Cloud disaster tolerance has been widely used as a data security mechanism in which multiple replicas of disaster tolerance data are stored in different backup nodes for reliability. In this paper, we deeply study the optimal data backup strategy that backup nodes set the resources prices and source nodes determine the resources quantities that they want to rent. Firstly, we apply a Stackelberg game framework to simulate the interaction among source nodes and backup nodes whose objective is to gain the maximum payoff of every source node and the maximum total payoff of all the backup nodes by adjusting strategies interactively. And then we propose an algorithm to compute the equilibrium price strategy for backup nodes and equilibrium price strategy for source nodes. Finally, we validate this optimal backup strategy through numerical analysis.
{"title":"Optimal backup strategy in cloud disaster tolerance","authors":"X. Liu, Xiaoqiang Di, Jinqing Li, Hui Qi, Huamin Yang, Ligang Cong","doi":"10.1109/CITS.2016.7546444","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546444","url":null,"abstract":"Cloud disaster tolerance has been widely used as a data security mechanism in which multiple replicas of disaster tolerance data are stored in different backup nodes for reliability. In this paper, we deeply study the optimal data backup strategy that backup nodes set the resources prices and source nodes determine the resources quantities that they want to rent. Firstly, we apply a Stackelberg game framework to simulate the interaction among source nodes and backup nodes whose objective is to gain the maximum payoff of every source node and the maximum total payoff of all the backup nodes by adjusting strategies interactively. And then we propose an algorithm to compute the equilibrium price strategy for backup nodes and equilibrium price strategy for source nodes. Finally, we validate this optimal backup strategy through numerical analysis.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129771872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546422
Zhuo Ma, W. Gao, Shuanyi Du, Bong-Kwon Kang
Frequency-domain equalization (FDE) is prior than time-domain equalization in complexity. FDE is based on the cyclic signal property within a data block. This means that the channel must remain constant during this time interval. But in fast fading environments, the channel is time-variant. In order to deal with this problem, a variety of sub-block based FDE techniques have been proposed, but these kinds of algorithms have very high complexity because a tentative equalization and decoding are necessary before sub-block processed. In many practical applications requiring high real-time attribution, processing speed of algorithms is more important than processing capacity, so we must sacrifice performance of algorithm in exchange for speed at this time. In this paper, a simple FDE algorithm without tentative equalization and decoding is proposed for fast fading channel. The proposed method reduces the complexity of algorithm by preserving partial of the frequency equalization result instead of tentative equalizing and decoding. Numerical simulation results show that this lower complexity of algorithm can also effectively decrease the intersymbol interference(ISI) in fast fading environment.
{"title":"A simple frequency-domain equalizer over doubly-selective channel without feedback","authors":"Zhuo Ma, W. Gao, Shuanyi Du, Bong-Kwon Kang","doi":"10.1109/CITS.2016.7546422","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546422","url":null,"abstract":"Frequency-domain equalization (FDE) is prior than time-domain equalization in complexity. FDE is based on the cyclic signal property within a data block. This means that the channel must remain constant during this time interval. But in fast fading environments, the channel is time-variant. In order to deal with this problem, a variety of sub-block based FDE techniques have been proposed, but these kinds of algorithms have very high complexity because a tentative equalization and decoding are necessary before sub-block processed. In many practical applications requiring high real-time attribution, processing speed of algorithms is more important than processing capacity, so we must sacrifice performance of algorithm in exchange for speed at this time. In this paper, a simple FDE algorithm without tentative equalization and decoding is proposed for fast fading channel. The proposed method reduces the complexity of algorithm by preserving partial of the frequency equalization result instead of tentative equalizing and decoding. Numerical simulation results show that this lower complexity of algorithm can also effectively decrease the intersymbol interference(ISI) in fast fading environment.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131089879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546397
Bo Qu, Xuelong Li, D. Tao, Xiaoqiang Lu
With the rapid development of remote sensing technology, huge quantities of high resolution remote sensing images are available now. Understanding these images in semantic level is of great significance. Hence, a deep multimodal neural network model for semantic understanding of the high resolution remote sensing images is proposed in this paper, which uses both visual and textual information of the high resolution remote sensing images to generate natural sentences describing the given images. In the proposed model, the convolution neural network is utilized to extract the image feature, which is then combined with the text descriptions of the images by RNN or LSTMs. And in the experiments, two new remote sensing image-captions datasets are built at first. Then different kinds of CNNs with RNN or LSTMs are combined to find which is the best combination for caption generation. The experiments results prove that the proposed method achieves good performances in semantic understanding of high resolution remote sensing images.
