Size Of String Research Articles

Enhanced performance prediction of ATL model transformations

Model transformation languages are domain-specific languages used to define transformations of models. These transformations consist of the translation from one modeling formalism into another or just the updating of a given model. Such transformations are often described declaratively and are often implemented based on very small models that cover the language of the input model. As a result, transformation developers are often unable to assess the time required to transform a larger model.Hence, we propose a prediction approach based on machine learning which uses a set of model characteristics as input and provides a prediction of the execution time of a transformation defined in the Atlas Transformation Language (ATL). In our previous work (Groner et al., 2023), we already showed that support vector regression in combination with a model characterization based on the number of model elements, the number of references, and the number of attributes is the best choice in terms of usability and prediction accuracy for the transformations considered in our experiments.A major weakness of our previous approach is that it fails to predict the performance of transformations that also transform attribute values of arbitrary length, such as string values. Therefore, we investigate in this work whether an extension of our feature sets that describes the average size of string attributes can help to overcome this weakness.Our results show that the random forest approach in combination with model characterizations based on the number of model elements, the number of references, the number of attributes, and the average size of string attributes filtered by the 85th percentile of their variance is the best choice in terms of the simple way to describe a model and the quality of the obtained prediction. With this combination, we obtained a mean absolute percentage error (MAPE) of 5.07% over all modules and a MAPE of 4.82% over all modules excluding the transformation for which our previous approach failed. Whereas, we obtained previously a MAPE of 38.48% over all modules and a MAPE of 4.45% over all modules excluding the transformation for which our previous approach failed.

Investigation of key problems of clustering perforation string running in horizontal well with unconventional oil-gas reservoirs

Currently, there are two main clustering perforation methods: coiled tubing-conveyed perforation (TCP) and cable-conveyed perforation (CCP). To improve the efficiency of CCP strings in wellbore pass-through capacity problems, considering wellbore geometry constraints, pipe string variable cross-section, flexible tool deformation, and other factors, the pass-through capacity analysis model of the perforating tool string was established and solved by geometric analysis and beam-column theory. Aiming at the running depth problem of a TCP string, considering the influence of the buckling effect, a model of coiled tubing running depth was established by the infinitesimal method. The field test data were used to verify the effectiveness of the two models. The effects of well trajectory, perforating string size, casing inner diameter, and coiled tubing size on the pass-through capacity of the CCP string and running depth of the TCP string were explored. The results indicate that with the increase of perforation string size or the reduction of casing inner diameter, the pass-through capacity of CCP string decreases; with the increase of coiled tubing specification, the running capacity of TCP string is improved. The work presented in this paper provides an effective analysis method and theoretical guidance for clustering perforation jobs in the field.

Study on the pressure wave velocity model of multiphase fluid in the annulus of dual-gradient drilling

Dual-gradient drilling technology is difficult to detect and deal with well kick, which may cause safety problems such as well control. Once a well kick occurs, the pressure in the narrow annulus increases instantaneously, so it is particularly important to clarify the transmission law of pressure wave. Taking the pressure fluctuation in the annulus of double gradient drilling as an example, considering the boundary between the inner wall of the casing annulus and the outer wall of the drill string, the fluid resistance, the flow field distribution and the multiphase flow, this paper deduces and establishes the multiphase flow pressure wave velocity model in the annulus, and compares the calculation results with the pressure wave velocity model in the circular pipe. The research shows that when the casing and drill string are in the static condition with small roughness and little difference between them, the shear stress on the inner wall of the annulus and the outer wall of the drill string can be treated as equal, and the derivation of the annulus pressure wave velocity model can be simplified. The pressure wave velocity of multiphase flow in annulus is related to casing size, drill string size and multiphase fluid properties. Among them, the gas content is the main influencing factor. With the increase of the gas content, the pressure wave velocity decreases, but the decreasing range will gradually decrease. When the solid content is small, it has little effect on the pressure wave velocity.

Study on the pressure wave velocity model of multiphase fluid in the annulus of dual-gradient drilling

Dual-gradient drilling technology is difficult to detect and deal with well kick, which may cause safety problems such as well control. Once a well kick occurs, the pressure in the narrow annulus increases instantaneously, so it is particularly important to clarify the transmission law of pressure wave. Taking the pressure fluctuation in the annulus of double gradient drilling as an example, considering the boundary between the inner wall of the casing annulus and the outer wall of the drill string, the fluid resistance, the flow field distribution and the multiphase flow, this paper deduces and establishes the multiphase flow pressure wave velocity model in the annulus, and compares the calculation results with the pressure wave velocity model in the circular pipe. The research shows that when the casing and drill string are in the static condition with small roughness and little difference between them, the shear stress on the inner wall of the annulus and the outer wall of the drill string can be treated as equal, and the derivation of the annulus pressure wave velocity model can be simplified. The pressure wave velocity of multiphase flow in annulus is related to casing size, drill string size and multiphase fluid properties. Among them, the gas content is the main influencing factor. With the increase of the gas content, the pressure wave velocity decreases, but the decreasing range will gradually decrease. When the solid content is small, it has little effect on the pressure wave velocity.

