• Geomechanics and Engineering
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• v.33 no.2
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• pp.183-194
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• 2023

This study presents the prediction of the California bearing ratio (CBR) of coarse- and fine-grained soils using artificial intelligence technology. The group method of data handling (GMDH) algorithm, an artificial neural network-based model, was used in the prediction of the CBR values. In the design of the prediction models, various combinations of independent input variables for both coarse- and fine-grained soils have been used. The results obtained from the designed GMDH-type neural networks (GMDH-type NN) were compared with other regression models, such as linear, support vector, and multilayer perception regression methods. The performance of models was evaluated with a regression coefficient (R²), root-mean-square error (RMSE), and mean absolute error (MAE). The results showed that GMDH-type NN algorithm had higher performance than other regression methods in the prediction of CBR value for coarse- and fine-grained soils. The GMDH model had an R² of 0.938, RMSE of 1.87, and MAE of 1.48 for the input variables {G, S, and MDD} in coarse-grained soils. For fine-grained soils, it had an R² of 0.829, RMSE of 3.02, and MAE of 2.40, when using the input variables {LL, PI, MDD, and OMC}. The performance evaluations revealed that the GMDH-type NN models were effective in predicting CBR values of both coarse- and fine-grained soils.

• Computers and Concrete
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• v.18 no.2
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• pp.279-295
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• 2016

A new innovative composite material is textile reinforced cementitious composite (TRCC). To achieve high flexural performance researchers suggest polymer modification of TRCC matrices. In this study, nine ready mix repair mortars commonly used in construction industry and the production of TRCC elements were examined. Mechanical properties such as compressive and flexural strength, drying shrinkage were studied. Being a significant durability concern, alkali silica reaction tests were performed according to related standards. Results showed that, some ready repair mortar mixes are potentially reactive due to the alkali silica reaction. Two of the ready mortar mixes labelled as non-shrinkage in their technical data sheets showed the highest shrinkage. In this experiment, researchers designed new matrices. These matrices were fine grained concretes modified with polymer additives; latexes and redispersible powders. Two latexes and six redispersible powder polymers were used in the study. Mechanical properties of fine grained concretes such as compressive and flexural strengths were determined. Results showed that some of the fine grained concretes cast with redispersible powders had higher flexural strength than ready mix repair mortars at 28 days. Matrix composition has to be designed for a suitable consistency for planned production processes of TRCC and mechanical properties for load-carrying capacity.

• The Journal of Engineering Geology
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• v.14 no.2
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• pp.147-168
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• 2004

Purpose of this study is to quantitatively characterize the fracture roughness which was measured with a confocal laser scanning microscope. The roughness discrete data measured by confocal laser microscope were analyzed by spectral analysis and fast Fourier transform (FFT).The roughness data by used noise reduction filter were applied for fractal analysis to describe roughness features quantitatively. Artificial fractures created by Brazilian test on granites were used to measure fracture roughness under the confocal laser scanning microscope. Measurements were performed along three scan lines on each fracture surface. 36 scan lines were determined on 12 specimens in total. Features of roughness showed that coarse and medium grained granites tend to more rough features than those of fine grained granites. Continuous analog data of roughness is possible to described as discrete data of measure roughness with a fixed interval under the confocal laser microscope. Results of FFT with the measured data showed the highest values on the second harmonics. Distribution of average amplitude of second harmonics was observed 0.9853 in coarse grained granite, 1.0792 in medium grained granite and 0.6794 in fine grained granite. This indicates that the larger roughness has the higher energy of harmonics as the result of fractal analysis in low frequency zone.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5C
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• pp.323-331
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• 2006

It is a recent worldwide trend that erosion characteristics of soil, the resistance factor against scour, are quantified and considered in the estimation of scour depths in fine-grained soils. As part of the efforts, local erosion characteristics on fine-grained soils of the West Coast area are analyzed through scour rate experiments, where a lot of sea-crossing long-span bridges are planned and being constructed in recent years. Four sites including Incheon Bridge, Choji Bridge, Hwankyung Bridge, and Janghang area are finally selected for this study and the scour rate tests are performed using 34 undisturbed soil samples from the sites. The critical shear stresses which represent erodibility of the soil tend to be proportional to the undrained shear strength values. The relative ability of cohesive fine-grained soils to resist erosion is assumed to be higher than that of noncohesive soils. Quantified local erosion characteristics of fine-grained soils in the West Coast area are presented in forms of charts showing relationships between scour rates and shear stresses, and suggested as basic data for the estimation of scour depths and design of bridge foundations in the West Coast area.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.71-77
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• 2016

There has been unknown polynomial time algorithm for cellular formation problem (CFP) that is one of the NP-hard problem. Therefore metaheuristic method has been applied this problem to obtain approximated solution. This paper shows the existence of polynomial-time heuristic algorithm in CFP. The proposed algorithm performs coarse-grained and fine-grained cell formation process. In coarse-grained cell formation process, the cell can be formed in accordance with machine frequently used that is the number of other products use same machine with special product. As a result, the machine can be assigned to most used cell. In fine-grained process, the product and machine are moved into other cell that has a improved grouping efficiency. For 35 experimental data, this heuristic algorithm performs better grouping efficiency for 12 data than best known of meta-heuristic methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1634-1652
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• 2022

