Match Field Research Articles

Utilizing Extremely Fast Decision Tree (EFDT) Algorithm to Categorize Conflict Flow on a Software-Defined Network (SDN) Controller

Software-Defined Networks (SDNs) provide a contemporary approach to networking technology, offering a versatile and dynamically efficient network architecture for enhanced surveillance and performance. However, SDN architectures may encounter flow conflicts. These conflicts arise when modifications are made to specific flow properties, such as priority, match field, and action. Despite the existence of recommended solutions, the process of resolving conflicts in SDN continues to encounter difficulties. This study proposes an Extremely Fast Decision Tree (EFDT) classification technique to detect and categorize conflicts inside the flow table. The novelty of this method is based on the development of an accurate and effective machine-learning technique implemented on the Ryu controller plane and validated using the Mininet simulator. The effectiveness and efficiency of the proposed method were evaluated using various indicators, demonstrating superior performance in recognizing and categorizing conflict flow types in all flow sizes ranging from 10,000 to 100,000.

Excavation Damage Zone fracture modelling for seismic tomography: A comparison of explicit fractures and effective medium approaches

We model the full wavefield produced by a seismic velocity survey and optimise the representation of the fracture zone to best match field waveforms. The velocity survey was part of a mapping study on fractures in the Excavation Damage Zone (EDZ) of ONKALO underground research facility at Olkiluoto. The EDZ results from excavation of the rock mass, which modifies stress conditions changing the nature and behaviour of pre-existing fractures and generating new fracturing. These fractures act as the main transport pathways for contaminants both in and out of a geological disposal facility (GDF). Our goal is to test different representations of the fracture zone and to determine which models most successfully improve the interpretation of the fracture zone, producing estimates of a key unknown parameter, fracture stiffness, in addition to fracture sizes, fracture geometry, fracture density and crack density. We use modelling techniques previously tested in theoretical and laboratory studies and assess their performance on a real engineering problem. The paper introduces the field experiment and relevant information from the GDF in Finland. It describes the methodologies used for representing the fracture networks in the models — Explicit Fracture models with two approximations called Pixelised Fracture Model (PFM) and Equivalent Discrete Fracture Medium (EDFM), the Effective Medium (EM) model, and two versions of the Localised Effective Medium (LEM) model (LEM fine, LEM thick). These alternative representations were used within models of the field experiment and the calculated waveforms were used in an iterative inversion for fracture stiffness. Results show that the EM model and the EDFM model were unsuccessful in matching recorded waveforms. The fine LEM model and the explicit PFM model produced the best results especially after iterative optimisation of the fracture stiffness, giving confidence that further optimisation will lead to improved characterisation of the fracturing from the full waveform data.

FENOMENA KOMUNIKASI KELUARGA DALAM KESUKSESAN TIMNAS SEPAK BOLA MAROKO PADA PIALA DUNIA 2022 DI QATAR

The progress of the Morocco national team at the 2022 World Cup in Qatar exceeded the expectations of many parties. Morocco looks amazing big European teams. Morocco's impressive performance since the group stage made them the first representatives from the African continent to reach the semifinals. The presence of parents and families of the Moroccan national team players is one of the keys to every victory for the Moroccan team. The direct presence of the family at the stadium to provide support and prayers is the spirit for the Moroccan team when they compete. Parents work together to support their children in the field. so that the cohesiveness of the Moroccan team is increasingly visible both outside the field and outside the match field. The research method used is a qualitative research method with a literature study approach.

Implementation Failure Recovery Mechanism using VLAN ID in Software Defined Networks

Link failure is a common problem that occurs in software-defined networks. The most proposed approach for failure recovery is to use pre-configured backup paths in the switch. However, it may increase the number of traffic packets after the traffic is rerouted through the backup path. In this research, the proposed method is the implementation of a failure recovery mechanism by utilizing the fast failover group feature in OpenFlow to store pre-configured backup paths in the switch. The disrupted traffic packets will be labeled using the VLAN ID, which can be used as a matching field. Due to this capability, VLAN ID can aggregate traffic packets into one entry table as a match field in the forwarding rules. Through implementation and evaluation, it is shown that the system can build a backup path in the switch and reroute the disrupted traffic to the backup path. Based on the parameters used, the results show that the proposed approach achieves a recovery time of around 1.02-1.26ms. Additionally, it can reduce the number of traffic packets and has a low amount of packet loss compared to previous methods.