Data Deduplication With Random Substitutions

Data deduplication saves storage space by identifying and removing repeats in the data stream. Compared with traditional compression methods, data deduplication schemes are more time efficient and are thus widely used in large scale storage systems. In this paper, we provide an information-theoretic analysis on the performance of deduplication algorithms on data streams in which repeats are not exact. We introduce a source model in which probabilistic substitutions are considered. More precisely, each symbol in a repeated string is substituted with a given edit probability. Deduplication algorithms in both the fixed-length scheme and the variable-length scheme are studied. The fixed-length deduplication algorithm is shown to be unsuitable for the proposed source model as it does not take into account the edit probability. Two modifications are proposed and shown to have performances within a constant factor of optimal with the knowledge of source model parameters. We also study the conventional variable-length deduplication algorithm and show that as source entropy becomes smaller, the size of the compressed string vanishes relative to the length of the uncompressed string, leading to high compression ratios.

Symmetric Encryption using Artificial Neural Network, Binary Tree Traversal, and Interleaving Salting

We have proposed a novel way of symmetric encryption utilizing interleaving salting, Binary Tree traversal, and an Artificial Neural Network in a sequential manner. We have presented the use of an Artificial Neural Network as an invertible(reversible) mathematical function so that decryption of the encrypted output may be possible. Knowledge of the encryption pipeline, salt, and neural network weights is required for decryption. As the same set of values is required for encryption and decryption, our proposed approach is a type of symmetric-key algorithm. Each user will have a unique key. Thus if a key attributing to a particular user is compromised, the integrity of the data of the remaining users will still be maintained. Our approach can be utilized to encrypt text data such as messages, documents, and letters. The encryption process consists of interleaving salting, creation of binary tree by considering the input as its level order traversal, and passing the preorder and inorder traversal of the constructed binary tree as input to the Artificial Neural Network. The output of the Artificial Neural Network would be the encrypted data. Decryption would require determining the input of an Artificial Neural Network from the output, hence solving multiple sets of linear equations and constructing a binary tree from its preorder and inorder traversal. We have then analyzed the variation of performance with the change in the input string size. The codebase of our proposed approach is publicly available at https://github.com/Atishaysjain/Symmetric-Encryption-using-ANN-and-Binary-Trees.

Improving Practical UC-Secure Commitments based on the DDH Assumption

At Eurocrypt 2011, Lindell presented practical static and adaptively UC-secure commitment schemes based on the DDH assumption. Later, Blazy et al. (at ACNS 2013) improved the efficiency of the Lindell's commitment schemes. In this paper, we present static and adaptively UC-secure commitment schemes based on the same assumption and further improve the communication and computational complexity, as well as the size of the common reference string.

Using Variation in Weighting Criteria and String Size Matching on Hybrid Model Schema Matching

Schema matching plays a vital role in the information integration process from heterogeneous databases. Generally, the process of schema matching is to receive input, which are two databases (one as the source and another as a target), to match similarity attributes, and generate output in the form of mapping the similarity of the attribute pairs that are declared suitable. Furthermore, the user will assess these attribute pairs to determine whether the results obtained are correct or still need to be revised. Our previous study developed a model and software prototype of hybrid schema matching using a combination of constraint-based method and instance-based method. In this study, the model improved by adding new features. This paper discusses the increasing effectiveness of adding the features to customize the weight of matching criteria and string sizes matching. The hybrid model's best effectiveness is obtained when the weight of instance is 0.286, the type is 0.238, width is 0.190, nullable is 0.143, unique is 0.095, and the domain is 0.048. The matching process using a bigger string size increases the model effectiveness with the highest precision of 97.66 when the string size interval is between (length-100) and (length+100). The best combination of weight and string size variation obtains 97.66% precision, a 99.90% recall, and an f-measure of 98.74%.

