Use Of Dynamic Data Research Articles

Исследование модернизации морского пассажирского порта на основе цифрового двойника и оценка инфраструктуры с помощью динамических данных от беспилотных авиационных систем

The current state of the maritime passenger transportation industry is considered, as well as the factors influencing the chosen industry are investigated (competition between ports in the sea region, new environmental requirements and a shortage of space for new ports and terminals in megacities). Models of the evolution of seaports and terminals in the regions of the seas are analyzed and the need to solve the problem of forecasting development, reasonable modernization is revealed infrastructure. The importance of integrating passenger ports into urban transport systems and ensuring effective interconnection of maritime transport with regional transport systems is noted. Special attention is paid to the growth and development potential of sea ferries and cruises in the Baltic Sea region, the historical importance of St. Petersburg for cruise tourism and the need for the gradual restoration of the port and the development of new route networks are noted. The necessity of developing new methods for modernizing the infrastructure of passenger seaports based on the creation of digital models and the use of dynamic data is substantiated. As a solution, it is proposed to create a new digital model of a marine passenger port using information obtained from unmanned aircraft systems. This model will accurately take into account the infrastructural features of passenger ports and terminals, as well as the established priority of berths for the service of cruise and ferry ships. For multi-scenario modeling, a new digital model of the marine passenger port of St. Petersburg “Marine Façade” is proposed. To analyze the simulation results, the developed software modules in the Python programming language are proposed to describe the behavior strategies of the decision maker (port manager). To describe the decision-making process in the conditions of uncertainty that arises when making a decision on the modernization of the port infrastructure, the choice of the Wald criterion was justified as a criterion. A series of experiments was performed, based on the data, digital 2D and 3D models of a marine passenger port were formed for subsequent use in the AnyLogic environment, and a digital twin was built. A distinctive feature of the model is the up-to-date information on the state of the transport infrastructure and integration with data on ship calls. The presented model, methods of working with the results of multi-dimensional modeling, the use of unmanned aircraft systems, and the development of a model based on decision-making under uncertainty can be applied to other passenger seaports and terminals, which emphasizes the universality of the proposed approach.

Architecture of an intelligent information system for forecasting components of medical projects

The article concerns the development of an intelligent information system for forecasting components of medical projects. The purpose of the study is to propose an intelligent information system for forecasting component medical projects, which is based on the use of neural network models, as well as statistical and expert methods, which, unlike existing ones, ensures the accuracy of forecasting component medical projects, adaptability to changes in their project environment, as well as accessibility for users. The task of the research is to substantiate the architecture and develop an algorithm for the operation of an intelligent information system for forecasting component medical projects, as well as to develop the user interface of this system and to carry out forecasting of component medical projects. The object of research is decision support processes in medical project management. The subject of the study is the architecture of an intelligent information system for forecasting the components of medical projects, which defines the model, structure, functions, and relationships between its components. The scientific novelty is to substantiate the algorithm and architecture of an intelligent information system for forecasting the components of medical projects based on the use of dynamic data (modern medical records, medical information system server, and other external data), which ensures the formation of a large database underlying the training of neural network models and ensuring high accuracy of forecasting the components of medical projects. The proposed intelligent information system is an effective tool that can be used to increase the accuracy of management decisions and the effectiveness of medical projects. The system involves the use of a medical information system for the formation of a historical database, which ensures the formation of a knowledge base and the development of a set of systematically interconnected blocks. The developed algorithm of the proposed intelligent information system involves the implementation of 17 steps, which reflect the intellectual approach, which involves the use of neural networks for forecasting the components of medical projects. A user interface of an intelligent information system for evaluating component medical projects has been developed, which involves the use of 6 tabs. The use of dialog boxes for forecasting components of 5 groups of projects is foreseen. These include projects for the creation of hospital districts, projects of highly specialized medicine, projects of specialized medicine, projects of primary medicine, and advisory and diagnostic projects. A proposed neural network for predicting the duration of diabetes treatment projects in children. It is a deep neural network with two levels, which provides forecast accuracy at the level of 95.4 %, which indicates its sufficient efficiency and feasibility of use in an intelligent information system. Established trends in the duration of diabetes treatment in children due to changes in the main factors that cause them. The obtained results depend based on improving the quality and accuracy of decision support for assessing the duration of diabetes treatment in children with different states of their disease

