Device Anomaly Detection Algorithm Based on Enhanced Long Short-Term Memory Network

The problems in equipment fault detection include data dimension explosion,computational complexity,low detection accuracy,etc.To solve these problems,a device anomaly detection algorithm based on enhanced long short-term memory(LSTM)is proposed.The algorithm first reduces the dimensionality of the device sensor data by principal component analysis(PCA),extracts the strongly correlated variable data among the multidimensional sensor data with the lowest possible information loss,and then uses the enhanced stacked LSTM to predict the extracted temporal data,thus improving the accuracy of anomaly detection.To improve the efficiency of the anomaly detection,a genetic algorithm(GA)is used to adjust the magnitude of the enhancements made by the LSTM model.The validation of the actual data from the pumps shows that the algorithm has significantly improved the recall rate and the detection speed of device anomaly detection,with the recall rate of 97.07%,which indicates that the algorithm is effective and efficient for device anomaly detection in the actual production environment.

Short-term and imminent geomagnetic anomalies of the Wenchuan M_S8.0 earthquake and exploration on earthquake forecast

The diurnal variation of the geomagnetic vertical component is exhibited mainly by changes of phase and amplitude before strong earthquakes. Based on data recorded by the network of geomagnetic observatories in China for many years, the anomalous features of the appearance time of the minima of diurnal variations （i.e, low-point time） of the geo- magnetic vertical components and the variation of their spatial distribution （i.e, phenomena of low-point displacement） have been studied before the Wenchuan Ms8.0 earthquake. The strong aftershocks after two months＇ quiescence of M6 aftershocks of the Ms8.0 event were forecasted based on these studies. There are good correlativities between these geomagnetic anoma- lies and occurrences of earthquakes. It has been found that most earthquakes occur near the boundary line of sudden changes of the low-point time and generally within four days before or after the 27th or 41st day counting from the day of the appearance of the anomaly. In addition, the imminent anomalies in diurnal-variation amplitudes near the epicentral areas have also been studied before the Wenchuan earthquake.

POSSIBLE CONTRIBUTION OF A TROPICAL CYCLONE TO SHORT-TERM CLIMATE ANOMALIES IN EAST ASIA VIA SNOW COVER ON THE TIBETAN PLATEAU

Snow cover on the Tibetan Plateau(TP) has been shown to be essential for the East Asian summer monsoon.In this paper, we demonstrate that tropical cyclone(TC) 04B(1999) in the northern Indian Ocean, which made landfall during the autumn of 1999, may have contributed to climate anomalies over East Asia during the following spring and summer by increasing snow cover on the TP. Observations indicate that snow cover on the TP increased markedly after TC 04B(1999) made landfall in October of 1999. Sensitivity experiments, in which the TC was removed from a numerical model simulation of the initial field, verified that TC 04B(1999) affected the distribution as well as increased the amount of snow on the TP. In addition, the short-term numerical modeling of the climate over the region showed that the positive snow cover anomaly induced negative surface temperature, negative sensible heat flux, positive latent heat flux, and positive soil temperature anomalies over the central and southern TP during the following spring and summer. These climate anomalies over the TP were associated with positive(negative) summer precipitation anomalies over the Yangtze River valley(along the southeastern coast of China).

COMPARISONS OF CIRCULATION ANOMALIES BETWEEN THE DAILY PRECIPITATION EXTREME AND NON-EXTREME EVENTS IN THE MIDDLE AND LOWER REACHES OF YANGTZE RIVER IN BOREAL SUMMER