Hydraulics analysis of the U-tubing effect in a riserless drilling system

As a newly developed marine drilling technology, riserless drilling (RD) shows obvious advantages for use in deep-water and ultra-deepwater petroleum resources exploitation. However, the available published hydraulic analysis models for RD are rare or imperfect, especially regarding the lack of accounting for the out-of-hole time. To analyse the actual flow characteristics of drilling mud in an RD system after the surface mud pumping is complete, this paper presents a new hydraulic simulation model of the U-tubing effect. The specific calculation methods of pressure loss in the drilling string and the wellbore annulus at different flow regimes (turbulent flow, transition flow, and laminar flow) are provided based on the Herschel-Bulkley (HB) rheological model. A case study shows that a critical volumetric flow rate (CVFR) exists for a specific RD system to just cause the standpipe pressure to become zero. Only when the initial pump circulation rate is greater than the CVFR can it ensure the normal operation of the RD. Otherwise, the fluid mud level inside the drilling string will drop, resulting in the u-tubing effect. In the first few seconds after the surface pump is shut down, the wellbore transient flow rate is influenced strongly by the initial circulation rate. When the initial flow rate is less than the CVFR, the transient flow rate is accelerated during the first few seconds, which is not the expected behaviour. The influence of the drilling string size, fluid density and rheological parameters of the drilling fluid on the transient flow rate and the Bottom Hole Pressure (BHP) are also considered. The results proved that the smaller values of the rheological parameters are beneficial for reducing the fluctuation of the BHP during the U-tubing process.

Adaptive Conflict Detection Algorithm Based on Rochester Software Transactional Memory

When the transactional memory system detects conflicts, the more read-write addresses are, the higher the false positive rate of this algorithm is. This paper studies the problem and proposes a new signature based optimization algorithm, adaptive increase signature algorithm (AISA). The algorithm can calculate the saturation value of the number of read-write addresses, and dynamically adjust the size of bit string through the calculated saturation value, thus greatly reducing the false positive rate. The experimental results show that AISA can control the false positive rate at a low level on the basis of considering the space cost, and its effect is almost the same as that of 6 times of space, which will improve the performance of transactional memory system greatly.

Analysis on the Critical Speed of Drilling String in Deep Water without Riser

According to logging data of the field, while drilling in the deep water without riser, rules of motion and stress distribution of drilling string is really complicated without the constraint of riser because of the comprehensive action of working load, environmental load, movement of platform, whirl of drilling string and so on. Especially with the increase of water depth, the drill string will vibrate severely when the speed reaches the critical value, which easily causes the dynamic failure of the drill string. Based on rotor dynamics theory, this paper has established the mechanics calculation model of nonlinear support drill string without riser to analyze the influences of bearing stiffness, water depth and section size of drill string on critical speed of drilling string. The result shows that critical speed of whirl of drilling string is decreased with the increase of wall thickness; critical speed of whirl of drilling string is decreased with the increase of the length of string in water; critical speed of whirl of drilling string is increased with the increase of the stiffness of bearing. According to the results, reasonable speed of drilling string has been given to prevent resonance. The results can be used as reference for deepwater drilling operations without riser.

Photovoltaic String Sizing Using Site-Specific Modeling

One key design decision for photovoltaic (PV) power plants is to select the number of PV modules connected in series, also called the string size. Longer strings typically lower total system costs, but the string size must still meet relevant electrical standards to ensure that the maximum system voltage remains less than the design voltage. Traditional methods calculate string size using the temperature coefficient of open-circuit voltage assuming that the coldest expected temperature occurs simultaneously with a full-sun irradiance of ${\text{1000}}\,{\text{W/m}}^{\text{2}}$ . Here, we demonstrate that this traditional method is unnecessarily conservative, resulting in a string size $\sim$ 10% shorter than necessary to maintain system voltage within limits. Instead, engineers may determine string size by modeling open-circuit voltage over time using historical weather data, a method consistent with the 2017 National Electric Code. For bifacial systems, we derive a simple additive term that predicts the additional voltage rise. We demonstrate that this site-specific modeling procedure predicts open-circuit voltages in close agreement with data from field measurements. We further perform a comprehensive sensitivity analysis to identify an appropriate safety factor. By using site-specific modeling instead of traditional methods, we estimate a $\sim$ 1.2% reduction in levelized cost of electricity, a significant improvement to PV power plant economics. The method is provided as an easy-to-use web tool and as an open-source Python package.

