Intelligent Troubleshooting of Vertical Bandsaws, Leveraging Ensemble Learning on Low-Level Data by Wisal Muhammad, Haseeb Khan, Tariq Kamal, Dahoon Ahn, Ki-Yong Oh

Get full text

Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy by Sun Chao, Hu Runze, Liu Niansong, Ding Jianjun

“…In response to address issues such as difficulties in judging data for classification and recognizing gas components with low accuracy, a KNN-SVM algorithm has been proposed. …”
Get full text

Noncoherent multiple symbol detection of CPFSK based on decision-feedback by Qiang CHEN, Guo-sheng RUI, Wen-jun SUN, Wen-biao TIAN, Yang ZHANG

“…There is a great deal of issues in the traditional symbol detection algorithm such as high computational com-plexity and large engineering implementation difficulty. …”
Get full text

Android malware detection based on APK signature information feedback by Xin-yu LIU, Jian WENG, Yue ZHANG, Bing-wen FENG, Jia-si WENG

“…A new malware detection method based on APK signature of information feedback (SigFeedback) was proposed.Based on SVM classification algorithm,the method of eigenvalue extraction adoped heuristic rule learning to sig APK information verify screening,and it also implemented the heuristic feedback,from which achieved the purpose of more accurate detection of malicious software.SigFeedback detection algorithm enjoyed the advantage of the high detection rate and low false positive rate.Finally the experiment show that the SigFeedback algorithm has high efficiency,making the rate of false positive from 13% down to 3%.…”
Get full text

Android malware detection based on APK signature information feedback by Xin-yu LIU, Jian WENG, Yue ZHANG, Bing-wen FENG, Jia-si WENG

“…A new malware detection method based on APK signature of information feedback (SigFeedback) was proposed.Based on SVM classification algorithm,the method of eigenvalue extraction adoped heuristic rule learning to sig APK information verify screening,and it also implemented the heuristic feedback,from which achieved the purpose of more accurate detection of malicious software.SigFeedback detection algorithm enjoyed the advantage of the high detection rate and low false positive rate.Finally the experiment show that the SigFeedback algorithm has high efficiency,making the rate of false positive from 13% down to 3%.…”
Get full text

Moving Target Detection and Active Tracking with a Multicamera Network by Long Zhao, Li Fei Liu, Qing Yun Wang, Tie Jun Li, Jian Hua Zhou

“…The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. …”
Get full text

Improved Crack Detection and Recognition Based on Convolutional Neural Network by Keqin Chen, Amit Yadav, Asif Khan, Yixin Meng, Kun Zhu

“…There are three obvious limitations existing in the present machine learning methods: low recognition rate, low accuracy, and long time. …”
Get full text

The Line Pressure Detection for Autonomous Vehicles Based on Deep Learning by Xuexi Zhang, Ying Li, Ruidian Zhan, Jiayang Chen, Junxian Li

“…However, these algorithms also have shortcomings such as low detection accuracy or relying on specific scenarios. …”
Get full text

An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…Currently, more and more intrusion detection systems based on machine learning and deep learning are being applied to SDN, but most have drawbacks such as complex models and low detection accuracy. …”
Get full text

BLSTM based night-time wildfire detection from video. by Ahmet K Agirman, Kasim Tasdemir

“…To this end, a BLSTM based night-time wildfire event detection from a video algorithm is proposed. It is shown in the experiments that the proposed algorithm attains 95.15% of accuracy when tested against a wide variety of actual recordings of night-time wildfire incidents and 23.7 ms per frame detection time. …”
Get full text

Simulation of Ground Visibility Based on Atmospheric Boundary Layer Data Using K-Nearest Neighbors and Ensemble Model Algorithms by Ruolan Liu, Shujie Yuan, Duanyang Liu, Lin Han, Fan Zu, Hong Wu, Hongbin Wang

“…This study introduces a machine learning approach for simulating visibility, utilizing the K-Nearest Neighbors algorithm and an ensemble model, which incorporate data from atmospheric boundary layer detection and conventional ground meteorological observations as simulation inputs. …”
Get full text

A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

“…Commonly used detection algorithms have large parameter counts, high requirements on equipment arithmetic, and are not satisfactory for application in low illumination environments in coal mines. …”
Get full text

A novel transformer-based approach for cardiovascular disease detection by Nimra Noor, Muhammad Bilal, Saadullah Farooq Abbasi, Omid Pournik, Theodoros N. Arvanitis

Get full text

PUE Attack Detection in CWSN Using Collaboration and Learning Behavior by Javier Blesa, Elena Romero, Alba Rozas, Alvaro Araujo, Octavio Nieto-Taladriz

“…A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. …”
Get full text

Leather Defect Detection Based on Improved YOLOv8 Model by Zirui Peng, Chen Zhang, Wei Wei

“…Addressing the low accuracy and slow detection speed experienced by algorithms based on deep learning for a leather defect detection task, a lightweight and improved leather defect detection algorithm, dubbed YOLOv8-AGE, has been proposed based on YOLOv8n. …”
Get full text

Coal mine conveyor monitoring video enhancement algorithm based on DP-YOLOv7 by Lei ZHANG

“…By introducing detail processing module (DPM) and low frequency enhancement filter (LEF) into PENet network, the detection effect in low light environment of coal mine is enhanced, and the coal dust and water vapor are denoised by domain adaptive algorithm. …”
Get full text

Research on Spread Spectrum Codes Optimized by Sparrow Search Algorithm and Extreme Gradient Boosting by LIANG Zhiru, BIAN Dongming, ZHANG Gengxin

“…To address the problem of low success rate of spread code identification for low signal-to-noise ratio DSSS signals, this paper combines the Third-order Correlation Function (TCF) of <italic>m</italic>-sequences and its peak characteristics to identify the pseudo-code period of DSSS signals as prior information through power spectrum secondary processing on the premise of denoising preprocessing. …”
Get full text

LDoS attack detection method based on traffic classification prediction by Liang Liu, Yue Yin, Zhijun Wu, Qingbo Pan, Meng Yue

“…Abstract Aiming at the low rate and strong concealment of low‐rate Denial of Service (LDoS) attacks, the calculation of traffic Hurst index is combined with traffic classification, and a machine learning LDoS attack detection method based on search sorting is proposed. …”
Get full text

Online Meta-Recommendation of CUSUM Hyperparameters for Enhanced Drift Detection by Jessica Fernandes Lopes, Sylvio Barbon Junior, Leonimer Flávio de Melo

“…The Cumulative Sum (CUSUM) method, based on calculating the cumulative values within a time series, is commonly used for change detection due to its early detection of small drifts, simplicity, low computational cost, and robustness to noise. …”
Get full text

Detection, Parameter Estimation and Direction Finding of Periodic Pulse Signals by V. B. Manelis, I. S. Faustov, V. A. Kozmin

“…To develop algorithms for detecting, estimating parameters, and direction finding of periodic pulse signals in the presence of low signal-to-noise ratios and the absence of a priori information about the parameters of a periodic pulse signal.Materials and methods. …”
Get full text