Fully Dynamic Data Management in Cloud Storage Systems with Secure Proof of Retrievability

For reliable storage services, we need a way not only to monitor the state of stored data but also to recover the original data when some data loss is discovered. To solve the problem, a novel technique called HAIL has been proposed. Unfortunately, HAIL cannot support dynamic data which is changed according to users' modification queries. There are many applications where dynamic data are used. So, we need a way to support dynamic data in cloud services to use cloud storage system for various applications. In this paper, we propose a new technique that can support the use of dynamic data in cloud storage systems. For dynamic data update, we design a new data chunk generation strategy which guarantee efficient data insertion, deletion, and modification. Our technique requires O(1) operations for each data update when existing techniques require O(n) operations where n is the size of data.

Comparison of geographic workflow preferences with real-time dynamic regional mapping data during catheter ablation

Abstract Funding Acknowledgements Type of funding sources: None. Introduction The clinical benefit of multielectrode high-density (HD) mapping during catheter ablation has been an area of active research. One advantage of HD mapping is improved sensitivity which can lead to better visualization and substrate delineation during the procedure. In addition to the advantages offered by the multielectrode grid mapping catheter (HD Grid), a novel software enable the display of beat-to-beat, dynamic regional mapping data from the current location of HD Grid in real-time (LiveView). The optimal settings and workflows to incorporate the dynamic data into routine ablation procedures have not been explored. Purpose To examine the common settings and workflow patterns among operators from different geographies when using dynamic mapping. Methods Observational procedural data including procedure time, total RF time, workflow preference, and fluoroscopy time, were prospectively collected from operators across Europe, the U.S., and Asia Pacific countries from May to September 2020. Cases from both catheter ablation of atrial and ventricular arrhythmias were included in the analysis. Results A total of 754 cases were collected (428, 133, and 193 cases from Europe, the U.S., and the Asia Pacific region, respectively). The most commonly reported indication across all three geographies was de novo paroxysmal atrial fibrillation (223/754, 30.0%). A steerable sheath was more frequently used with the mapping catheter in Europe and U.S. compared to Asia Pacific countries. Contrary to cases from the U.S. and Asia Pacific countries where the double transseptal approach was the preferred technique for left atrial procedures (78.8% and 55.3%, respectively), the single transseptal approach was more commonly observed in European cases (233/428, 54.4%). Visualization of real-time mapping data after creation of traditional full-chamber maps were commonly observed in all three geographies. Regardless of geography, the CS catheter was commonly used a reference electrode; and the most common map appearance settings for interior projection, exterior projection, and interpolation was 7, 7, and 7 respectively. Voltage cutoff of 0.1 mV, range from 0.01 to 1.5 mV, was most frequently observed for delineating scar in atrial arrhythmia cases analyzed in this dataset. Conclusions While there is a geographical difference in ablation workflow, common settings and patterns can be observed in all three regions. This data suggests that minimal workflow changes are required to incorporate the use of dynamic data into routine procedures. Adaptation of LiveView can help improve procedure efficiency and efficacy by reducing the need for full chamber maps, identifying areas that were under ablated, and confirming ablation endpoints. Further control study examining procedure efficiency and efficacy associated with dynamic mapping may be warranted.

New method of tapping potential of remaining oil after chemical flooding

In the study area, the chemical flooding type II oil layer and the water flooding type III oil layer exhibited alternating distribution in the horizon. The recovery factor during the chemical flooding stage was relatively low, at 7.44%, and had the potential for mining. Subsequent water flooding phases cannot use conventional potential tapping methods. It is necessary to further explore new targeted potential tapping methods and explore new ways for more cost-effective development. This study makes full use of dynamic data, fine reservoir description data and numerical modeling data to identify the remaining oil in the subsequent waterflooding stage, through coordinated adjustment of well patterns in the second and third types of oil layers, using unblocking, periodic production, reduced-speed oil production, and rotation Use wells and other methods to comprehensively tap potential and tap remaining oil.