Based on the NCEP/NCAR reanalysis dataset and in situ meteorological observations of daily precipitation in boreal summer from 1979 to 2008, the features of circulation anomalies have been investigated using the composite analysis for the extreme events and non-extreme events of regional mean daily rainfall(RMDR) occurring over the midand lower- Yangtze valley(MLYV). The extreme RMDR(ERMDR) events are the events at and above the percentile99 in the rearranged time-series of the RMDR with ascending order of rainfall amount. The non-extreme RMDR events are those at the percentiles 90-85 and 80-75 separately. Our results suggest that the threshold value is 25 mm/day for the ERMDR at percentile 99. Precipitation at all the percentiles is found to occur more frequently in the Meiyu rainfall season in MLYV, and the ERMDR events have occurred with higher frequency since the 1990 s. For the percentiles-associated events, the MLYV is under the control of an anomalous cyclonic circulation in the mid- and lower- troposphere with vastly different anomalous circulation at higher levels. However, at both low and high levels, the ERMDR events-related anomalous circulation is stronger compared to that linked to the non-ERMDR events. The dominant sources of water vapor differ between the ERMDR and non-ERMDR events. During the ERMDR events plentiful water vapor is transported from the Bay of Bengal into the MLYV directly by divergence while there is distinctly increased water vapor from the South China Sea(SCS) in non-RMERMDR episodes. The diabatic heating rates < Q1>, < Q2> and< Q1>- < Q2> have their anomalous patterns and are consistent with each other for these percentiles but their strength decreases markedly with the drop of rainfall intensity. For the precipitation at percentiles 99 and 90-85, the sea surface temperature anomalies(SSTA) in the Pacific distribute positively(negatively) in the south(north), and are stronger when the ERMDR emerges, with little or no SSTA as the events at percentile 80-75 occur. Besides, these results suggest that the genesis of the ERMDR event is directly related to intense local circulation anomalies and the circulation anomalies over the Pacific and SCS in tropical to mid-latitudes, and probably linked with the Pacific SSTA closely while the non-ERMDR events are mainly associated with the anomalous circulation on a local basis. The findings here help understand and predict the happening of ERMDR events over the MLYV.

An Efficient Correlation-Aware Anomaly Detection Framework in Cellular Network

Nowadays,the fifth-generation(5G)mobile communication system has obtained prosperous development and deployment,reshaping our daily lives.However,anomalies of cell outages and congestion in 5G critically influence the quality of experience and significantly increase operational expenditures.Although several big data and artificial intelligencebased anomaly detection methods have been proposed for wireless cellular systems,they change distributions of the data and ignore the relevance among user activities,causing anomaly detection ineffective for some cells.In this paper,we propose a highly effective and accurate anomaly detection framework by utilizing generative adversarial networks(GAN)and long short-term memory(LSTM)neural networks.The framework expands the original dataset while simultaneously keeping the distribution of data unchanged,and explores the relevance among user activities to further improve the system performance.The results demonstrate that our framework can achieve 97.16%accuracy and 2.30%false positive rate by utilizing the correlation of user activities and data expansion.

The Anomaly Field of Subsurface Fluids and Its Formation and Evolution Mechanism Before Three Strong Earthquakes in the Northern North China Area

The data of pre-seismic subsurface fluid anomalies of such earthquakes as Datong-YanggaoM_s6.1 event on Oct.19,1989,western Baotou M_s6.4 event on May 3,1996 and Zhangbei-Shangyi M_s6.2 event on Jan.10,1998 are systematically collected and arranged.Then thefeatures of patterns,spatial distribution,time variation and time-spatial evolution of theseanomalies are compared and comprehensively analyzed.Then the formation and evolutionmechanism of medium-and short-term anomaly field of subsurface fluids in the northernNorth China area is proposed.The results show that the medium-term anomaly field is causedby regional tectonic activities,which further strengthen the local tectonic activities andpromote the formation and evolution of the seismic source body.The enhancement of loealtectonic activities causes the formation of anomaly field of short-term subsurface fluids,andthe evolution of source body engenders the source-precursor anomalies of subsurface fluids inthe epicenters at imminent stage.

Real-time anomaly detection for very short-term load forecasting

Although the recent load information is critical to very short-term load forecasting(VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications.This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF.This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonly used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Finally, a general anomaly detection framework is proposed for the future research.

The Beijing network of digital geomagnetic pulsation observatories

We present herein an introduction to the Beijing network of digital geomagnetic pulsation observatories, and describe its essential features, and important roles in earthquake prediction studies and other geomagnetic investigations. The network provides digitalized data of geomagnetic events, such as magnetic storms, magnetic disturbances, geomagnetic daily variations, and geomagnetic pulsations. The digitalized data, convenient for processing and analysis, contain very rich information because of high accuracy and wide dynamic range of the instruments.

