Complex networks can often be divided in dense sub-networks called communities. Using a partition edit distance, we study how three community detection algorithms transform their outputs if the input network is slight...
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Complex networks can often be divided in dense sub-networks called communities. Using a partition edit distance, we study how three community detection algorithms transform their outputs if the input network is slightly modified. The instabilities appear to be important and we propose a modification of one algorithm to stabilize it and to allow the tracking of the communities in an evolving network. This modification has one parameter which is a tradeoff between stability and quality. The resulting algorithm appears to be very effective. We finally use it on an evolving network of blogs.
In the conclusion of the paper “Low-Complexity SIC detection algorithms for Multiple-Input Multiple-Output Systems” published in 2015, it is claimed that the proposed optimal-ordered successive interference cancella...
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ISBN:
(纸本)9781728119496
In the conclusion of the paper “Low-Complexity SIC detection algorithms for Multiple-Input Multiple-Output Systems” published in 2015, it is claimed that the proposed optimal-ordered successive interference cancellation (OSIC) detector mainly uses “fast Givens rotations” and a new method for updating the squared norms of the rows in the inverse Cholesky factor of the error covariance matrix, to achieve the lowest average complexity among the existing OSIC detectors, including a previous one published in 2011 that also utilizes the inverse Cholesky factor and Givens rotations. This paper shows that “fast Givens rotations” proposed by the above-mentioned paper in 2015 and the Givens rotations utilized in the previous detector are similar and then they should both require the same complexity. We also show that the detector proposed in 2015 and the previous detector both take the dominant complexity to compute the initial inverse Cholesky factor and triangularize the permuted inverse Cholesky factor by Givens rotations, and then the dominant complexity is not affected by the method to update the squared norms of the rows in the inverse Cholesky factor. Finally, it is concluded that both the detectors require the same dominant complexity, including the same average complexity when both of them permute the channel matrix in the same way. On the other hand, we revise the incorrect complexities quoted or claimed in the above-mentioned paper published in 2015, to show that the worst-case complexity of the OSIC detector proposed in 2015 is equal to that of the previous OSIC detector.
8 times 8 transform has been introduced in H.264psilas high profile to improve the video quality. After transform and quantization, if all the coefficients of the blockpsilas residue data become zero, this block is ca...
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8 times 8 transform has been introduced in H.264psilas high profile to improve the video quality. After transform and quantization, if all the coefficients of the blockpsilas residue data become zero, this block is called all-zero block (AZB). Many 4 times 4 transform AZB early detection algorithms have been proposed to skip transform and quantization process. In this paper, after theoretical analysis performed for the sufficient condition of 8 times 8 AZB detection, sum of absolute differences(SAD) and sum of absolute transformed(SATD) based 8 times 8 AZB detection algorithms are proposed. Experimental results show that the proposed algorithms achieve major improvement of computation reduction from 0.95% to 79.48% for 720p sequences. The computation reduction increases as QP increases.
To reduce the influence of imperfect correlation characteristic between the spread sequences and noise in the channel on the performance of detection algorithms, two improved algorithms used to detect parallel combina...
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To reduce the influence of imperfect correlation characteristic between the spread sequences and noise in the channel on the performance of detection algorithms, two improved algorithms used to detect parallel combinatory spread spectrum (PCSS) signal are proposed. The improved detection algorithms based on cyclic correlation apply the cyclic correlation characteristic of PCSS signals to suppress inner-interference and noise as well as jamming in the channel. And the other ones based on multi-user detection (MUD) use the configuration characteristic of PCSS signal to improve the performance of the detection. The mathematics models of improved detection algorithms are provided and the performances are analyzed. Theoretic analysis and experimental results indicate that the improved algorithms based on cyclic correlation have the better performance to suppress noise and jamming in the channel and the improved algorithms based on MUD have the better performance to suppress inner-interference as the result of imperfect correlation characteristic between the spread sequences. At the same time, the complexities of the algorithms are increased that limit their applied occasion except for abrupt communication systems.
With the wide application of civil aircraft on-board navigation system, the demand for its safety and stability is increasing. In this paper, the aircraft navigation state data is acquired by GNSS and INS sensors, and...
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ISBN:
(数字)9798350378917
ISBN:
(纸本)9798350378924
With the wide application of civil aircraft on-board navigation system, the demand for its safety and stability is increasing. In this paper, the aircraft navigation state data is acquired by GNSS and INS sensors, and the navigation state model is constructed. Through Kalman filtering algorithm, any abnormal or inconsistent navigation state is detected to monitor the real-time performance of the navigation system. When potential deceptive interference is detected, the algorithm is able to take appropriate decisions autonomously, such as switching to an alternate navigation system, sending warning notifications to the flight crew, and so on. In the simulated spoofed interference scenario, the algorithm successfully detected more than 95% of the interference events with an average response time of less than 5 seconds. When the on-board GNSS spoofing causes a position deviation of 250 m or more, the designed algorithm is able to realize a more accurate acquisition of the spoofing duration. The reliability and effectiveness of the proposed algorithm in spoofed jamming scenarios are verified, and the anti-jamming capability of the civil aircraft airborne navigation system is improved.
Aims: Our aim is to improve the accuracy of existing heart beat detection algorithms in order to provide reliable heart beat locations in a multi-modal beat detection scheme. Methods: A rhythm-based algorithm is prese...