Use of Dynamic Data and a New Material-Balance Equation for Estimating Average Reservoir Pressure, Original Gas in Place, and Optimal Well Spacing in Shale Gas Reservoirs

Summary The average reservoir pressure is a key parameter in material-balance calculations, but its determination is challenging when dealing with shales because of their low and ultralow permeabilities. This paper presents an easy-to-reproduce methodology for calculating the average reservoir pressure from flowing data, and its use in a new material-balance equation (MBE) that considers the simultaneous contribution of free, adsorbed, and dissolved gas. The procedure developed in this paper uses a modified gas-compressibility factor (Z′) introduced in the new MBE. Because Z′ accounts for the combined effect of free, adsorbed, and dissolved gas, then total original gas in place (OGIP) can be determined from extrapolation of the MBE straight line to an average reservoir pressure equal to zero. Drainage area can be estimated on the basis of calculated OGIP and volumetric equations. As such, the methodology offers the potential to help improve well spacing in shale gas reservoirs in such a way that no stranded gas is left in the reservoir, or that excess wells are not drilled in the field. This can help to improve recoveries from shales by assisting in the determination of the optimal number of wells needed to drain a given play efficiently. In conventional reservoirs, a well is shut in, and the average reservoir pressure is determined from the corresponding pressure-buildup test. But, for the case of unconventional shale gas reservoirs, shutting the wells in is unacceptable because of the long time it would require for estimating average reservoir pressure. The methodology developed in this paper for shale gas reservoirs circumvents this problem by using dynamic data. Production data from multistage hydraulically fractured horizontal wells completed in a Canadian shale gas reservoir are used for testing the effectiveness of the new methodology. Comparison of typical well-spacing values vs. the drainage area calculated with the new methodology leads to the conclusion that, probably, only 40% of the gas is being drained efficiently. The novelty of this work relies on the development of a methodology for calculating average reservoir pressure, OGIP, drainage area, and optimal well spacing in shale reservoirs through the combination of dynamic data and a new MBE that considers simultaneously the effects of free, adsorbed, and dissolved gas.

Feasibility of myocardial flow reserve prediction without the use of dynamic data from myocardial perfusion positron emission tomography

Quantification of myocardial flow reserve (MFR) provides diagnostic value for detection of cardiovascular artery disease. However, the common calculation method for MFR requires dynamic acquisition and specific software. The study aimed to predict coronary artery disease by simpler calculation of myocardial count without the use of dynamic data from 13N-ammonia myocardial perfusion positron emission tomography (MP-PET). This study included 40 consecutive patients suspected of ischemic heart disease and 7 healthy controls (34 men and 13 women, 66 ± 12years). All participants underwent adenosine stress and rest 13N-ammonia MP-PET. From the dynamic images, the MFR in the entire left ventricular myocardium (ELV) and the three-vessel area was calculated by dividing stress myocardial blood flow (MBF) by rest MBF. From the static images, the myocardium-to-background ratio (MBR) was calculated by dividing each area's counts/pixel by background counts in the upper thoracic aorta/pixel in both stress and rest images. The MBR-increasing rate (MBR-IR) was calculated by dividing stress MBR by rest MBR. The relationship between MFR and MBR-IR in each area was examined. The cutoff diagnostic value of MBR-IR corresponding to that of MFR for detection of cardiovascular artery disease was calculated. Each MBR-IR was closely correlated with each MFR (r = 0.830 in ELV, r = 0.864 in LAD, r = 0.829 in LCX, r = 0.757 in RCA). The cutoff values of MBR-IR were 1.45 in ELV, 1.46 in LAD, 1.41 in LCX, and 1.45 in RCA, respectively. This study demonstrated that quantification of MBR-IR may provide diagnostic value for detection of coronary artery disease as well as MFR.

