A Group-Based Binary Splitting Algorithm for UHF RFID Anti-Collision Systems

Su, Jian; Sheng, Zhengguo; Liu, Alex X.; Yu, Han; Chen, Yongrui

doi:10.1109/tcomm.2019.2952126

Cited by 85 publications

(52 citation statements)

References 45 publications

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“…To evaluate our method on the dataset, we use the confusion matrix (CM) to evaluate the Accuracy, Recall, Precision, and F-measure. Equations (4) to (7), where TP represents the number of true positives, TN represents the number of true negatives, FP represents the number of false positives, and FN represents the number of false negatives [25], [26], [27]. Accuracy: the proportion of correctly classified instance; Recall: the proportion of elements correctly classified as positive out of all positive elements; Precision: the proportion of elements correctly classified as true alarms out of all the elements the detection model classified as positive; F-measure: the average of the sum of the detection rate and the recall rate; Detection time: the time taken for the test sample to complete the test.…”

Section: A Experimental Settingsmentioning

confidence: 99%

SLGBM: An Intrusion Detection Mechanism for Wireless Sensor Networks in Smart Environments

Jiang

Zhao

2020

IEEE Access

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Wireless sensor network (WSN), which serves as one of the key components of the cyber physical system, is a wireless network composed of many stationary or moving sensors in a self-organizing and multi-hop manner. It cooperatively senses, collects, processes and transmits the information of the perceived objects in the geographical area covered by the network, and finally sends this information to the owner of the network. There are some typical attacks in WSN, such as Blackhole, Grayhole, Flooding and Scheduling attacks, which may cause damages to the WSN system in a short time. Moreover, intrusion detection methods for WSN suffer from the disadvantages of low detection rate, large calculation overhead, and high false alarm rate due to the limited resources of sensor nodes and a large amount of redundancy as well as high correlation of network data. In view of the above problems, we propose SLGBM, an intrusion detection method for wireless sensor networks. First, the sequence backward selection (SBS) algorithm is applied to reduce the data dimension on the feature space of the original traffic data so as to reduce the computational overhead. A LightGBM algorithm is then utilized to detect different network attacks. The experimental results based on the WSN-DS dataset show that F-measure of our proposed SLGBM are obviously superior to current typical detection methods, which are 99.8%, 99.4%, 99.1%, 96.5%, and 96.1% in Normal, Blackhole, Grayhole, Flooding, and Scheduling (TDMA) attack detections respectively.

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Section: A Experimental Settingsmentioning

confidence: 99%

SLGBM: An Intrusion Detection Mechanism for Wireless Sensor Networks in Smart Environments

Jiang

Zhao

2020

IEEE Access

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“…Since the 1980s, scholars have studied the job scheduling problem of parallel batch machines extensively [1]. In this section, we review the results of research dealing with different job sizes and minimization of the maximum completion time [14][15][16][17][18][19][20].…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem

Zhang

Song

et al. 2020

Applied Sciences

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With the rapid economic development, manufacturing enterprises are increasingly using an efficient workshop production scheduling system in an attempt to enhance their competitive position. The classical workshop production scheduling problem is far from the actual production situation, so it is difficult to apply it to production practice. In recent years, the research on machine scheduling has become a hot topic in the fields of manufacturing systems. This paper considers the batch processing machine (BPM) scheduling problem for scheduling independent jobs with arbitrary sizes. A novel fast parallel batch scheduling algorithm is put forward to minimize the makespan in this paper. Each of the machines with different capacities can only handle jobs with sizes less than the capacity of the machine. Multiple jobs can be processed as a batch simultaneously on one machine only if their total size does not exceed the machine capacity. The processing time of a batch is determined by the longest of all the jobs processed in the batch. A novel and fast 4.5-approximation algorithm is developed for the above scheduling problem. For the special case of all the jobs having the same processing times, a simple and fast 2-approximation algorithm is achieved. The experimental results show that fast algorithms further improve the competitive ratio. Compared to the optimal solutions generated by CPLEX, fast algorithms are capable of generating a feasible solution within a very short time. Fast algorithms have less computational costs.

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“…As an important branch, hand gesture recognition [2] is of great significance for promoting the development of HCI. Meanwhile, the development of hand gesture recognition also promotes the progress of many fields, such as smart home [3], industrial internet of things [4][5][6], sign language interaction [7], radio frequency identification [8,9], etc. As a result, hand gesture recognition has become a research hotspot recently [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A Novel Detection and Recognition Method for Continuous Hand Gesture Using FMCW Radar

et al. 2020

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In this paper, a novel method for continuous hand gesture detection and recognition is proposed based on a frequency modulated continuous wave (FMCW) radar. Firstly, we adopt the 2-Dimensional Fast Fourier Transform (2D-FFT) to estimate the range and Doppler parameters of the hand gesture raw data, and construct the range-time map (RTM) and Doppler-time map (DTM). Meanwhile, we apply the Multiple Signal Classification (MUSIC) algorithm to calculate the angle and construct the angletime map (ATM). Secondly, a hand gesture detection method is proposed to segment the continuous hand gestures using a decision threshold. Thirdly, the central time-frequency trajectory of each hand gesture spectrogram is clustered using the k-means algorithm, and then the Fusion Dynamic Time Warping (FDTW) algorithm is presented to recognize the hand gestures. Finally, experiments show that the accuracy of the proposed hand gesture detection method can reach 96.17%. The hand gesture average recognition accuracy of the proposed FDTW algorithm is 95.83%, while its time complexity is reduced by more than 50%. INDEX TERMS FMCW radar, continuous hand gesture recognition, detection, time-frequency trajectory, FDTW.

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A Group-Based Binary Splitting Algorithm for UHF RFID Anti-Collision Systems

Abstract: Yongrui (2019) A group-based binary splitting algorithm For UHF RFID anti-collision systems. IEEE Transactions on Communications. p. 1.

Cited by 85 publications

References 45 publications

SLGBM: An Intrusion Detection Mechanism for Wireless Sensor Networks in Smart Environments

SLGBM: An Intrusion Detection Mechanism for Wireless Sensor Networks in Smart Environments

A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem

A Novel Detection and Recognition Method for Continuous Hand Gesture Using FMCW Radar

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