerical solutions for this kind of problems.

Keywords: Axial load, cavity, inclined load, strip footing.

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239 Conjunctive Surface Runoff and Groundwater Management in Salinity Soils

Authors: S. Chuenchooklin, T. Ichikawa, P. Mekpruksawong

Abstract:

This research was conducted in the Lower Namkam Irrigation Project situated in the Namkam River Basin in Thailand. Degradation of groundwater quality in some areas is caused by saline soil spots beneath ground surface. However, the tail regulated gate structure on the Namkam River, a lateral stream of the Mekong River. It is aimed for maintaining water level in the river at +137.5 to +138.5 m (MSL) and flow to the irrigation canals based on a gravity system since July 2009. It might leach some saline soil spots from underground to soil surface if lack of understanding of the conjunctive surface water and groundwater behaviors. This research has been conducted by continuously the observing of both shallow and deep groundwater level and quality from existing observation wells. The simulation of surface water was carried out using a hydrologic modeling system (HEC-HMS) to compute the ungauged side flow catchments as the lateral flows for the river system model (HEC-RAS). The constant water levels in the upstream of the operated gate caused a slight rising up of shallow groundwater level when compared to the water table. However, the groundwater levels in the confined aquifers remained less impacted than in the shallow aquifers but groundwater levels in late of wet season in some wells were higher than the phreatic surface. This causes salinization of the groundwater at the soil surface and might affect some crops. This research aims for the balance of water stage in the river and efficient groundwater utilization in this area.

Keywords: Surface water, groundwater observation, irrigation, water balance.

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238 Topology Preservation in SOM

Authors: E. Arsuaga Uriarte, F. Díaz Martín

Abstract:

The SOM has several beneficial features which make it a useful method for data mining. One of the most important features is the ability to preserve the topology in the projection. There are several measures that can be used to quantify the goodness of the map in order to obtain the optimal projection, including the average quantization error and many topological errors. Many researches have studied how the topology preservation should be measured. One option consists of using the topographic error which considers the ratio of data vectors for which the first and second best BMUs are not adjacent. In this work we present a study of the behaviour of the topographic error in different kinds of maps. We have found that this error devaluates the rectangular maps and we have studied the reasons why this happens. Finally, we suggest a new topological error to improve the deficiency of the topographic error.

Keywords: Map lattice, Self-Organizing Map, topographic error, topology preservation.

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237 Natural Gas Dehydration Process Simulation and Optimization: A Case Study of Khurmala Field in Iraqi Kurdistan Region

Authors: R. Abdulrahman, I. Sebastine

Abstract:

Natural gas is the most popular fossil fuel in the current era and future as well. Natural gas is existed in underground reservoirs so it may contain many of non-hydrocarbon components for instance, hydrogen sulfide, nitrogen and water vapor. These impurities are undesirable compounds and cause several technical problems for example, corrosion and environment pollution. Therefore, these impurities should be reduce or removed from natural gas stream. Khurmala dome is located in southwest Erbil-Kurdistan region. The Kurdistan region government has paid great attention for this dome to provide the fuel for Kurdistan region. However, the Khurmala associated natural gas is currently flaring at the field. Moreover, nowadays there is a plan to recover and trade this gas and to use it either as feedstock to power station or to sell it in global market. However, the laboratory analysis has showed that the Khurmala sour gas has huge quantities of H2S about (5.3%) and CO2 about (4.4%). Indeed, Khurmala gas sweetening process has been removed in previous study by using Aspen HYSYS. However, Khurmala sweet gas still contents some quintets of water about 23 ppm in sweet gas stream. This amount of water should be removed or reduced. Indeed, water content in natural gas cause several technical problems such as hydrates and corrosion. Therefore, this study aims to simulate the prospective Khurmala gas dehydration process by using Aspen HYSYS V. 7.3 program. Moreover, the simulation process succeeded in reducing the water content to less than 0.1ppm. In addition, the simulation work is also achieved process optimization by using several desiccant types for example, TEG and DEG and it also study the relationship between absorbents type and its circulation rate with HCs losses from glycol regenerator tower.

Keywords: Aspen Hysys, Process simulation, gas dehydration, process optimization.

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236 A New Evolutionary Algorithm for Cluster Analysis

Authors: B.Bahmani Firouzi, T. Niknam, M. Nayeripour

Abstract:

Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.