TxRace

Detecting data races is important for debugging shared-memory multithreaded programs, but the high runtime overhead prevents the wide use of dynamic data race detectors. This paper presents TxRace, a new software data race detector that leverages commodity hardware transactional memory (HTM) to speed up data race detection. TxRace instruments a multithreaded program to transform synchronization-free regions into transactions, and exploits the conflict detection mechanism of HTM for lightweight data race detection at runtime. However, the limitations of the current best-effort commodity HTMs expose several challenges in using them for data race detection: (1) lack of ability to pinpoint racy instructions, (2) false positives caused by cache line granularity of conflict detection, and (3) transactional aborts for non-conflict reasons (e.g., capacity or unknown). To overcome these challenges, TxRace performs lightweight HTM-based data race detection at first, and occasionally switches to slow yet precise data race detection only for the small fraction of execution intervals in which potential races are reported by HTM. According to the experimental results, TxRace reduces the average runtime overhead of dynamic data race detection from 11.68x to 4.65x with only a small number of false negatives.

TxRace

Detecting data races is important for debugging shared-memory multithreaded programs, but the high runtime overhead prevents the wide use of dynamic data race detectors. This paper presents TxRace, a new software data race detector that leverages commodity hardware transactional memory (HTM) to speed up data race detection. TxRace instruments a multithreaded program to transform synchronization-free regions into transactions, and exploits the conflict detection mechanism of HTM for lightweight data race detection at runtime. However, the limitations of the current best-effort commodity HTMs expose several challenges in using them for data race detection: (1) lack of ability to pinpoint racy instructions, (2) false positives caused by cache line granularity of conflict detection, and (3) transactional aborts for non-conflict reasons (e.g., capacity or unknown). To overcome these challenges, TxRace performs lightweight HTM-based data race detection at first, and occasionally switches to slow yet precise data race detection only for the small fraction of execution intervals in which potential races are reported by HTM. According to the experimental results, TxRace reduces the average runtime overhead of dynamic data race detection from 11.68x to 4.65x with only a small number of false negatives.

TxRace

Detecting data races is important for debugging shared-memory multithreaded programs, but the high runtime overhead prevents the wide use of dynamic data race detectors. This paper presents TxRace, a new software data race detector that leverages commodity hardware transactional memory (HTM) to speed up data race detection. TxRace instruments a multithreaded program to transform synchronization-free regions into transactions, and exploits the conflict detection mechanism of HTM for lightweight data race detection at runtime. However, the limitations of the current best-effort commodity HTMs expose several challenges in using them for data race detection: (1) lack of ability to pinpoint racy instructions, (2) false positives caused by cache line granularity of conflict detection, and (3) transactional aborts for non-conflict reasons (e.g., capacity or unknown). To overcome these challenges, TxRace performs lightweight HTM-based data race detection at first, and occasionally switches to slow yet precise data race detection only for the small fraction of execution intervals in which potential races are reported by HTM. According to the experimental results, TxRace reduces the average runtime overhead of dynamic data race detection from 11.68x to 4.65x with only a small number of false negatives.

Dynamic and Speculative Polyhedral Parallelization of Loop Nests Using Binary Code Patterns

Speculative parallelization is a classic strategy for automatically parallelizing codes that cannot be handled at compile-time due to the use of dynamic data and control structures. Another motivation of being speculative is to adapt the code to the current execution context, by selecting at run-time an efficient parallel schedule. However, since this parallelization scheme requires on-the-fly semantics verification, it is in general difficult to perform advanced transformations for optimization and parallelism extraction. We propose a framework dedicated to speculative parallelization of scientific nested loop kernels, able to transform the code at runtime by re-scheduling the iterations to exhibit parallelism and data locality. The run-time process includes a transformation selection guided by profiling phases on short samples, using an instrumented version of the code. During this phase, the accessed memory addresses are interpolated to build a predictor of the forthcoming accesses. The collected addresses are also used to compute on-the-fly dependence distance vectors by tracking accesses to common addresses. Interpolating functions and distance vectors are then employed in dynamic dependence analysis and in selecting a parallelizing transformation that, if the prediction is correct, does not induce any rollback during execution. In order to ensure that the rollback time overhead stays low, the code is executed in successive slices of the outermost original loop of the nest. Each slice can be either a parallelized version, a sequential original version, or an instrumented version. Moreover, such slicing of the execution provides the opportunity of transforming differently the code to adapt to the observed execution phases. Parallel code generation is achieved almost at no cost by using binary code patterns that are generated at compile-time and that are simply patched at run-time to result in the transformed code.The framework has been implemented with extensions of the LLVM compiler and an x86-64 runtime system. Significant speed-ups are shown on a set of benchmarks that could not have been handled efficiently by a compiler.