{"title":"Deep semantic understanding of high resolution remote sensing image","authors":"Bo Qu, Xuelong Li, D. Tao, Xiaoqiang Lu","doi":"10.1109/CITS.2016.7546397","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546397","url":null,"abstract":"With the rapid development of remote sensing technology, huge quantities of high resolution remote sensing images are available now. Understanding these images in semantic level is of great significance. Hence, a deep multimodal neural network model for semantic understanding of the high resolution remote sensing images is proposed in this paper, which uses both visual and textual information of the high resolution remote sensing images to generate natural sentences describing the given images. In the proposed model, the convolution neural network is utilized to extract the image feature, which is then combined with the text descriptions of the images by RNN or LSTMs. And in the experiments, two new remote sensing image-captions datasets are built at first. Then different kinds of CNNs with RNN or LSTMs are combined to find which is the best combination for caption generation. The experiments results prove that the proposed method achieves good performances in semantic understanding of high resolution remote sensing images.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125678439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546402
Saadullah Kalwar, F. Umrani, M. Magarini
Long Term Evolution (LTE) is getting popularity among cellular service providers throughout the World and it is going to dominate cellular systems in coming years. According to 3GPP specifications, LTE adopts Orthogonal Frequency-Division Multiplexing (OFDM) as modulation scheme in the downlink. The problem of systems based on OFDM is that they are prone to Carrier Frequency Offset (CFO). In uplink, LTE uses Single-Carrier Frequency Division Multiple Access (SC-FDMA) instead of OFDM. The main reason of its use is the better peak-to-average power ratio performance in comparison to OFDM, a property required in uplink to increase the duration of the battery of the user device. As OFDM, also SC-FDMA suffers with the problem of CFO. In this paper, a CFO estimation method for LTE uplink is analyzed and simulated by using MATLAB. The proposed method, termed feedback method, uses demodulation reference signals to estimate the CFO. After estimation of CFO, its effect is compensated in time-domain by multiplication with a linear phase.
{"title":"Feedback method for estimation and compensation of carrier frequency offset in LTE uplink","authors":"Saadullah Kalwar, F. Umrani, M. Magarini","doi":"10.1109/CITS.2016.7546402","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546402","url":null,"abstract":"Long Term Evolution (LTE) is getting popularity among cellular service providers throughout the World and it is going to dominate cellular systems in coming years. According to 3GPP specifications, LTE adopts Orthogonal Frequency-Division Multiplexing (OFDM) as modulation scheme in the downlink. The problem of systems based on OFDM is that they are prone to Carrier Frequency Offset (CFO). In uplink, LTE uses Single-Carrier Frequency Division Multiple Access (SC-FDMA) instead of OFDM. The main reason of its use is the better peak-to-average power ratio performance in comparison to OFDM, a property required in uplink to increase the duration of the battery of the user device. As OFDM, also SC-FDMA suffers with the problem of CFO. In this paper, a CFO estimation method for LTE uplink is analyzed and simulated by using MATLAB. The proposed method, termed feedback method, uses demodulation reference signals to estimate the CFO. After estimation of CFO, its effect is compensated in time-domain by multiplication with a linear phase.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127719612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Device-to-Device (D2D) communication has advantages of improving the spectral resource efficiency. But unfortunately, it brings about interference and potential secrecy hazard. In this paper, a Stackelberg game based power control algorithm is provided to enhance the physical layer security underlaying D2D communication by utilizing the interference. Then, a mathematical model based on Stackelberg game is set up, in which we regard the secrecy energy efficiency as the utility function. After that, the existence and uniqueness of the Stackelberg Equilibrium is proved. In addition, a power control algorithm is offered, which can iteratively converge to the Stackelberg Equilibrium. Finally the simulation results show that by applying the provided algorithm, both the cellular user and the D2D pair have the secrecy energy efficiency improved.