Data-driven unsupervised anomaly detection and recovery of unmanned aerial vehicle flight data based on spatiotemporal correlation

Anomaly detection is crucial to the flight safety and maintenance of unmanned aerial vehicles(UAVs)and has attracted extensive attention from scholars.Knowledge-based approaches rely on prior knowledge,while model-based approaches are challenging for constructing accurate and complex physical models of unmanned aerial systems(UASs).Although data-driven methods do not require extensive prior knowledge and accurate physical UAS models,they often lack parameter selection and are limited by the cost of labeling anomalous data.Furthermore,flight data with random noise pose a significant challenge for anomaly detection.This work proposes a spatiotemporal correlation based on long short-term memory and autoencoder(STCLSTM-AE)neural network data-driven method for unsupervised anomaly detection and recovery of UAV flight data.First,UAV flight data are preprocessed by combining the Savitzky-Golay filter data processing technique to mitigate the effect of noise in the original historical flight data on the model.Correlation-based feature subset selection is subsequently performed to reduce the reliance on expert knowledge.Then,the extracted features are used as the input of the designed LSTM-AE model to achieve the anomaly detection and recovery of UAV flight data in an unsupervised manner.Finally,the method's effectiveness is validated on real UAV flight data.

Atmospheric Meteorological Parameters and Ionospheric F2 Layer Critical Frequency (foF2) Observation for 6^th December, 2016 Indonesia Earthquake (M 6.5): A Case Study

On 6^th December, 2016, an earthquake with M 6.5 occurred at the tectonic plate boundary, southwest of Sumatra, Indonesia (Latitude: 0.5897°S, Longitude: 101.3431°E). In this case, ionospheric critical frequency of F2 layer (foF2) variations and meteorological parameters, viz., air temperature, relative humidity, atmospheric pressure and wind speed variations were investigated so as to detect any anomalies. Data are obtained from different websites freely available for researchers. In the absence of real ionosonde foF2 data, IRI 2016 model data were used. For each parameter, anomaly window were defined when values fell beyond ± 6 ℃,< 70 %,± 4 mb and ± 3.5 km h-1 from the event day value and one third of total foF2 values broke the limits of the upper and lower bounds. Certain random anomalies in temperature, relative humidity, pressure, wind speed and foF2 frequencies were observed different days prior to occurrence of the quake but each parameter showed anomalies 12 days before the occurrence. Also, geomagnetic tranquility was justified through Kp and Dst indices. This study reveals that continuous monitoring of atmospheric meteorological parameters and regular ionospheric foF2 observations might help us to predict an earthquake about a week prior to the occurrence.

A Short Term Review of Operated Cases in the Plastic Surgery Unit at the Komfo Anokye Teaching Hospital, Kumasi, Ghana

Introduction: Surgical problems are of much disturbance to the world and should therefore be given serious attention. The prevalence of these surgical problems, has made plastic surgery become a broadly relevant and acceptable way for addressing problems like injuries, congenital anomalies, surgical infections and malignancies among others. Aim: This study is to quantify and characterize surgical procedures done in the plastic surgery theatre located in the new Accident and Emergency (A & E) Building of KATH. Materials and Methods: Data were obtained from the Operation Register/Theatre Books in the plastic surgery theatre at the A & E Centre on cases operated on from October 1, 2009 to September 30, 2012. Data entry, presentation and analysis were done using Statistical Package for the Social Sciences (SPSS) 20.0 version. Results: Adults formed the majority of patients who sought for plastic surgery with a percentage of 70.3%. The male patients also outnumbered the females recording (61.5%) out of the total number of patients. Most of the cases recorded were acquired cases (93.2%). Reconstructive surgery was the commonest operation performed (30%);in 53.8% cases general anaesthesia was used. Conclusion: Among all the procedures used reconstructive surgery was the commonest surgery performed in the unit and general anaesthesia was the most type of anaesthesia used for the operations.