GEOLOGICAL MODEL EVALUATION THROUGH WELL TEST SIMULATION: A CASE STUDY FROM THE WYTCH FARM OILFIELD, SOUTHERN ENGLAND

This paper presents an approach to the evaluation of reservoir models using transient pressure data. Braided fluvial sandstones exposed in cliffs in SW England were studied as the surface equivalent of the Triassic Sherwood Sandstone, a reservoir unit at the nearby Wytch Farm oilfield. Three reservoir models were built; each used a different modelling approach ranging in complexity from stochastic pixel‐based modelling using commercially available software, to a spreadsheet random number generator. In order to test these models, numerical well test simulations were conducted using sector models extracted from the geological models constructed. The simulation results were then evaluated against the actual well test data in order to find the model which best represented the field geology.Two wells at Wytch Farm field were studied. The results suggested that for one of the sampled wells, the model built using the spreadsheet random number generator gave the best match to the well test data. In the well, the permeability from the test interpretation matched the geometric average permeability. This average is the “correct” upscaled permeability for a random system, and this was consistent with the random nature of the geological model. For the second well investigated, a more complex “channel object” model appeared to fit the dynamic data better.All the models were built with stationary properties. However, the well test data suggested that some parts of the field have different statistical properties and hence show non‐stationarity. These differences would have to be built into the model representing the local geology.This study presents a workflow that is not yet considered standard in the oil industry, and the use of dynamic data to evaluate geological models requires further development. The study highlights the fact that the comparison or matching of results from reservoir models and well‐test analyses is not always straightforward in that different models may match different wells. The study emphasises the need for integrated analyses of geological and engineering data. The methods and procedures presented are intended to form a feedback loop which can be used to evaluate the representivity of a geological model.

Methods for facilitating web-based participatory research informatics

Scientific datasets are often generated and used by “communities”, or groups of users and creators. These communities, today often virtual, can include researchers, decision-makers, and the general public; participants in these communities may contribute different components during various iterations in the data generation process, and have different needs for resulting data products. As this “participatory research informatics” model, which includes elements of collaborative research, public participation, and digital data libraries, becomes the norm, new approaches to dynamic data management will be important. Researchers commonly use the web as a medium for research collaboration among colleagues, as well as to disseminate results to decision-makers and the public. In addition, the web can be used to facilitate dynamic collaboration by allowing research-in-progress to be accessed and edited by multiple participants. Indeed, one key benefit of using the web to facilitate research projects is that data can undergo revisions and corrections while being displayed in some form over the web. However, it can be a challenge to keep track of multiple edits to files while maintaining the integrity of a web-interface. Here we describe a system for promoting collaboration in the creation, maintenance, and use of dynamic data over the web. Using simple Microsoft Excel spreadsheets combined with traditional relational databases to facilitate dynamic data generation and updates and maintain a data schema, we are able to facilitate efficient collaboration within and among participant communities. This approach allows for the separation of web display and content, which in turn allows participants to be responsible for their own content. This separation simplifies the interaction between those responsible for the content (researchers and other participants), those responsible for the data display (web designers), and those responsible for data management, storage, and retrieval (web programmers). The approach described here is particularly well suited to large, spatially-specific ecological datasets because it can be used to facilitate the “real-time” editing and display of visual data such as web-maps, as well as to encourage multiple participants to both contribute to and interact with “beta” data and content.