{"title":"Improving physical layer security in underlay D2D communication via Stackelberg game based power control","authors":"Wanbing He, Wei Zhang, Wei Bai, Yueming Cai, Xinrong Guan, Junyue Qu","doi":"10.1109/CITS.2016.7546390","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546390","url":null,"abstract":"Device-to-Device (D2D) communication has advantages of improving the spectral resource efficiency. But unfortunately, it brings about interference and potential secrecy hazard. In this paper, a Stackelberg game based power control algorithm is provided to enhance the physical layer security underlaying D2D communication by utilizing the interference. Then, a mathematical model based on Stackelberg game is set up, in which we regard the secrecy energy efficiency as the utility function. After that, the existence and uniqueness of the Stackelberg Equilibrium is proved. In addition, a power control algorithm is offered, which can iteratively converge to the Stackelberg Equilibrium. Finally the simulation results show that by applying the provided algorithm, both the cellular user and the D2D pair have the secrecy energy efficiency improved.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129231735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546456
Xue Yang, Junzhao Du, Sicong Liu, Rui Li, Hui Liu
The atmospheric environment is facing increasing threats from industrial pollutions. This paper presents an air pollution source estimation algorithm using mobile sensor networks. We propose a continuous point source model of pollution under windy conditions. Then we use quadrocopters which equipped with sensors that can detect pollutants to collect concentration information. Based on the collected information, we take advantage of the maximum likelihood estimation method to estimate the diffusion parameters. To improve the accuracy of the estimation of diffusion source position and make the quadrocopter approaching the source, we further propose a scheduling strategy based on the particle swarm optimizer basis. We conduct extensive experiments to show the effectiveness of our proposed approach.
{"title":"Air pollution source estimation profiling via mobile sensor networks","authors":"Xue Yang, Junzhao Du, Sicong Liu, Rui Li, Hui Liu","doi":"10.1109/CITS.2016.7546456","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546456","url":null,"abstract":"The atmospheric environment is facing increasing threats from industrial pollutions. This paper presents an air pollution source estimation algorithm using mobile sensor networks. We propose a continuous point source model of pollution under windy conditions. Then we use quadrocopters which equipped with sensors that can detect pollutants to collect concentration information. Based on the collected information, we take advantage of the maximum likelihood estimation method to estimate the diffusion parameters. To improve the accuracy of the estimation of diffusion source position and make the quadrocopter approaching the source, we further propose a scheduling strategy based on the particle swarm optimizer basis. We conduct extensive experiments to show the effectiveness of our proposed approach.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116792859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546428
Takanori Kudo, Tomotaka Kimura, Yoshiaki Inoue, Hirohisa Aman, K. Hirata
Machine learning techniques have been achieving significant performance improvements in various kinds of tasks, and they are getting applied in many research fields. While we benefit from such techniques in many ways, they can be a serious security threat to the Internet if malicious attackers become able to utilize them to detect software vulnerabilities. This paper introduces a new concept of self-evolving botnets, where computing resources of infected hosts are exploited to discover unknown vulnerabilities in non-infected hosts. We propose a stochastic epidemic model that incorporates such a feature of botnets, and show its behaviors through numerical experiments and simulations.
