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A Blockchain-Based Authentication Protocol for WLAN Mesh Security Access
Get PDFIn order to deploy a secure WLAN mesh network, authentication of both users and APs is needed, and a secure authentication mechanism should be employed. However, some additional configurations of trusted third party agencies are still needed on-site to deploy a secure authentication system. This paper proposes a new block chain-based authentication protocol for WLAN mesh security access, to reduce the deployment costs and resolve the issues of requiring key delivery and central server during IEEE 802.11X authentication. This method takes the user’s authentication request as a transaction, considers all the authentication records in the mesh network as the public ledger and realizes the effective monitoring of the malicious attack. Finally, this paper analyzes the security of the protocol in detail, and proves that the new method can solve the dependence of the authentication node on PKI and CA
Cross-Lingual Non-Ferrous Metals Related News Recognition Method Based on CNN with A Limited Bi-Lingual Dictionary
Get PDFTo acquire non-ferrous metals related news from different countries’ internet, we proposed a cross-lingual non-ferrous metals related news recognition method based on CNN with a limited bilingual dictionary. Firstly, considering the lack of related language resources of non-ferrous metals, we use a limited bilingual dictionary and CCA to learn cross-lingual word vector and to represent news in different languages uniformly. Then, to improve the effect of recognition, we use a variant of the CNN to learn recognition features and construct the recognition model. The experimental results show that our proposed method acquires better results
A Study on Dual-Load-Zone Model of Overlying Strata and Evolution Law of Mining Stress
Get PDFThe changeable structure and movement law of overlying strata are the main contributor to the change of mining stress. Starting from the relevant theory of key stratum and particularly based on the theory of mine ground pressure and strata control, this research proposed a new solution to mining stress problems by establishing a dual-load-zone stratum structural model. Elastic foundation beam theory was used to solve the stress of overlying strata of the dual-load-zones with superposition method, which revised the traditional calculation method of mining stress. The abnormal increase of lead abutment pressure in the mining area was explained effectively, through which the evolution law of mining stress in the case of hard rock was obtained. The results indicate that mining stress experiences a drastic change within the range of 50 m ahead of the coal wall due to the collapse of main roof; under the influence of main key stratum and inferior key strata, the influence range of lead abutment pressure is extended up to approximately 120 m in the working face; this remarkable increase can be attributed to the excessive length of sagging zone. Results from both the dual-load-zone model experiment and field measurement demonstrate high consistency. The model can predict the influence range of abutment pressure effectively and thus guide the safety production of mining
An Energy-Efficient Protocol Using an Objective Function & Random Search with Jumps for WSN
Get PDFWireless Sensor Networks (WSNs) have hardware and software limitations and are deployed in hostile environments. The problem of energy consumption in WSNs has become a very important axis of research. To obtain good performance in terms of the network lifetime, several routing protocols have been proposed in the literature. Hierarchical routing is considered to be the most favorable approach in terms of energy efficiency. It is based on the concept parent-child hierarchy where the child nodes forward their messages to their parent, and then the parent node forwards them, directly or via other parent nodes, to the base station (sink). In this paper, we present a new Energy-Efficient clustering protocol for WSNs using an Objective Function and Random Search with Jumps (EEOFRSJ) in order to reduce sensor energy consumption. First, the objective function is used to find an optimal cluster formation taking into account the ratio of the mean Euclidean distance of the nodes to their associated cluster heads (CH) and their residual energy. Then, we find the best path to transmit data from the CHs nodes to the base station (BS) using a random search with jumps. We simulated our proposed approach compared with the Energy-Efficient in WSNs using Fuzzy C-Means clustering (EEFCM) protocol using Matlab Simulink. Simulation results have shown that our proposed protocol excels regarding energy consumption, resulting in network lifetime extension
Dynamic Trust Model Based on Service Recommendation in Big Data
Get PDFIn big data of business service or transaction, it is impossible to provide entire information to both of services from cyber system, so some service providers made use of maliciously services to get more interests. Trust management is an effective solution to deal with these malicious actions. This paper gave a trust computing model based on service-recommendation in big data. This model takes into account difference of recommendation trust between familiar node and stranger node. Thus, to ensure accuracy of recommending trust computing, paper proposed a fine-granularity similarity computing method based on the similarity of service concept domain ontology. This model is more accurate in computing trust value of cyber service nodes and prevents better cheating and attacking of malicious service nodes. Experiment results illustrated our model is effective