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Aims: Our aim is to improve the accuracy of existing heart beat detection algorithms in order to provide reliable heart beat locations in a multi-modal beat detection scheme. Methods: A rhythm-based algorithm is presented which on top of a base beat detection method processes the detected beats by rejecting annotations and filling in gaps while minimizing a deviation score. A novel beat detection method based on rational modelling of ECG signals is also presented as a base algorithm. Results: The rhythm-correction algorithm applied to Sachin Vernekar's phase 11 entry was submitted to the third phase of the PhysioNet/CinC Challenge 2014 contest. The algorithm has 99.98% gross and average sensitivity and 99.96% gross and average positive predictivity compared to 99.92% and 99.94%, respectively, of the base algorithm. Due to run-time performance problems, the rational algorithm was not able to qualifY in the contest. Conclusions: The rhythm-based method improves the results of the base algorithm on the training data set. The hidden records are not yet available at the time of writing of this paper; therefore we are not able to report the final performance of the algorithm. Run-time improvement of the rational algorithm remains future work.
Abstract-In Video tracking, detection and tracking usually need two algorithms. The process is complex and need much time which detection and tracking are. In this paper a hybrid valued sequential state vector is ...
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ISBN:
(纸本)9781424479573
Abstract-In Video tracking, detection and tracking usually need two algorithms. The process is complex and need much time which detection and tracking are. In this paper a hybrid valued sequential state vector is formulated. The state vector is characterized by information of target appearance flag and of location. Particle filter-based method implements detection and tracking at one time. In order to reduce process time and think of pixel position in tracking field, feature histogram of luminance is as observe vector and used posterior estimate. In this paper, the luminance component is derived and target is recognized and tracked through image processor based on DSP in order to implementing real-time. The experimental results confirm that method can detect and track the object in real-time successfully when the number of particles is 160. The method is robust for rolling, scale and partial occlusion.
The paper presents a state-of-the-art analysis of modern drowsiness detection algorithms based on computer vision technologies as well as considers the problem of yawning detection for the vehicle driver. Based on the...
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The paper presents a state-of-the-art analysis of modern drowsiness detection algorithms based on computer vision technologies as well as considers the problem of yawning detection for the vehicle driver. Based on the analysis of the literature we classify drowsiness detection techniques into three groups: the driving pattern of the vehicle; psychophysiological characteristics of drivers; and computer vision techniques for driver monitoring. The computer vision methods look most promising since they are non-intrusive for the driver. The importance of the driver drowsiness monitoring system rises from the number of drowsiness-related accidents. Yawning is an important identifier of drowsiness, even though it is not the most reliable drowsiness indicator. Some of the methods that are based on computer vision are presented and discussed in the paper. We developed and evaluated a yawning detection model. We analyzed available datasets for yawning detection and conclude that the existing datasets have to be enhanced by pictures taken in real driving conditions. We propose yawning detection dataset-preparation as well as detection model development and evaluation.
In neutral atom quantum computers, readout and preparation of the atomic qubits are usually based on fluorescence imaging and subsequent analysis of the acquired image. For each atom site, the brightness or some compa...
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ISBN:
(数字)9798331541378
ISBN:
(纸本)9798331541385
In neutral atom quantum computers, readout and preparation of the atomic qubits are usually based on fluorescence imaging and subsequent analysis of the acquired image. For each atom site, the brightness or some comparable metric is estimated and used to predict the presence or absence of an atom. Across different setups, we can see a vast number of different approaches used to analyze these images. Often, the choice of detection algorithm is either not mentioned at all or it is not justified. We investigate several different algorithms and compare their performance in terms of both precision and execution run time. To do so, we rely on a set of synthetic images across different simulated exposure times with known occupancy states, which we generated using a previously validated imaging simulation. Since the use of simulation provides us with the ground truth of atom site occupancy, we can easily state precise error rates and variances of the reconstructed property. However, knowing the relative performance of these algorithms is not sufficient to justify their use, since better ones can exist that were not compared. To investigate this possibility, we calculated the Cramer-Rao bound in order to establish an upper limit that even a perfect estimator cannot outperform. As the metric of choice, we used the number of photonelectrons that can be contributed to a specific atom site. Every estimator that reconstructs a different property can simply be scaled accordingly. Since the bound depends on the occupancy of neighboring sites, we provide the best and worst cases, as well as a half filled one, which should represent an averaged bound best. Our comparison shows that of our tested algorithms, a global nonlinear least-squares solver that uses the optical system's point spread function (PSF) to return a global bias and each sites' number of photoelectrons performed the best, on average crossing the worst-case bound for longer exposure times. Its main drawback is its huge
Road detection is a relevant task within vision-based systems devoted to assist the driver. Although they have been improved during the last decade, these algorithms are usually validated using qualitative results. No...
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Road detection is a relevant task within vision-based systems devoted to assist the driver. Although they have been improved during the last decade, these algorithms are usually validated using qualitative results. Nonetheless, quantitative evaluation is necessary either to enable the comparison between different algorithms or to achieve the optimal performance of a given one. In this paper we present a composite index to quantitatively assess the performance of road detection algorithms. The measure is based on a weighted combination of different evaluations which use a trade-off between precision and recall scores. Obtaining a single index score is a major benefit. It can be used to easily compare algorithms or to properly set their parameters. Moreover, innovatively our proposal includes a human perception criterion to improve its usefulness. Experiments on real-world data corroborate the usefulness of the proposed index.
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