Yirong Jiang¹, Weijin Jiang^2,3,4,*, Jiahui Chen^2,*, Yang Wang², Yuhui Xu², Lina Tan², Liang Guo⁵

Journal on Internet of Things, Vol.1, No.2, pp. 41-53, 2019, DOI:10.32604/jiot.2019.07231

Abstract The symbolic network adds the emotional information of the relationship, that is, the “+” and “-” information of the edge, which greatly enhances the modeling ability and has wide application in many fields. Weak unbalance is an important indicator to measure the network tension. This paper starts from the weak structural equilibrium theorem, and integrates the work of predecessors, and proposes the weak unbalanced algorithm EAWSB based on evolutionary algorithm. Experiments on the large symbolic networks Epinions, Slashdot and WikiElections show the effectiveness and efficiency of the proposed method. In EAWSB, this paper proposes a compression-based indirect representation method, which… More >

Qirun Wang^1,2, Fujian Zhu^3,4, Yan Leng^3,4, Yongjun Ren^3,4,*, Jinyue Xia⁵

Journal on Internet of Things, Vol.1, No.1, pp. 33-39, 2019, DOI:10.32604/jiot.2019.05898

Abstract With the rapid development of E-commerce and E-government, there are so many electronic records have been produced. The increasing number of electronic records brings about storage difficulties, the traditional electronic records center is difficult to cope with the current fast growth requirements of electronic records storage and management. Therefore, it is imperative to use cloud storage technology to build electronic record centers. However, electronic records also have weaknesses in the cloud storage environment, and one of them is that once electronic record owners or managers lose physical control of them, the electronic records are more likely to be tampered with… More >

Haoran Zhu¹, Demin Gao^1,2,*, Shuo Zhang¹

Journal on Internet of Things, Vol.1, No.1, pp. 25-31, 2019, DOI:10.32604/jiot.2019.05897

Abstract Forest fire prediction constitutes a significant component of forest management. Timely and accurate forest fire prediction will greatly reduce property and natural losses. A quick method to estimate forest fire hazard levels through known climatic conditions could make an effective improvement in forest fire prediction. This paper presents a description and analysis of a forest fire prediction methods based on machine learning, which adopts WSN (Wireless Sensor Networks) technology and perceptron algorithms to provide a reliable and rapid detection of potential forest fire. Weather data are gathered by sensors, and then forwarded to the server, where a fire hazard index… More >

Yue Zhao¹, Jianjian Yue¹, Wei Song^1,*, Xiaona Xu¹, Xiali Li¹, Licheng Wu¹, Qiang Ji²

Journal on Internet of Things, Vol.1, No.1, pp. 17-23, 2019, DOI:10.32604/jiot.2019.05866

Abstract We proposed a method using latent regression Bayesian network (LRBN) to extract the shared speech feature for the input of end-to-end speech recognition model. The structure of LRBN is compact and its parameter learning is fast. Compared with Convolutional Neural Network, it has a simpler and understood structure and less parameters to learn. Experimental results show that the advantage of hybrid LRBN/Bidirectional Long Short-Term Memory-Connectionist Temporal Classification architecture for Tibetan multi-dialect speech recognition, and demonstrate the LRBN is helpful to differentiate among multiple language speech sets. More >

Yong Xie¹, Zui Tao^2,*, Wen Shao³, John J. Qu⁴, Hai Huan³, Chuanyang Tian³

Journal on Internet of Things, Vol.1, No.1, pp. 9-16, 2019, DOI:10.32604/jiot.2019.05859

Abstract Radiation cross-calibration is an effective method to check and verify the accuracy and stability of sensor measurements. Satellites with high radiation accuracy are used to calibrate satellites with low radiation accuracy. In order to ensure the reliability of the radiation cross-calibration method, we propose to obtain the gain and offset of the GaoFen-1 satellite by linear regression after the radiation cross-calibration of the satellite with low precision and compare with the official coefficient. Finally, we get the relationship between the error in radiation cross-calibration results and side swing angle. The linear correction coefficients of each band are: 0.618, 0.625, 0.512… More >

Qian Dang¹, Huafeng Zhang¹, Bo Zhao², Yanwen He², Shiming He^3,*, Hye-Jin Kim⁴

Journal on Internet of Things, Vol.1, No.1, pp. 1-7, 2019, DOI:10.32604/jiot.2019.05804

Abstract As the development of smart grid and energy internet, this leads to a significant increase in the amount of data transmitted in real time. Due to the mismatch with communication networks that were not designed to carry high-speed and real time data, data losses and data quality degradation may happen constantly. For this problem, according to the strong spatial and temporal correlation of electricity data which is generated by human’s actions and feelings, we build a low-rank electricity data matrix where the row is time and the column is user. Inspired by matrix decomposition, we divide the low-rank electricity data… More >