A Novel Method for Routing Optimization in Software-Defined Networks

Software-defined network (SDN) is a new form of network architecture that has programmability, ease of use, centralized control, and protocol independence. It has received high attention since its birth. With SDN network architecture, network management becomes more efficient, and programmable interfaces make network operations more flexible and can meet the different needs of various users. The mainstream communication protocol of SDN is OpenFlow, which contains a Match Field in the flow table structure of the protocol, which matches the content of the packet header of the data received by the switch, and completes the corresponding actions according to the matching results, getting rid of the dependence on the protocol to avoid designing a new protocol. In order to effectively optimize the routing for SDN, this paper proposes a novel algorithm based on reinforcement learning. The proposed technique can maximize numerous objectives to dynamically update the routing strategy, and it has great generality and is not reliant on any specific network state. The control of routing strategy is more complicated than many Q-learning-based algorithms due to the employment of reinforcement learning. The performance of the method is tested by experiments using the OMNe++ simulator. The experimental results reveal that our PPO-based SDN routing control method has superior performance and stability than existing algorithms.

Referee positioning, but not match demands, score difference, or field location, are associated with breakdown decision-making accuracy in elite rugby sevens referees

ABSTRACT This study quantified rugby referees’ decision-making accuracy at the breakdown in an elite rugby sevens tournament, examining whether decision-making accuracy differed over time, and if it was associated with match demands, score difference, field location, and referee positioning. During the National Sevens Tournament (six referees, 22 matches), decision-making accuracy was analysed using video coding from 602 breakdowns and match demands were examined using GNSS technology and heart rate recordings. Overall, the referees had a decision-making accuracy of 88.2% with no changes over time (all p > 0.05). There were no significant associations between match demands, score difference, or field location and decision-making accuracy (all p > 0.05). However, significantly more incorrect decisions occurred when the referees were in a suboptimal position (29.0%) compared to an optimal position (10.9%) at the breakdown (p < 0.05). The findings suggest that referees’ decision-making accuracy during the breakdown remains relatively consistent across an elite rugby sevens tournament. While unaffected by match demands, score difference or field location, referees’ decision-making accuracy may be improved by optimising their positioning at the breakdown.

Underwater Acoustic Source Localization via Kernel Extreme Learning Machine

Fiber-optic hydrophones have received extensive research interests due to their advantage in ocean underwater target detection. Here, kernel extreme learning machine (K-ELM) is introduced to source localization in underwater ocean waveguide. As a data-driven machine learning method, K-ELM does not need a priori environment information compared to the conventional method of match field processing. The acoustic source localization is considered as a supervised classification problem, and the normalized sample covariance matrix formed over a number of snapshots is utilized as an input. The K-ELM is trained to classify sample covariance matrices (SCMs) into different depth and range classes with simulation. The source position can be estimated directly from the normalized SCMs with K-ELM. The results show that the K-ELM method achieves satisfactory high accuracy on both range and depth localization. The proposed K-ELM method provides an alternative approach for ocean underwater source localization, especially in the case with less a priori environment information.

How Are Linkage Results Using Privacy-Preserving Record Linkage Different?

IntroductionPrivacy-Preserving Record Linkage (PPRL) presents opportunities to improve privacy protection when performing record linkage on the most sensitive data. Currently our linkage agency performs all linkages in clear text, but expansion of data sources is now including extremely sensitive data, such as justice data. Understanding that specific circumstances may demand different approaches to linkage, we evaluated a PPRL algorithm implemented through the LinXmart software. This is the first real-world evaluation of PPRL in British Columbia and among the first in Canada. Objectives and ApproachOur standard linkage method is probabilistic and relies on rules established by analysts to determine accepted links. Datasets are linked to a population spine (N=8,440,442) containing all current and past residents of the province. LinXmart was configured to link to the top weighted candidate above a predetermined confidence threshold. We evaluated performance by comparing the standard method to PPRL for three increasingly complex (messy) datasets. Initial results on the simplest/cleanest dataset informed an iterative process to improve implementation of PPRL. ResultsOverall linkage rates were lower for standard linkage (81%) compared to PPRL (90%). Records with a unique ID linked at similarly high rates in clear-text and PPRL, while the performance of PPRL with records without the unique ID varied depending on the exact parameters chosen for the match threshold and field comparisons. Conclusion / ImplicationsThis work suggests that for datasets that include a well-populated unique identifier, PPRL can be implemented in real-world linkages without a substantial drop-off in linkage quality. Messier data require careful tuning of linkage parameters to match the performance of clear linkage. PPRL may best be used in cases where clear text identifiers cannot be shared, and where some degradation in linkage rates is acceptable.