Evaluation of the Watermark sensor for use with drip irrigated vegetable crops

The Watermark 200SS sensor was evaluated for the measurement of soil matric potential (SMP) with drip-irrigated vegetable crops. Pepper and melon crops were grown sequentially during autumn-winter and spring-summer, in a sandy loam soil in a greenhouse. Ranges of SMP were generated by applying three different irrigation treatments — 100, 50 and 0% of crop water requirements, during two treatment periods (16 December 2002–7 January 2003; 20 January–10 February 2003) in pepper and one treatment period (26 May–6 June 2003) in melon. Watermark sensors and tensiometers were positioned, at identical distances from irrigation emitters, at 10 cm soil depth, with four replicate sensors for each measurement. Electrical resistance from Watermark sensors and SMP from tensiometers were recorded at 30-min intervals. An in-situ calibration equation was derived using data from the first pepper treatment period. For data in the three treatment periods, SMP was calculated from Watermark electrical resistance using the in-situ, Thomson and Armstrong (in Appl Eng Agric 3:186–189 1987), Shock et al. (1998) and Allen (2000) calibration equations. Additionally, the Thomson and Armstrong (in Appl Eng Agric 3:186–189 1987) and Shock et al. (1998) equations were re-parameterised with the SOLVER® function of Microsoft Excel 2000® using data from the first pepper treatment period. Watermark-derived SMP, for each equation, were compared with tensiometer-measured SMP, for −30 kPa, measuring to −2.5 kPa. Where the soil was not drying rapidly, the Shock et al. (1998) equation generally provided an accurate indication of SMP at −30 to −80 kPa. The use of dynamic data (collected every 30 min) compared to static data (collected only at 6 a.m.) did not influence the evaluation of calibration equations. This study suggested that the Watermark sensor can provide an accurate indication of SMP provided that a suitable calibration equation is derived/verified for the specific cropping conditions, and that the performance characteristics of the sensor are considered.

Structural Damage Identification from Dynamic‐Test Data

The paper deals with a methodology for the use of dynamic response as an inspection and surveillance tool for concrete structures (mainly bridges). The method is based upon a finite‐element analysis for identification of stiffness characteristics (related to cracking) starting from modal dynamic parameters (natural frequencies and mode shapes) derived from dynamic tests. The use of dynamic data is convenient because acceleration transducers can be easily mounted in the structure instead of displacement transducers, mainly when the bridge to be tested overpasses a river, high valley, or traffic road. Several damage‐identification examples are performed with groups of reinforced concrete beams with different and well‐defined cracking patterns. Dynamic response is measured by acceleration transducers. This experimental verification clearly shows the effectiveness of the proposed method in the identification of location, extension, and amount of cracking when some important requirements concerning the dynamic data recorded are taken into account. In particular, more than the first natural frequency must be evaluated.

Respiratory control of heart rate: laws derived from analog computer simulation.

The application of dynamic systems analysis, essential for the design of controlled missiles and of man-made automatic control systems of all kinds, to the control systems within the human organism, is beginning to bear fruit in medical science. These organic control systems, which are part of the living process, generally far surpass any man-made systems in subtlety and ingenuity. Their exploration in terms of feedback control theory is highly instructive both to the medical scientist and to the control engineer, since these systems generally display a quality and perfection of control design several orders of magnitude greater than the human mind can now conceive. Some aspects of the control of the human heart rate are presented here. Normal and irregular respiration widely changes the rate of the heart from beat to beat. The mathematical laws describing this behavior were derived from analog computer simulation. On the analog computer a mathematical model of the dynamics of the processes involved was created. This was achieved through the use of dynamic data obtained from experiments designed by the help of control theory. These mathematical laws are useful for understanding the operation of the system concerned, and especially valuable for predicting the existence of hitherto unknown structural and organizational relationships, which can be confirmed experimentally. The electronic analog computer, being fed information about the respiration of the subject, in the form of an electric signal proportional to chest circumference, is able to calculate the timing of the heart beat from beat to beat.