Research on the Law of Garlic Price Based on Big Data
Get PDFIn view of the frequent fluctuation of garlic price under the market economy and the current situation of garlic price, the fluctuation of garlic price in the circulation link of garlic industry chain is analyzed, and the application mode of multidisciplinary in the agricultural industry is discussed. On the basis of the big data platform of garlic industry chain, this paper constructs a Garch model to analyze the fluctuation law of garlic price in the circulation link and provides the garlic industry service from the angle of price fluctuation combined with the economic analysis. The research shows that the average price rate of the price of garlic shows “agglomeration” and cyclical phenomenon, which has the characteristics of fragility, left and a non-normal distribution and the fitting value of the GARCH model is very close to the true value. Finally, it looks into the industrial service form from the perspective of garlic price fluctuation
An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks
Get PDFRecently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of “hot spots” among sensors to enhance the lifetime of networks. The clustering process takes sensors’ location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself. Related experimental results display that the presented method can avoid long distance communicate between sensor nodes. Furthermore, this algorithm reduces energy consumption effectively and improves package delivery rate
RETRACTED: Implementation System of Human Eye Tracking Algorithm Based on FPGA
No full textWith the high-speed development of transportation industry, highway traffic safety has become a considerable problem. Meanwhile, with the development of embedded system and hardware chip, in recent years, human eye detection eye tracking and positioning technology have been more and more widely used in man-machine interaction, security access control and visual detection.In this paper, the high parallelism of FPGA was utilized to realize an elliptical approximate real-time human eye tracking system, which was achieved by the series register structure and random sample consensus (RANSAC), thus improving the speed of image processing without using external memory. Because eye images acquired by the camera often generate a lot of noises due to uneven light and dark background, the preprocessing technologies such as color conversion, image filtering, histogram modification and image sharpening were adopted. In terms of feature extraction of images, the eye tracking algorithm in this paper adopted seven-section rectangular eye tracking characteristic method, which increased a section between the mouth and the nose on the basis of the traditional six-section method, so its recognition accuracy is much higher. It is convenient for the realization of hardware parallel system in FPGA. Finally, aiming at the accuracy and real-time performance of the design system, a more comprehensive simulation test was carried out.The human eye tracking system was verified on DE2-115 multimedia development platform, and the performance of VGA (resolution: 640×480) images of 8-bit grayscale was tested. The results showed that the detection speed of this system was about 47 frames per second under the condition that the detection rate of human face (front face, no inclination) was 93%, which reached the real-time detection level. Additionally, the accuracy of eye tracking based on FPGA system was more than 95%, and it has achieved ideal results in real-time performance and robustness
An Improved Integration for Trimmed Geometries in Isogeometric Analysis
Get PDFTrimming techniques are efficient ways to generate complex geometries in Computer-Aided Design (CAD). In this paper, an improved integration for trimmed geometries in isogeometric analysis (IGA) is proposed. The proposed method can improve the accuracy of the approximation and the condition number of the stiffness matrix. In addition, comparing to the traditional approaches, the trimming techniques can reduce the number of the integration elements with much fewer integration points, which improves the computational efficiency significantly. Several examples are illustrated to show the effectiveness of the proposed approach
Key Process Protection of High Dimensional Process Data in Complex Production
Get PDFIn order to solve the problem of locating and protecting key processes and detecting outliers efficiently in complex industrial processes. An anomaly detection system which is based on the two-layer model fusion frame is designed in this paper. The key process is located by using the random forest model firstly, then the process data feature selection, dimension reduction and noise reduction are processed. Finally, the validity of the model is verified by simulation experiments. It is shown that this method can effectively reduce the prediction accuracy variance and improve the generalization ability of the traditional anomaly detection model from the experimental results