RETCAM: An efficient TCAM compression model for flow table of OpenFlow

OpenFlow is a widely adopted dataplane protocol in software-defined networking (SDN). However, the expansion of supported match fields in OpenFlow brings additional pressure to the storage space of ternary content addressable memory (TCAM) in physical device, since the arbitrary wildcard support in the match field of OpenFlow relies heavily on TCAM for looking-up speed. In this paper, a mathematical model aiming at the storage space reduction of the flow table in TCAM is presented, which is named as RETCAM. RETCAM analyzes the relationships among all the match fields and then categorize the redundancy among different fields into three types. Based on the three redundancy types, three compression algorithms named as inter-field merge, field mapping and intra-field compression are presented. The outcomes of each compression algorithm are flow entries with smaller bit-width which is sent to TCAM for flow matching. In this way, the flexibility of OpenFlow is not harmed, thus maintaining the function integrity of the original flow table. Simulation at the end shows that RETCAM saves almost about 60% of TCAM space for a given flow table with no damage to the function integrity of OpenFlow, and the compression performance stands stable with the increase of flow table size.

Characterization with dense array data of seismic sources in the shallow part of the San Jacinto fault zone

SUMMARY We analyse dominant sources identified in a catalogue of more than 156 000 localizations performed using a 26-d data set recorded by a dense array set on the San Jacinto fault near Anza, in California. Events were localized using an array processing technique called Match Field Processing. As for all array processing techniques, the quality of the event position decrease when the events are outside of the array. We thus separate localizations in and outside the array using simple geometrical conditions. We compare the time distribution of the localization to additional data such as meteorological data, day of human activity as well as existing catalogues to determine the nature of the dominant events located using our method. We find that most of the events located outside of the array could be attributed to a surface structure excited by wind. On the other hand, part of the localizations under the array occur during regional earthquakes and could correspond to diffraction on the fault's heterogeneities. The rest of the localizations inside the array could be generated by the fault itself.

RuleTailor: Optimizing Flow Table Updates in OpenFlow Switches With Rule Transformations

Software-defined networking (SDN) provides flexible network control, which has enabled new, more complex network control mechanisms. These approaches impose high demands on flow updates in OpenFlow switches. Existing SDN controllers and firmware have been optimized for high-speed network updates, but specific switch implementations differ in their behavior. Previous optimization schemes for updates ignore the diversity of instruction types and switch behavior. In this paper, we present RuleTailor , an efficient, measurement-based optimization framework for SDN flow updates, to overcome these limitations. In contrast to other measurement-based optimization frameworks, RuleTailor uses new techniques, such as instruction type transformation, pseudo deletion, and match field distance, which can work in both the control plane and the data plane. Our evaluation shows that RuleTailor achieves a performance of fewer than 12 milliseconds per update in a content-addressable flow table with 1k entries, outperforming the state-of-the-art measurement-based framework, Tango, by a factor of 10.

Marine Polysaccharides in Pharmaceutical Applications: Fucoidan and Chitosan as Key Players in the Drug Delivery Match Field.

The use of marine-origin polysaccharides has increased in recent research because they are abundant, cheap, biocompatible, and biodegradable. These features motivate their application in nanotechnology as drug delivery systems; in tissue engineering, cancer therapy, or wound dressing; in biosensors; and even water treatment. Given the physicochemical and bioactive properties of fucoidan and chitosan, a wide range of nanostructures has been developed with these polysaccharides per se and in combination. This review provides an outline of these marine polysaccharides, including their sources, chemical structure, biological properties, and nanomedicine applications; their combination as nanoparticles with descriptions of the most commonly used production methods; and their physicochemical and biological properties applied to the design of nanoparticles to deliver several classes of compounds. A final section gives a brief overview of some biomedical applications of fucoidan and chitosan for tissue engineering and wound healing.

Association Between Match Activity, Endurance Levels and Maturity in Youth Football Players.

The aim of the study was to examine the associations between maximal and submaximal field tests with match physical activity and biological maturation in youth football players. Sixty-eight youth football players (U14, U15, U16, U17) performed maximal and submaximal field endurance tests. Biological maturity was estimated calculating the distance from peak height velocity (Y-PHV). Physical match activities were tracked using GPS units and players' post-match rate of perceived exertion (RPE) was recorded. Mainly moderate associations were found between field tests and match activities. Large correlations were found between Yo-Yo Intermittent Recovery test level 1, distance covered at high and very high-speed running, the quantity of very high and maximal metabolic power running. Small to moderate associations between match activities and Y-PHV were observed. The magnitude of correlation between match activities and field tests increased from moderate to large when matches with an RPE>5 were considered. The results provide further evidence of the association between young football players' aerobic performance and match work rate. Submaximal field tests demonstrate ecological validity and may constitute a practical alternative to performing maximal tests. Maturation was found to have a moderate effect on youth players' match work rate.

