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3rd European-Alliance-for-Innovation (EAI) International Conference on Advanced Hybrid Information Processing (ADHIP)

作者： Wang, Chao Nanyang Inst Technol Sch Software Nanyang Peoples R China

ISBN: (纸本)9783030364021;9783030364014

In order to solve the problem of too low total load of individual nodes, a dynamic network load evaluation algorithm based on throughput monitoring was proposed. The node monitoring quantity analysis and evaluation parameter determination were used to complete the monitoring description of the dynamic network throughput rate. On this basis, through the improvement of load effect, evaluation mechanism establishment and correction factor calculation, the new evaluation algorithm was completed. The experimental results showed that after applying the dynamic network load evaluation algorithm based on throughput monitoring, the problem of too low total load of individual nodes was effectively solved.

关键词： Throughput monitoring Load evaluation network algorithm Node monitoring Equilibrium mechanism Correction factor

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Study on Adaptive Hybrid Prediction algorithm and Its Implementation Based on Neural network

Study on Adaptive Hybrid Prediction Algorithm and Its Implem...

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International Forum on Materials Processing Technology (IFMPT) / International Conference on Sensors, Instrument and Information Technology (ICSIIT)

作者： Liang, Cheng Northeast Petr Univ Daqing 163318 Heilongjiang Peoples R China

ISBN: (纸本)9783038350453

In this paper, nonlinear time series forecasting system combining algorithm proposed prediction model. For the model of the existing combination forecasting method selection and mixed results so that it can be improved terms for a variety of different sequences with adaptive prediction. The results show that for different test data set, the method can effectively use all kinds of prediction Models pool without specific filter to adjust the mixing weight ratio of each of the prediction results so that the adaptive prediction, ensure higher prediction accuracy achieved.

关键词： Adaptive Neural network algorithm Predictive algorithm

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SWAP: A Sliding Window algorithm for In-network Packet Measurement 19

SWAP: A Sliding Window Algorithm for In-network Packet Measu...

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3rd International Conference on High Performance Compilation, Computing and Communications (HP3C)

作者： Hang, Zijun Shi, Yang Wen, Mei Quan, Wei Zhang, Chunyuan Natl Univ Def Technol Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781450366380

network traffic measurement is a fundamental part of many network applications, such as DDOS detection, capacity planning, and quality-of-service improvement. To achieve this, we need to count the number of packets passed during a past time interval. Traditionally, switches sample the packets and send them to the CPU for analysis. It is unavoidable that the sampling will sacrifice the measuring accuracy. Nowadays, programmable switches can keep the counters in the data plane. However, they still rely on the CPU to drain and clear the records periodically, which brings in too much communication latency. To overcome these disadvantages, we propose a metering mechanism under the RMT architectural model called SWAP. SWAP is carefully designed to count the number of packets during an interval accurately with little hardware resource usage. We prototype it using P4 and simulation results show SWAP achieves high efficiency and moderate accuracy at line speed.

关键词： Software-Defined networks P4 Programmable switches network algorithm

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INBIA: a boosting methodology for proteomic network inference

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BMC BIOINFORMATICS 2018年第7期19卷 77-88页

作者： Sardina, Davide S. Micale, Giovanni Ferro, Alfredo Pulvirenti, Alfredo Giugno, Rosalba Univ Verona Dept Comp Sci Str Grazie 15 I-37134 Verona Italy Univ Catania Dept Math & Comp Sci Viale A Doria 6 I-95125 Catania Italy Univ Catania Dept Clin & Expt Med Dept Math & Comp Sci Viale A Doria 6 I-95125 Catania Italy

Background: The analysis of tissue-specific protein interaction networks and their functional enrichment in pathological and normal tissues provides insights on the etiology of diseases. The Pan-cancer proteomic project, in The Cancer Genome Atlas, collects protein expressions in human cancers and it is a reference resource for the functional study of cancers. However, established protocols to infer interaction networks from protein expressions are still missing. Results: We have developed a methodology called Inference network Based on iReflndex Analysis (INBIA) to accurately correlate proteomic inferred relations to protein-protein interaction (PPI) networks. INBIA makes use of 14 network inference methods on protein expressions related to 16 cancer types. It uses as reference model the iReflndex human PPI network. Predictions are validated through non-interacting and tissue specific PPI networks resources. The first, Negatome, takes into account likely non-interacting proteins by combining both structure properties and literature mining. The latter, TissueNet and GIANT, report experimentally verified PPIs in more than 50 human tissues. The reliability of the proposed methodology is assessed by comparing INBIA with PERA, a tool which infers protein interaction networks from Pathway Commons, by both functional and topological analysis. Conclusion: Results show that INBIA is a valuable approach to predict proteomic interactions in pathological conditions starting from the current knowledge of human protein interactions.