Keywords: Data clustering, Hybrid evolutionary optimization algorithm, K-means algorithm, Simulated Annealing (SA), Particle Swarm Optimization (PSO).

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235 Generation of 3D Models Obtained with Low-Cost RGB and Thermal Sensors Mounted on Drones

Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Felipe Piña García

Abstract:

Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimize the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain). To this end, a flight with this type of sensors has been planned, developed and analyzed. It has been applied to the archaeological site of Juliobriga (Cantabria, Spain). A strong dependence of the thermal sensor on the GSD, and the capability of this technique to interpret underground materials. This research allows to state that the thermal nature of the site does not provide main information about the site itself, but with combination with other types of information, such as the DEM, the typology of materials, etc., can produce very positive results with respect to the exploration and knowledge of the site. 

Keywords: process optimization, RGB models, thermal models, UAV, workflow

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234 Annual Power Load Forecasting Using Support Vector Regression Machines: A Study on Guangdong Province of China 1985-2008

Authors: Zhiyong Li, Zhigang Chen, Chao Fu, Shipeng Zhang

Abstract:

Load forecasting has always been the essential part of an efficient power system operation and planning. A novel approach based on support vector machines is proposed in this paper for annual power load forecasting. Different kernel functions are selected to construct a combinatorial algorithm. The performance of the new model is evaluated with a real-world dataset, and compared with two neural networks and some traditional forecasting techniques. The results show that the proposed method exhibits superior performance.

Keywords: combinatorial algorithm, data mining, load forecasting, support vector machines

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233 Mining News Sites to Create Special Domain News Collections

Authors: David B. Bracewell, Fuji Ren, Shingo Kuroiwa

Abstract:

We present a method to create special domain collections from news sites. The method only requires a single sample article as a seed. No prior corpus statistics are needed and the method is applicable to multiple languages. We examine various similarity measures and the creation of document collections for English and Japanese. The main contributions are as follows. First, the algorithm can build special domain collections from as little as one sample document. Second, unlike other algorithms it does not require a second “general" corpus to compute statistics. Third, in our testing the algorithm outperformed others in creating collections made up of highly relevant articles.

Keywords: Information Retrieval, News, Special DomainCollections,

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232 Prediction of a Human Facial Image by ANN using Image Data and its Content on Web Pages

Authors: Chutimon Thitipornvanid, Siripun Sanguansintukul

Abstract:

Choosing the right metadata is a critical, as good information (metadata) attached to an image will facilitate its visibility from a pile of other images. The image-s value is enhanced not only by the quality of attached metadata but also by the technique of the search. This study proposes a technique that is simple but efficient to predict a single human image from a website using the basic image data and the embedded metadata of the image-s content appearing on web pages. The result is very encouraging with the prediction accuracy of 95%. This technique may become a great assist to librarians, researchers and many others for automatically and efficiently identifying a set of human images out of a greater set of images.

Keywords: Metadata, Prediction, Multi-layer perceptron, Human facial image, Image mining.

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231 Iterative Clustering Algorithm for Analyzing Temporal Patterns of Gene Expression

Authors: Seo Young Kim, Jae Won Lee, Jong Sung Bae

Abstract:

Microarray experiments are information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. For biologists, a key aim when analyzing microarray data is to group genes based on the temporal patterns of their expression levels. In this paper, we used an iterative clustering method to find temporal patterns of gene expression. We evaluated the performance of this method by applying it to real sporulation data and simulated data. The patterns obtained using the iterative clustering were found to be superior to those obtained using existing clustering algorithms.

Keywords: Clustering, microarray experiment, temporal pattern of gene expression data.

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230 WebGD: A CORBA-based Document Classification and Retrieval System on the Web

Authors: Fuyang Peng, Bo Deng, Chao Qi, Mou Zhan

Abstract:

This paper presents the design and implementation of the WebGD, a CORBA-based document classification and retrieval system on Internet. The WebGD makes use of such techniques as Web, CORBA, Java, NLP, fuzzy technique, knowledge-based processing and database technology. Unified classification and retrieval model, classifying and retrieving with one reasoning engine and flexible working mode configuration are some of its main features. The architecture of WebGD, the unified classification and retrieval model, the components of the WebGD server and the fuzzy inference engine are discussed in this paper in detail.