{"title":"Behavior analysis of self-evolving botnets","authors":"Takanori Kudo, Tomotaka Kimura, Yoshiaki Inoue, Hirohisa Aman, K. Hirata","doi":"10.1109/CITS.2016.7546428","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546428","url":null,"abstract":"Machine learning techniques have been achieving significant performance improvements in various kinds of tasks, and they are getting applied in many research fields. While we benefit from such techniques in many ways, they can be a serious security threat to the Internet if malicious attackers become able to utilize them to detect software vulnerabilities. This paper introduces a new concept of self-evolving botnets, where computing resources of infected hosts are exploited to discover unknown vulnerabilities in non-infected hosts. We propose a stochastic epidemic model that incorporates such a feature of botnets, and show its behaviors through numerical experiments and simulations.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114654536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546433
Ting Peng, Yuebin Chen, Jie Xiao, Yang Zheng, Jiangfeng Yang
In the cognitive radios (CR), there is a security issue-spectrum sensing data falsification attacks (SSDF) in the process of cooperation. Some malicious users (MUs) who unwilling to cooperate friendly with other users may launch SSDF attacks by falsifying their local sensing information sent to fusion center (FC) intentionally, result in interfering with the detection and threat the CR networks. In order to defense against the SSDF attacks, an improved soft fusion-based algorithm is given in this paper, the key idea of the algorithm is that the cooperation is viewed as a service-evaluation process and making use of cognitive users' (CUs) average reputation degrees to reflect the service quality, then allocate properly the CUs' weights in the fusion according to the reputation degrees. Simulation results show that the sensing performance of the improved algorithm is better than the traditional soft-fusion CSS in the presence of SSDF attacks.
{"title":"Improved soft fusion-based cooperative spectrum sensing defense against SSDF attacks","authors":"Ting Peng, Yuebin Chen, Jie Xiao, Yang Zheng, Jiangfeng Yang","doi":"10.1109/CITS.2016.7546433","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546433","url":null,"abstract":"In the cognitive radios (CR), there is a security issue-spectrum sensing data falsification attacks (SSDF) in the process of cooperation. Some malicious users (MUs) who unwilling to cooperate friendly with other users may launch SSDF attacks by falsifying their local sensing information sent to fusion center (FC) intentionally, result in interfering with the detection and threat the CR networks. In order to defense against the SSDF attacks, an improved soft fusion-based algorithm is given in this paper, the key idea of the algorithm is that the cooperation is viewed as a service-evaluation process and making use of cognitive users' (CUs) average reputation degrees to reflect the service quality, then allocate properly the CUs' weights in the fusion according to the reputation degrees. Simulation results show that the sensing performance of the improved algorithm is better than the traditional soft-fusion CSS in the presence of SSDF attacks.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114688338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546423
Gongsheng Yuan, Lizhen Wang, Peizhong Yang, Lan Chen
Mining spatial co-location pattern is one of the most important researches in the field of spatial data mining. In the past researches, many spatial co-location pattern mining algorithms and the expansions about these algorithms have been proposed. However, some of these methods often produce a large number of patterns which are difficult to use. If we want to use the subset of the prevalent co-location pattern set to summarize the whole set and as the increase of the number of patterns in subset, the patterns in subset always are the best summary for the original prevalent set. This is a NP-hard problem. In this paper, we consider the problem of ordering a prevalent co-location pattern set so that each prefix of the ordering gives as good a summary of the set as possible. And according to the features of spatial data, we define an estimation of participation index function and a prevalent co-location pattern loss function to formulate this problem and design a greedy algorithm which gives an approximation quality.
