Nowadays, wireless LAN has become the most widely deployed technology in mobile devices for providing Internet access. Operators and service providers remarkably increase the density of wireless access points in order...
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Nowadays, wireless LAN has become the most widely deployed technology in mobile devices for providing Internet access. Operators and service providers remarkably increase the density of wireless access points in order to provide their subscribers with better connectivity and user experience. As a result, WLAN users usually find themselves covered by multiple access points and have to decide which one to associate with. In traditional implementations, most wireless stations would select the access point with the strongest signal, regardless of traffic load on that access point, which might result in heavy congestion and unfair load. In this paper, we propose a novel on-line association algorithm to deal with any sequence of STAs during a long-term time such as one day. the performance of our algorithm is evaluated through simulation and experiments. Simulation results show that our algorithm improves the overall WLAN throughput by up to 37%, compared with the conventional RSSI-based approach. Our algorithm also performs better than SSF (Strongest Signal First) and LAB (Largest Available Bandwidth) in the experiments.
The distribution function of the current multidimensional distribution data association algorithm does not have timeliness, which causes the data to generate interference signals during the distribution process, and c...
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The distribution function of the current multidimensional distribution data association algorithm does not have timeliness, which causes the data to generate interference signals during the distribution process, and correlation trajectory errors. Based on DNAzyme, a multidimensional distribution data association algorithm is proposed. The classification characteristics of mostly distributed data is adopted to extract the characteristic parameters of the data. At the same time, the internal storage structure of different data is strengthened to ensure the safe storage of data and connect the signal between the sensor and the data in time, and as a result, establishes good data communication relationship.
The default mechanism for a wireless station to select which access point (AP) to associate with is based on the strength of the received signal by the station. This leads to stations associating to the closest AP. In...
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ISBN:
(纸本)9781509029914
The default mechanism for a wireless station to select which access point (AP) to associate with is based on the strength of the received signal by the station. This leads to stations associating to the closest AP. In situations where user stations are concentrated around one AP, the default algorithm (DA) results in an unbalanced distribution of station-AP associations. This causes congestion at the AP with many associated stations, which degrades the network throughput. We propose a novel association algorithm called Time-Load algorithm (TLA) that associates stations to an AP based on the time-loading of that AP as well as its signal strength. We evaluate the performance of our TLA in comparison with the DA in different scenarios based on network throughput and packet delivery ratio. The simulation results clearly indicate that the TLA outperforms the DA in all scenarios alleviating highly loaded APs and improving throughput experience.
With the advent of the information age, students in the day-to-day management of information will inevitably encounter some data processing problems. When the amount of data processing is large, it is difficult to mee...
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With the advent of the information age, students in the day-to-day management of information will inevitably encounter some data processing problems. When the amount of data processing is large, it is difficult to meet the needs of calculation if the manual method is adopted, Accordingly, this paper proposes a data mining algorithm based on association and clustering, and uses it in the student information analysis system, which effectively improves the efficiency of data mining. In order to improve the ease of operation of the system, the GUI operation interface is designed by using Matlab software, and the data association analysis of student achievement can be achieved by simple button operation. Finally, the feasibility of the system is verified, and tested the feasibility of data analysis in different confidence conditions, the test results indicate that the clustering analysis using the analysis system of student performance can be achieved successfully. The data were correlated and results, is a kind of efficient student information analysis system.
Aiming at the problems of low governance efficiency and high risk of information leakage in dynamic association analysis of large-scale data security protection in enterprises, this paper studies the privacy protectio...
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Aiming at the problems of low governance efficiency and high risk of information leakage in dynamic association analysis of large-scale data security protection in enterprises, this paper studies the privacy protection and governance strategies by combining the FP-Growth (Frequent Pattern-Growth) association algorithm to improve data security and governance efficiency. First, the sensitive data of enterprises was classified and preprocessed into three types: high sensitivity, medium sensitivity and low sensitivity, and unified format and standardization were performed. Then, the FP-Growth method was used to mine frequent patterns in the data, identify potential security threats and the relationship between sensitive information; finally, the data compression optimization method based on the tree structure was used, combining block partitioning and global indexing to improve memory utilization and algorithm operation efficiency. Experiments show that when processing large data scales, compared with the two advanced association algorithms Apriori and Eclat, FP-Growth’s running time is reduced by 24.8% and 14.5% respectively; memory consumption is reduced by 9.4% and 4.2% respectively. The conclusion shows that the FP-Growth algorithm helps to improve the level of security governance and provide effective support for enterprise digitalization.
In order to study the impact of Online Merge Offline (OMO) hybrid teaching model on college mathematics courses, the article constructs a new hybrid teaching model based on the OMO model and evaluates it using a modif...
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In order to study the impact of Online Merge Offline (OMO) hybrid teaching model on college mathematics courses, the article constructs a new hybrid teaching model based on the OMO model and evaluates it using a modified oriented evaluation model based on an improved multi-party weighting index algorithm (Context Evaluation-Input Evaluation-Process Evaluation-Product Evaluation, CIPP), to evaluate it. The results show that the entropy method is better in the improved CIPP evaluation model, and the correct rate of the entropy method is 93.25 %. The improved correlation algorithm takes less time and is faster, with the average time of the improved correlation algorithm being 100ms and the lowest time of the original correlation algorithm being 300ms. The hybrid teaching mode is more excellent than the traditional teaching mode, and the rate of student achievement in the hybrid teaching mode is 49.9 higher than the rate of student achievement in the traditional teaching mode.
With the development of IEEE 802.11 AMC (Medium Access Control) protocols, efficient utilization of wireless local area networks (WLANs) has become a very important issue. In typical IEEE 802.11 networks, the associat...