A Multi-match Approach to the Author Uncertainty Problem

A Multi-match Approach to the Author Uncertainty Problem

Analysis of surface and seismic sources in dense array data with match field processing and Markov chain Monte Carlo sampling

SUMMARY We introduce a methodology based on array processing to detect and locate weak seismic events in a complex fault zone environment. The method is illustrated using data recorded by a dense array of 1108 vertical component geophones in a 600 m × 600 m area on the Clark branch of the San Jacinto Fault. Because surface and atmospheric sources affect weak ground motion, it is necessary to discriminate them from weak seismic sources at depth. Source epicentral positions and associated apparent velocities are extracted from continuous seismic waveforms using Match Field Processing (MFP). We implement MFP at specific frequencies targeting surface and subsurface sources, using for computational efficiency a forward model of acoustic source in a homogenous medium and Markov Chain Monte Carlo sampling. Surface sources such as Betsy gun shots and a moving vehicle are successfully located. Weak seismic events are also detected outside of the array, and their backazimuth angle is retrieved and found to be consistent with the fault geometry. We also show that the homogeneous acoustic model does not yield satisfying results when extracting microseismic event depth, because of the ambiguity between depth and the apparent velocity based on surface data.

Effects of Completion Design on Thermal Efficiency in SAGD

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 193357, “SAGD Circulation Phase: Thermal Efficiency Evaluation of Five Wellbore Completion Designs in Lloydminster Reservoir,” by Daniel Ayala Rivas, SPE, and Ian Gates, SPE, University of Calgary, prepared for the 2018 SPE Thermal Well Integrity and Design Symposium, Banff, Alberta, Canada, 27–29 November. The paper has not been peer reviewed. During the circulation (startup) phase of steam-assisted gravity drainage (SAGD), high-quality steam injected through the injector and producer wells heats the reservoir between the wells. The viscosity is thus lowered, making fluids mobile at approximately 50 to 100°C and creating interwell fluid communication. This paper uses a simulation model to evaluate and compare the thermal efficiency of five different completion design cases during the SAGD circulation phase in the Lloydminster formation in the Lindbergh area in Alberta, Canada. The results show that completion-design configuration affects the heat transfer and thermal efficiency of the circulation process. Introduction The SAGD process is the most commonly used thermal method of in-situ recovery for extracting heavy oil and bitumen resources in Alberta and can yield recovery factors of greater than 60%. The technique requires two parallel horizontal wells, a producer and an injector, known as a well pair. The horizontal producer well is placed approximately 3 m above the oil/water contact (OWC) or above the bottom of the reservoir, and the injector well is placed above the horizontal producer well. Most SAGD well pairs are placed 5 m apart, which corresponds to approximately 50 kPa of hydrostatic head from the injector to the producer. The lateral section of the well pair is approximately 700–1200 m in length. The SAGD thermal method usually consists of two phases, the circulation phase and the full SAGD, or production, phase. After the circulation phase, the well pair is converted to the production phase, during which steam is injected through both tubing strings of the injector well in a dual-completion design while bitumen or heavy oil and condensed steam are produced through the producer well using natural or mechanical lifting. Constant steam injection causes the steam chamber to grow and expand in the reservoir. Variations in thermal efficiency during the circulation phase result from factors such as tubing size, well trajectory, well length, completion configuration, reservoir properties, and operating parameters. To the authors’ knowledge, no published study has determined the thermal efficiency of different completion designs during the circulation phase of a SAGD well pair in a Lloydminster formation. A previous study used a discretized thermal reservoir-wellbore modeling simulator to history match field data obtained from a SAGD well pair in the Lloydminster area. Operating Strategies and Reservoir Model The complete paper discusses SAGD operating strategies and development of well and completion designs in pilot and commercial operations.