关键词： Protein interaction network network inference Protein expression network algorithm

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Characteristics of different swimming styles of swimming events based on artificial neural network data acquisition system

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NEURAL COMPUTING & APPLICATIONS 2023年第6期35卷 4337-4352页

作者： Xu, Wei Xu, Lie Heilongjiang Univ Dept Sports Teaching & Res Harbin 150080 Heilongjiang Peoples R China Harbin Inst Technol Coll Extended Educ Harbin 150006 Heilongjiang Peoples R China

In recent years, remote data collection and remote monitoring technologies based on artificial neural networks have been increasingly used in various industries. In order to in-depth study whether the data collection system based on artificial neural network theory can analyze the characteristics of different strokes in swimming events, this paper uses simulation comparison method, data integration method, and step-by-step construction method to collect samples, analyze the data collection system, and streamline the algorithm. And integrate and create a data collection system that can analyze the characteristics of swimming styles. After constructing the system, select the image frequency 450 ms once, and set the signal frequency to 2.5 KHZ. Set the waveforms to sawtooth wave and sine wave, respectively;the voltage range of sine wave is - 6 to 8 V, and the sampling frequency is 250. The voltage range of the sawtooth wave is - 8 to 6 V, and the sampling frequency is 45 KHZ. Experiments show that the system basically works normally during the sampling process. To further study the stability of the system, this test is in a swimming pool with a one-story building with a relative humidity of 85%. It is set to send 110 data frames from the coordinator segment to the normal segment every 2.5 s. The acquisition success rate is 88% when there is interference and 96% when there is no interference, which is much higher than that when there is interference. Therefore, a retransmission mechanism must be used when designing the software for common segment points to ensure reliable data transmission. In general, the data acquisition system we designed basically meets the design standards. It is basically realized that starting from the artificial neural network, a data acquisition system that can analyze swimming styles is designed.

关键词： Artificial neural network Data acquisition system Different swimming styles of swimming events Sensor technology network algorithm

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Connect to green: High-speed rail network and firms' environmental performance

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TRANSPORT POLICY 2024年 159卷 297-313页

作者： Li, Shuaihang Liu, Qing Shao, Zhi Shanghai Univ Finance & Econ Coll Business Shanghai Peoples R China Hefei Univ Technol Sch Econ Hefei Peoples R China Tsinghua Univ Sch Econ & Management Beijing Peoples R China

High-speed rail (HSR) has completely revolutionized intercity travel, significantly impacting economic activities. Recent studies have increasingly focused on how HSR affects environmental pollution. Given China's extensive HSR policy in recent years, we extend this discussion in the context of China, introducing several new dimensions. Firstly, by manually collecting the daily operating routes of each HSR line in China, we construct a dynamic, directed, and weighted HSR network and provide a detailed description of the topological evolution of Chinese HSR from 2007 to 2014. Secondly, by employing network theory algorithms, we develop a city-level HSR strength index. This approach diverges from the commonly used multi-period difference- in-differences (DID) specification, allowing us to better address heterogeneity and discontinuity issues in identifying HSR effects. Thirdly, by leveraging the specific structure of the HSR network, we analyze how cities are interconnected and, for the first time, discuss the impact of "HSR-catalyzed supervision pressure"on firms' pollution performance. Our findings show that firms exposed to higher HSR service intensity are more likely to reduce their SO2 emissions, a result that remains robust across various checks and other pollutants. We propose an intercity interaction story, predicting that HSR facilitates spillovers among city groups, thereby increasing environmental supervision pressure from neighboring cities in the HSR network. In further empirical analysis, we identify three specific sources of supervision pressure: peer pressure, vertical pressure, and public pressure.

关键词： High-speed rail network algorithm Environmental performance Supervision pressure

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RwHash: Rewritable Hash Table for Fast network Processing with Dynamic Membership Updates 17

RwHash: Rewritable Hash Table for Fast Network Processing wi...