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With the development of IEEE 802.11 AMC (Medium Access Control) protocols, efficient utilization of wireless local area networks (WLANs) has become a very important issue. In typical IEEE 802.11 networks, the association between mobile users (MUs) and access point (AP) is based on the signal strength information. As a result, it often results in the extremely unfair bandwidth allocation among MUs. In this paper, we propose a distributed association algorithm to achieve load balancing among the APs. The proposed algorithm gradually balances the AP loads for the available multiple bit rate choices in a distributed manner. We analyze the stability and overhead of the proposed algorithm, and show the improvement of the fairness via computer simulation. Additionally, we have implemented a prototype on a testbed to prove its feasibility(1).
Background Paired-coil TMS can delineate causal connections between cortical areas. Short-interval interhemispheric inhibition (SIHI) is a rapid inhibitory process, in which one primary motor cortex (M1) inhibits the ...
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Background Paired-coil TMS can delineate causal connections between cortical areas. Short-interval interhemispheric inhibition (SIHI) is a rapid inhibitory process, in which one primary motor cortex (M1) inhibits the other through the corpus callosum. Previous work suggests that both SIHI and motor evoked potentials (MEPs) originate in the motor hotspot. However, SIHI and MEPs are mediated by different neuronal populations. Objectives Here we used a recently published TMS-based association-method (Weise et al., 2023, Nat Protoc 18:293–318) to test if the neuronal populations mediating SIHI and MEPs can be spatially discriminated. Method s: We mapped the origin of SIHI and MEPs of hand muscles in each hemisphere, using the novel association-method to perform a ‘source space’ mapping on 18 healthy volunteers. Results The origin of SIHI (the ‘coldspot’) was identifiable in the majority of subjects near the motor hotspot, at the hand-knob and around the central sulcus. It was displaced posterolaterally from the motor hotspot by about 6 mm. Post-hoc analyses revealed that precisely targeting the coldspot elicited significantly stronger SIHI compared to targeting the motor hotspot. Conclusions Findings demonstrate that the TMS-based association-method for source-space mapping enables physiological investigation of the distinct neuronal populations that give rise to interhemispheric inhibition of the contralateral motor cortex versus motor evoked potentials in contralateral hand muscles. SIHI can be more effectively elicited by targeting the coldspot rather than the hotspot, a potentially relevant distinction when aiming to modify interhemispheric neural communication, e.g., in stroke rehabilitation.
The constantly increasing diversity of the infrastructure used to deliver Internet services to the end user has created a demand for experimental network facilities featuring heterogeneous resources. Therefore, federa...
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The constantly increasing diversity of the infrastructure used to deliver Internet services to the end user has created a demand for experimental network facilities featuring heterogeneous resources. Therefore, federation of existing network testbeds has been identified as a key goal in the testbed community, leading to a recent activity burst in this research field. In this paper, we present a federation scheme that was built during the Onelab 2 EU project. This scheme federates the N1TOS wireless testbed with the wired PlanetLab Europe testbed, allowing researchers to access and use heterogeneous experimental facilities under an integrated environment. The usefulness of the resulting federated facility is demonstrated through the testing of an implemented end-to-end delay aware association scheme proposed for wireless mesh networks. We present extensive experiments under both wired congestion and wireless channel contention conditions that demonstrate the effectiveness of the proposed approach in realistic settings. The experiments are also reproduced in a well-established network simulator and a comparative study between the results obtained in the realistic and simulated environments is presented. Both the architectural building blocks that enable the federation of the testbeds and the execution of the experiment on combined resources, as well as the important insights obtained from the experimental results are described and analyzed, pointing out the importance of integrated experimental facilities for the design and development of the Future Internet. (c) 2014 Elsevier B.V. All rights reserved.
Data mining has the potential to provide information for improving clinical acupuncture strategies by uncovering hidden rules between acupuncture manipulation and therapeutic effects in a data set. In this study, we p...
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Data mining has the potential to provide information for improving clinical acupuncture strategies by uncovering hidden rules between acupuncture manipulation and therapeutic effects in a data set. In this study, we performed acupuncture on 30 patients with hemiplegia due to acute ischemic stroke. All participants were pre-screened to ensure that they exhibited immediate responses to acupuncture. We used a twirling reinforcing acupuncture manipulation at the specific lines between the bilateral Baihui(GV20) and Taiyang(EX-HN5). We collected neurologic deficit score, simplified Fugl-Meyer assessment score, muscle strength of the proximal and distal hemiplegic limbs, ratio of the maximal H-reflex to the maximal M-wave(Hmax/Mmax), muscle tension at baseline and immediately after treatment, and the syndromes of traditional Chinese medicine at baseline. We then conducted data mining using an association algorithm and an artificial neural network backpropagation algorithm. We found that the twirling reinforcing manipulation had no obvious therapeutic difference in traditional Chinese medicine syndromes of "Deficiency and Excess". The change in the muscle strength of the upper distal and lower proximal limbs was one of the main factors affecting the immediate change in Fugl-Meyer scores. Additionally, we found a positive correlation between the muscle tension change of the upper limb and Hmax/Mmax immediate change, and both positive and negative correlations existed between the muscle tension change of the lower limb and immediate Hmax/Mmax change. Additionally, when the difference value of muscle tension for the upper and lower limbs was 〉 0 or 〈 0, the difference value of Hmax/Mmax was correspondingly positive or negative, indicating the scalp acupuncture has a bidirectional effect on muscle tension in hemiplegic limbs. Therefore, acupuncture with twirling reinforcing manipulation has distinct effects on acute ischemic stroke patients with different symptoms or stages of
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