Keywords: Text Mining, document classification, knowledgeprocessing, fuzzy logic, Web, CORBA

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229 An Overview of Construction and Demolition Waste as Coarse Aggregate in Concrete

Authors: S. R. Shamili, J. Karthikeyan

Abstract:

Fast development of the total populace and far and wide urbanization has surprisingly expanded the advancement of the construction industry. As a result of these activities, old structures are being demolished to make new buildings. Due to these large-scale demolitions, a huge amount of debris is generated all over the world, which results in a landfill. The use of construction and demolition waste as landfill causes groundwater contamination, which is hazardous. Using construction and demolition waste as aggregate can reduce the use of natural aggregates and the problem of mining. The objective of this study is to provide a detailed overview on how the construction and demolition waste material has been used as aggregate in structural concrete. In this study, the preparation, classification, and composition of construction and demolition wastes are also discussed.

Keywords: Aggregate, construction and demolition waste, landfill, large scale demolition.

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228 Eclectic Rule-Extraction from Support Vector Machines

Authors: Nahla Barakat, Joachim Diederich

Abstract:

Support vector machines (SVMs) have shown superior performance compared to other machine learning techniques, especially in classification problems. Yet one limitation of SVMs is the lack of an explanation capability which is crucial in some applications, e.g. in the medical and security domains. In this paper, a novel approach for eclectic rule-extraction from support vector machines is presented. This approach utilizes the knowledge acquired by the SVM and represented in its support vectors as well as the parameters associated with them. The approach includes three stages; training, propositional rule-extraction and rule quality evaluation. Results from four different experiments have demonstrated the value of the approach for extracting comprehensible rules of high accuracy and fidelity.

Keywords: Data mining, hybrid rule-extraction algorithms, medical diagnosis, SVMs

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227 Robotics and Embedded Systems Applied to the Buried Pipeline Inspection

Authors: Robson C. Santos, Julio C. P. Ribeiro, Iorran M. de Castro, Luan C. F. Rodrigues, Sandro R. L. Silva, Diego M. Quesada

Abstract:

The work aims to develop a robot in the form of autonomous vehicle to detect, inspection and mapping of underground pipelines through the ATmega328 Arduino platform. Hardware prototyping is very similar to C / C ++ language that facilitates its use in robotics open source, resembles PLC used in large industrial processes. The robot will traverse the surface independently of direct human action, in order to automate the process of detecting buried pipes, guided by electromagnetic induction. The induction comes from coils that send the signal to the Arduino microcontroller contained in that will make the difference in intensity and the treatment of the information, and then this determines actions to electrical components such as relays and motors, allowing the prototype to move on the surface and getting the necessary information. This change of direction is performed by a stepper motor with a servo motor. The robot was developed by electrical and electronic assemblies that allowed test your application. The assembly is made up of metal detector coils, circuit boards and microprocessor, which interconnected circuits previously developed can determine, process control and mechanical actions for a robot (autonomous car) that will make the detection and mapping of buried pipelines plates. This type of prototype can prevent and identifies possible landslides and they can prevent the buried pipelines suffer an external pressure on the walls with the possibility of oil leakage and thus pollute the environment.

Keywords: Robotic, metal detector, embedded system, pipeline.

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226 Discovery of Sequential Patterns Based On Constraint Patterns

Authors: Shigeaki Sakurai, Youichi Kitahata, Ryohei Orihara

Abstract:

This paper proposes a method that discovers sequential patterns corresponding to user-s interests from sequential data. This method expresses the interests as constraint patterns. The constraint patterns can define relationships among attributes of the items composing the data. The method recursively decomposes the constraint patterns into constraint subpatterns. The method evaluates the constraint subpatterns in order to efficiently discover sequential patterns satisfying the constraint patterns. Also, this paper applies the method to the sequential data composed of stock price indexes and verifies its effectiveness through comparing it with a method without using the constraint patterns.

Keywords: Sequential pattern mining, Constraint pattern, Attribute constraint, Stock price indexes

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225 Issue Reorganization Using the Measure of Relevance

Authors: William Wong Xiu Shun, Yoonjin Hyun, Mingyu Kim, Seongi Choi, Namgyu Kim

Abstract:

The need to extract R&D keywords from issues and use them to retrieve R&D information is increasing rapidly. However, it is difficult to identify related issues or distinguish them. Although the similarity between issues cannot be identified, with an R&D lexicon, issues that always share the same R&D keywords can be determined. In detail, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Furthermore, the relationship among issues that share the same R&D keywords can be shown in a more systematic way by clustering them according to keywords. Thus, sharing R&D results and reusing R&D technology can be facilitated. Indirectly, redundant investment in R&D can be reduced as the relevant R&D information can be shared among corresponding issues and the reusability of related R&D can be improved. Therefore, a methodology to cluster issues from the perspective of common R&D keywords is proposed to satisfy these demands.