{"title":"Spatial co-location pattern ordering","authors":"Gongsheng Yuan, Lizhen Wang, Peizhong Yang, Lan Chen","doi":"10.1109/CITS.2016.7546423","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546423","url":null,"abstract":"Mining spatial co-location pattern is one of the most important researches in the field of spatial data mining. In the past researches, many spatial co-location pattern mining algorithms and the expansions about these algorithms have been proposed. However, some of these methods often produce a large number of patterns which are difficult to use. If we want to use the subset of the prevalent co-location pattern set to summarize the whole set and as the increase of the number of patterns in subset, the patterns in subset always are the best summary for the original prevalent set. This is a NP-hard problem. In this paper, we consider the problem of ordering a prevalent co-location pattern set so that each prefix of the ordering gives as good a summary of the set as possible. And according to the features of spatial data, we define an estimation of participation index function and a prevalent co-location pattern loss function to formulate this problem and design a greedy algorithm which gives an approximation quality.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128329339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-06DOI: 10.1109/CITS.2016.7546395
Bin Sun, Haiying Li
By general exploration there is one or more geologic abnormal areas within Fumei No. 1 Coalmine Industrial Square and Shaft, which will affect the mine shaft construction and safety production. However, traditional methods for hidden disaster-causing factors will not meet the exploration demands because of their defects. For example, direct current electric method, geological radar and even three-dimensional seismic prospecting can not simultaneously identify geologic abnormal areas of water-bearing condition both underground and in mid-deep zone. Therefore, to explore hidden disaster-causing factors more fully, this paper puts forward a signal acquisition and processing way based on transient electromagnetic method. On the principle of transient electromagnetic method, a system of transient electromagnetic signal acquisition is built and composed of transmitter unit and receiver unit. By triggering start button, the system wirelessly triggers transmitter unit, i.e. one pulse magnetic field to the underground each time. 4ms later, two receiver coils simultaneously collect signals of the secondary pulsed magnetic field caused by underground medium. Finally the signal data are stored in CF card after RC filtering, operational amplifying, sample integral and analog-to-digital conversion. From the signal data processing and analyzing results, there are hidden disaster-causing factors in the exploration zone: one collapse column, one coalmine goaf and one underground watercourse. Compared with the geological data of pilot holes of shaft, these three geologic abnormal places are confirmed, which powerfully helps prove the reliability and efficiency of this method of signal acquisition and processing. These relevant exploration data can not only provide geologic basis for construction of industrial square buildings and structures, but also supply design and construction of shafts with instructions, and furthermore, serve as data reference for exploration of hidden disaster-causing factors in more complicated geological conditions areas.
{"title":"A study on transient electromagnetic signal acquisition and processing for exploring hidden disaster-causing factors in coalmine","authors":"Bin Sun, Haiying Li","doi":"10.1109/CITS.2016.7546395","DOIUrl":"https://doi.org/10.1109/CITS.2016.7546395","url":null,"abstract":"By general exploration there is one or more geologic abnormal areas within Fumei No. 1 Coalmine Industrial Square and Shaft, which will affect the mine shaft construction and safety production. However, traditional methods for hidden disaster-causing factors will not meet the exploration demands because of their defects. For example, direct current electric method, geological radar and even three-dimensional seismic prospecting can not simultaneously identify geologic abnormal areas of water-bearing condition both underground and in mid-deep zone. Therefore, to explore hidden disaster-causing factors more fully, this paper puts forward a signal acquisition and processing way based on transient electromagnetic method. On the principle of transient electromagnetic method, a system of transient electromagnetic signal acquisition is built and composed of transmitter unit and receiver unit. By triggering start button, the system wirelessly triggers transmitter unit, i.e. one pulse magnetic field to the underground each time. 4ms later, two receiver coils simultaneously collect signals of the secondary pulsed magnetic field caused by underground medium. Finally the signal data are stored in CF card after RC filtering, operational amplifying, sample integral and analog-to-digital conversion. From the signal data processing and analyzing results, there are hidden disaster-causing factors in the exploration zone: one collapse column, one coalmine goaf and one underground watercourse. Compared with the geological data of pilot holes of shaft, these three geologic abnormal places are confirmed, which powerfully helps prove the reliability and efficiency of this method of signal acquisition and processing. These relevant exploration data can not only provide geologic basis for construction of industrial square buildings and structures, but also supply design and construction of shafts with instructions, and furthermore, serve as data reference for exploration of hidden disaster-causing factors in more complicated geological conditions areas.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133843362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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