Due to the increasing need for data sharing in the age of big data, how to achieve data access control and implement user permission revocation in the blockchain environment becomes an urgent problem. To solve the above problems, we propose a novel blockchain-based data sharing scheme (BDSS) with fine-grained access control and permission revocation in this paper, which regards the medical environment as the application scenario. In this scheme, we separate the public part and private part of the electronic medical record (EMR). Then, we use symmetric searchable encryption (SSE) technology to encrypt these two parts separately, and use attribute-based encryption (ABE) technology to encrypt symmetric keys which used in SSE technology separately. This guarantees better fine-grained access control and makes patients to share data at ease. In addition, we design a mechanism for EMR permission grant and revocation so that hospital can verify attribute set to determine whether to grant and revoke access permission through blockchain, so it is no longer necessary for ciphertext re-encryption and key update. Finally, security analysis, security proof and performance evaluation demonstrate that the proposed scheme is safe and effective in practical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1553-1571
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• 2018

Currently, many of schemes for smart grid data aggregation are based on a one-level gateway (GW) topology. Since the data aggregation granularity in this topology is too single, the control center (CC) is unable to obtain more fine-grained data aggregation results for better monitoring smart grid. To improve this issue, Shen et al. propose an efficient privacy-preserving cube-data aggregation scheme in which the system model consists of two-level GW. However, a risk exists in their scheme that attacker could forge the signature by using leaked signing keys. In this paper, we propose a secure and fine-grained electricity consumption aggregation scheme for smart grid, which employs the homomorphic encryption to implement privacy-preserving aggregation of users' electricity consumption in the two-level GW smart grid. In our scheme, CC can achieve a flexible electricity regulation by obtaining data aggregation results of various granularities. In addition, our scheme uses the forward-secure signature with backward-secure detection (FSBD) technique to ensure the forward-backward secrecy of the signing keys. Security analysis and experimental results demonstrate that the proposed scheme can achieve forward-backward security of user's electricity consumption signature. Compared with related schemes, our scheme is more secure and efficient.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.107-115
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• 2022

Recently, big data applications need another database different from the Relation database. NoSQL databases are used to save and handle massive amounts of data. NoSQL databases have many advantages over traditional databases like flexibility, efficiently processing data, scalability, and dynamic schemas. Most of the current applications are based on the web, and the size of data is in increasing. NoSQL databases are expected to be used on a more and large scale in the future. However, NoSQL suffers from many security issues, and one of them is access control. Many recent applications need Fine-Grained Access control (FGAC). The integration of the NoSQL databases with FGAC will increase their usability in various fields. It will offer customized data protection levels and enhance security in NoSQL databases. There are different NoSQL database models, and a document-based database is one type of them. In this research, we choose the CouchDB NoSQL document database and develop an access control mechanism that works at a fain-grained level. The proposed mechanism uses role-based access control of CouchDB and restricts read access to work at the document level. The experiment shows that our mechanism effectively works at the document level in CouchDB with good execution time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2550-2572
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• 2023

Epidemiological survey is an important means for the prevention and control of infectious diseases. Due to the particularity of the epidemic survey, 1) epidemiological survey in epidemic prevention and control has a wide range of people involved, a large number of data collected, strong requirements for information disclosure and high timeliness of data processing; 2) the epidemiological survey data need to be disclosed at different institutions and the use of data has different permission requirements. As a result, it easily causes personal privacy disclosure. Therefore, traditional access control technologies are unsuitable for the privacy protection of epidemiological survey data. In view of these situations, we propose a black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data. Firstly, a black box-assisted multi-attribute authority management mechanism without a trusted center is established to avoid authority deception. Meanwhile, the establishment of a master key-free system not only reduces the storage load but also prevents the risk of master key disclosure. Secondly, a sensitivity classification method is proposed according to the confidentiality degree of the institution to which the data belong and the importance of the data properties to set fine-grained access permission. Thirdly, a hierarchical authorization algorithm combined with data sensitivity and hierarchical attribute-based encryption (ABE) technology is proposed to achieve hierarchical access control of epidemiological survey data. Efficiency analysis and experiments show that the scheme meets the security requirements of privacy protection and key management in epidemiological survey.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1343-1356
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• 2013

Cloud computing has emerged as perhaps the hottest development in information technology at present. This new computing technology requires that the users ensure that their infrastructure is safety and that their data and applications are protected. In addition, the customer must ensure that the provider has taken the proper security measures to protect their information. In order to achieve fine-grained and flexible access control for cloud computing, a new construction of hierarchical attribute-based encryption(HABE) with Ciphertext-Policy is proposed in this paper. The proposed scheme inherits flexibility and delegation of hierarchical identity-based cryptography, and achieves scalability due to the hierarchical structure. The new scheme has constant size ciphertexts since it consists of two group elements. In addition, the security of the new construction is achieved in the standard model which avoids the potential defects in the existing works. Under the decision bilinear Diffie-Hellman exponent assumption, the proposed scheme is provable security against Chosen-plaintext Attack(CPA). Furthermore, we also show the proposed scheme can be transferred to a CCA(Chosen-ciphertext Attack) secure scheme.