Keywords: Clustering, Social Network Analysis, Text Mining, Topic Analysis.

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224 Modeling Language for Constructing Solvers in Machine Learning: Reductionist Perspectives

Authors: Tsuyoshi Okita

Abstract:

For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach in order to make a solver quickly. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem. It is noted that our formal modeling language is not intend for providing an efficient notation for data mining application, but for facilitating a designer who develops solvers in machine learning.

Keywords: Formal language, statistical inference problem, reduction.

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223 Geomorphology of Karst Features of Shiraz City and Arjan Plain and Development Limitations

Authors: Meysam Jamali, Ebrahim Moghimi, Zean Alabden Jafarpour

Abstract:

Karst term is the determiner of a variety of areas or landforms and unique perspectives that have been formed in result of the of the ingredients dissolution of rocks constituter by natural waters. Shiraz area with an area of 5322km2 is located in the simple folded belt in the southern part of Zagros Mountain of Fars, and is surrounded with Limestone Mountains (Asmari formation). Shiraz area is located in Calcareous areas. The infrastructure of this city is lime and absorbing wells that the city can influence the Limestone dissolution and those accelerate its rate and increase the cavitation below the surface. Dasht-e Arjan is a graben, which has been created as the result of activity of two normal faults in its east and west sides. It is a complete sample of Karst plains (Polje) which has been created with the help of tectonic forces (fault) and dissolution process of water in Asmari limestone formation. It is located 60km. off south west of Shiraz (on Kazeroon-Shiraz road). In 1971, UNESCO has recognized this plain as a reserve of biosphere. It is considered as one of the world’s most beautiful geological phenomena, so that most of the world’s geologists are interested in visiting this place. The purpose of this paper is to identify and introduce landscapes of Karst features shiraz city and Dasht-e Arjan including Karst dissolution features (Lapiez, Karst springs, dolines, caves, underground caves, ponors, and Karst valleys), anticlines and synclines, and Arjan Lake.

Keywords: Dasht-eArjan, Fault, Karst features, Shiraz City, Zagros.

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222 Ozone Decomposition over Silver-Loaded Perlite

Authors: Krassimir Genov, Vladimir Georgiev, Todor Batakliev, Dipak K. Sarker

Abstract:

The Bulgarian natural expanded mineral obtained from Bentonite AD perlite (A deposit of "The Broken Mountain" for perlite mining, near by the village of Vodenicharsko, in the municipality of Djebel), was loaded with silver (as ion form - Ag+ 2 and 5 wt% by the incipient wetness impregnation method), and as atomic silver - Ag0 using Tollen-s reagent (silver mirror reaction). Some physicochemical characterization of the samples are provided via: DC arc-AES, XRD, DR-IR and UV-VIS. The aim of this work was to obtain and test the silver-loaded catalyst for ozone decomposition. So the samples loaded with atomic silver show ca. 80% conversion of ozone 20 minutes after the reaction start. Then conversion decreases to ca. 20 % but stay stable during the prolongation of time.

Keywords: aluminum-silicates, Ag/perlite expanded glass, ozone decomposition

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221 Methodology of Restoration Research in Czech Republic

Authors: M. Rehor, V. Ondracek

Abstract:

Restoration research has become important on principle recently in Czech Republic. The reason is simple. More than 70 % of mined brown coal comes from the North Bohemian Basin these days. Open cast brown coal mining has lead to large damage on the landscape. Reclamation of phytotoxic areas is one of the serious problems in the North Bohemian Basin. It mainly concerns the areas with the occurrence of overburden rocks from the coal bed enriched with coal. The presented paper includes the characteristics of the important phytotoxic areas and the methodology of their reclamation. The results are documented with the long term monitoring of physical, mineralogical, chemical and pedological parameters of rocks in the testing areas.

Keywords: Brown coal, dump, methodology, restoration.

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220 Knowledge Discovery from Production Databases for Hierarchical Process Control

Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata

Abstract:

The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system thus the proposed solution has been verified. The paper documents how is possible to apply the new discovery knowledge to use in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.

Keywords: Hierarchical process control, knowledge discovery from databases, neural network.

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