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13th ACM/IEEE Symposium on Architectures for networking and Communications Systems (ANCS)

作者： Song, Tian Yang, Yating Crowley, Patrick Beijing Inst Technol Sch Comp Sci & Technol Beijing Peoples R China Washington Univ Dept Comp Sci & Engn St Louis MO USA

ISBN: (纸本)9781509063864

Hash table is one of the most fundamental and critical data structures for membership query and maintenance. However, the performance of a standard hash table degrades greatly when the hash collision is large due to high load factor or unpredictable dynamic membership updates, especially per-packet updates in network processing. In this paper, we shape a hash table from the conventional slim-and-tall style to a wide-and-short style by facilitating an extension of logical cache block. Then, a cache aware hash table (CaHash) is given and explored in detail. Based on an observation that the operation sequences may be in a potential and probabilistic successive order, especially for network applications, a rewritable hash table (RwHash) is finally proposed, which provides two rewritable policies to dynamically move elements within a bucket when updating. Theoretical analysis shows that, no matter what load factor and collision are, RwHash can achieve near-optimal performance the same as the performance when a standard hash table in the case of no collision. Real experiments show that RwHash can achieve 4.10 times speedup in some parameter and even more with different configurations than a standard hash table in the case of heavy collisions. Our approaches are elegantly practical in implementation for both software and hardware.

关键词： Hash Table network algorithm Membership Query

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THE NEGOPY network ANALYSIS PROGRAM

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SOCIAL networkS 1981年第3期3卷 215-223页

作者： RICHARDS, WD RICE, RE STANFORD UNIV INST COMMUN RESSTANFORDCA 94305

A method and its associated computer program for (specifically communication) network analysis are described. The program described here, NEGOPY, is relational, or linkage-based. The conceptual orientation, computational algorithm, operating characteristics, format and availability of NEGOPY are described. Finally, a partial bibliography of works describing other aspects of NEGOPY and research studies using NEGOPY is included.

关键词： network analysis computer program relational method network algorithm NEGOPY

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LErNet: characterization of lncRNAs via context-aware network expansion and enrichment analysis 16

LErNet: characterization of lncRNAs via context-aware networ...

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16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB)

作者： Bonnici, Vincenzo Caligola, Simone Fiorini, Giulia Giudice, Luca Giugno, Rosalba Univ Verona Dept Comp Sci I-37134 Verona Italy

ISBN: (纸本)9781728114620

Long non-coding RNAs (lncRNAs) have recently acquired a boost of interest for their implication in several biological conditions. However, many of these elements are not yet characterized. LErNet is a method to in silico define and predict the roles of lncRNAs. The core of the approach is a network expansion algorithm which enriches the genomic context of lncRNAs. The context is built by integrating the genes encoding proteins that are found next to the non-coding elements both at genomic and system level. The pipeline is particularly useful in situations where the functions of discovered lncRNAs are not yet known. The results show both the outperformance of LErNet compared to enrichment approaches in literature and its robustness in case of partially missing context information. LErNet is provided as an R package.

关键词： network algorithm network enrichment analysis network expansion non-coding RNA

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network partitioning algorithms with scale-free objective: algorithmes de partitionnement de réseaux avec un objectif scale-free

Network partitioning algorithms with scale-free objective: A...

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作者： Martin, Nicolas Université Grenoble Alpes

学位级别：博士

En raison de la complexité inhérente à l’analyse de réseau de très grande taille, l’élaboration d’algorithmes de partitionnement et diverses problématiques connexes sont traitées au long de cette thèse. Dans un premier temps, une question préliminaire est traitée: puisque les nœuds au sein d’une partie ne sont pas nécessairement connexes, comment quantifier l’impact d’une contrainte de connexité ? Nous proposons ensuite un algorithme de partitionnement assurant que le réseau réduit soit scale-free. Ceci permet de tirer profit des propriétés intrinsèques de ce type de réseaux. Nous nous intéressons également aux propriétés à préserver pour respecter la nature physique et dynamique du réseau initial. Dans une troisième partie, nous proposons une méthode pour identifier les nœuds à mesurer dans un réseau pour garantir une reconstruction efficace de la valeur moyenne des autre nœuds. Finalement, nous proposons trois applications: la première concerne le trafic routier et nous montrons que notre premier algorithme de partitionnement permet d’obtenir un réseau réduit émulant efficacement le réseau initial. Les deux autres applications concernent les réseaux d’épidémiologie. Dans la première nous montrons qu’un réseau réduit scale-free permet de construire une stratégie efficace d’attribution de soin au sein d’une population. Dans la dernière application, nous tirons profit des résultats sur la reconstruction de moyenne pour estimer l’évolution d’une épidémie dans un réseau de grande taille. In light of the complexity induced by large-scale networks, the design of network partitioning algorithms and related problematics are at the heart of this thesis. First, we raise a preliminary question on the structure of the partition itself: as the parts may includes disconnected nodes, we want to quantify the drawbacks to impose the nodes inside each part to be connected. Then we study the design of a partitioning algorithm inducing a reduced scale-free network. This allows to take

关键词： algorithme réseaux Reduction de réseaux Réseau invariant d'échelle Partition de réseaux Réseau de traffic Epidémiologie network algorithm network reduction Scale-Free networks network partition Road traffic network network epidemics 004 620

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