Investigation of the Effect of Natural Fractures on Multiple Shale-Gas Well Performance Using Non-Intrusive EDFM Technology

The influence of complex natural fractures on multiple shale-gas well performance with varying well spacing is poorly understood. It is difficult to apply the traditional local grid refinement with structured or unstructured gridding techniques to accurately and efficiently handle complex natural fractures. In this study, we introduced a powerful non-intrusive embedded discrete fracture model (EDFM) technology to overcome the limitations of exiting methods. Through this unique technology, complex fracture configurations can be easily and explicitly embedded into structured matrix blocks. We set up a field-scale two-phase reservoir model to history match field production data and predict long-term recovery from Marcellus. The effective fracture properties were determined thorough history matching. In addition, we extended the single-well model to include two horizontal wells with and without including natural fractures. The effects of different numbers of natural fractures on two-well performance with varying well spacing of 200 m, 300 m, and 400 m were examined. The simulation results illustrate that gas productivity almost linearly increases with the number of two-set natural fractures. Furthermore, the difference of well performance between different well spacing increases with an increase in natural fracture density. A larger well spacing is preferred for economically developing the shale-gas reservoirs with a larger natural fracture density. The findings of this study provide key insights into understanding the effect of natural fractures on well performance and well spacing optimization.

The influence of match phase and field position on collective team behaviour in Australian Rules football

ABSTRACTThis study investigated the influence of match phase and field position on collective team behaviour in Australian Rules football (AF). Data from professional male athletes (years 24.4 ± 3.7; cm 185.9 ± 7.1; kg 85.4 ± 7.1), were collected via 10 Hz global positioning system (GPS) during a competitive AFL match. Five spatiotemporal metrics (x-axis centroid, y–axis centroid, length, width, and surface area), occupancy maps, and Shannon Entropy (ShannEn) were analysed by match phase (offensive, defensive, and contested) and field position (defensive 50, defensive midfield, forward midfield, and forward 50). A multivariate analysis of variance (MANOVA) revealed that field position had a greater influence on the x-axis centroid comparative to match phase. Conversely, match phase had a greater influence on length, width, and surface area comparative to field position. Occupancy maps revealed that players repositioned behind centre when the ball was in their defensive half and moved forward of centre when the ball was in their forward half. Shannon Entropy revealed that player movement was more variable during offence and defence (ShannEn = 0.82–0.93) compared to contest (ShannEn = 0.68–0.79). Spatiotemporal metrics, occupancy maps, and Shannon Entropy may assist in understanding the game style of AF teams.

A novel software-defined network packet security tunnel forwarding mechanism.

The OpenFlow protocol match field capacity is fixed and limited, and packet forwarding in software-defined network lacks valid authentication of data source, integrity verification, and confidentiality protection mechanism. OpenFlow only supports the MPLS label tunnel establishment, and therefore cannot establish a secure tunnel flexibly. In order to solve these problems, we propose P4Sec, a novel software-defined network packet security tunnel forwarding mechanism. As P4 allows the data plane to be reprogrammed to realize the characteristics of packet forwarding, we build a software-defined network security tunnel to prevent data malicious tampering, stealing, forgery and other malicious network behavior, implementing packet routing and forwarding based on gateway identity. Finally, we construct a P4Sec prototype system based on the software switch BMv2, verify the effectiveness of the mechanism through experimental analysis, and evaluate the overhead of the mechanism. The results demonstrate that P4Sec security mechanism ensure the authenticity, integrity, and confidentiality of forwarded data, and realize the secure forwarding requirements of data packets in software-defined network.

Match Field based Algorithm Selection Approach in Hybrid SDN and PCE Based Optical Networks

The evolving internet-based services demand high-speed data transmission in conjunction with scalability. The next generation optical network has to exploit artificial intelligence and cognitive techniques to cope with the emerging requirements. This work proposes a novel way to solve the dynamic provisioning problem in optical network. The provisioning in optical network involves the computation of routes and the reservation of wavelenghs (Routing and Wavelength assignment -RWA). This is an extensively studied multi-objective optimization problem and its complexity is known to be NP-Complete. As the exact algorithms incurs more running time, the heuristic based approaches have been widely preferred to solve this problem. Recently the software-defined networking has impacted the way the optical pipes are configured and monitored. This work proposes the dynamic selection of path computation algorithms in response to the changing service requirements and network scenarios. A software-defined controller mechanism with a novel packet matching feature was proposed to dynamically match the traffic demands with the appropriate algorithm. A software-defined controller with Path Computation Element-PCE was created in the ONOS tool. A simulation study was performed with the case study of dynamic path establishment in ONOS-Open Network Operating System based software defined controller environment. A java based NOX controller was configured with a parent path computation element. The child path computation elements were configured with different path computation algorithms under the control of the parent path computation element. The use case of dynamic bulk path creation was considered. The algorithm selection method is compared with the existing single algorithm based method and the results are analyzed.