Realistic Diagnostics to Evaluate Imbalance and Heterogeneity of Lithium-Ion Battery Modules

Lithium-ion battery (LIB) packs for the electric drive vehicles (EDVs) consist of hundreds to thousands of unit cells. These multitudes of cells are arranged in various series-parallel configurations to build the complete pack. Ensuring the safety of these complicated packs in a myriad of operating conditions (including abuse conditions such as extreme fast charging, collisions, etc.) is a crucial requirement for the overall safety of the EDVs and is an open and evolving field of research. Pack safety undoubtedly relies on the inherent safety and abuse tolerance of the unit cell. However, the combination of many cells in packs introduces new and sometimes unknown pack dynamics, which could compromise the overall pack safety. Thus, advanced diagnostics and intelligent algorithms involving information from multiple levels, e.g., unit cells to modules to packs, are required to ensure the overall safety of the battery pack.Many researchers have used the electrochemical impedance spectroscopy (EIS) to estimate the state of charge (SOC) and state of health (SOH) of batteries, notably in single cell settings [1-4]. The form factor and measurement time of conventional full spectra EIS, however, makes it unsuitable as an onboard diagnostic tool. The impedance measurement box (IMB) can generate the impedance spectra within 0.1-1638.4Hz in ten seconds [5-6]. This opens the possibility of using full frequency impedance spectra as an online diagnostic tool for battery SOC, SOH and state of stability estimation. Incremental capacity (IC) or dQ.dV-1 is another diagnostic method and has been primarily used for single cell’s aging and SOH estimation [7-8]. Full pack’s IC analysis is complex and challenging due to a multitude of intrinsic (material, manufacturing process, etc.) and extrinsic (environment, non-uniform current, etc.) uncertainties [9, 10] and has not been looked at extensively.This paper includes experimental case studies to investigate whether rapid impedance and dQ.dV-1 diagnostic methods could identify and quantify different abnormal conditions in modules. Realistic in-vehicle abnormal conditions such as localized self-discharge and non-uniform aging were evaluated using automotive grade 16 Ah gr/NMC in series (up to 10S1P) and parallel (up to 1S4P) module settings at different SOCs. Understanding imbalance associated with localized self-discharge is crucial for long-term safety, especially for an aggressively used vehicle and following crash conditions [8]. On the other hand, cell-to-cell variability is a key concern for aged batteries as it may precede potential fault associated shorts from fast charging, or localized elevated temperature.The analyses structure includes characterizing the measurement uncertainty (noise behavior) for each of the case study, followed by identifying distinct signals related to abnormal conditions above the noise floor. Baseline conditions with no abnormality were used for all the cases evaluated for detection signal identification. The impedance-based diagnostic method found to be sensitive to the string size and frequency range. For instance, the detection signal for the local imbalance is found to be more sensitive to the lower frequency, thus more likely to be detected. On the other hand, a higher frequency is suitable for cell-to-cell heterogeneity detection. Both the dQ.dV-1 and impedance-based diagnostic methods (with existing accuracy and precision) were sensitive to identify and detect series string's abnormality but struggled to detect parallel string issues.

Advanced diagnostics to evaluate heterogeneity in lithium-ion battery modules

Abstract Battery packs for electric and stationary applications experience varied operating conditions, including abuse—e.g., fast charging, overcharging, thermal, vibration, shock, etc.—throughout their lifetimes. Innovative diagnostic tools and algorithms that go beyond single cells and deal with modules and packs are essential for early detection of off-normal issues. High-resolution tools with known detection limits are key to developing appropriate mitigation strategies. With the advent of rapid impedance spectroscopy that can generate a broadband impedance spectrum in ∼10 s, the case for impedance-based diagnostics that can be readily aligned with other methods, such as incremental capacity or dQ.dV−1, has become promising. This study used the aforementioned diagnostic methods to identify realistic in-vehicle battery abnormalities (e.g., localized self-discharge and non-uniform aging), in series (up to 10S) and parallel (4P) strings, using 16 Ah graphite/NMC cells. The impedance-based diagnostic is found to be sensitive to the string size and state. Depending on the type of abnormality, detection frequency varied. The dQ.dV−1 method showed the potential to detect long-term aging-related heterogeneity in modules. In general, both the impedance and dQ.dV−1 methods were able to detect series strings’ abnormalities, but struggled to find those issues within parallel modules.

On the size of the smallest alphabet for Lyndon trees

We consider the problem of reverse-engineering the Lyndon tree, i.e., given a full binary ordered tree T with n leaves as input, we are to compute a string w of length n of which Lyndon tree is isomorphic to the input tree T. Hereby we call such a string a solution string. Although the problem is easily solvable in linear time for binary alphabets and unbounded-size alphabets, it is not known how to efficiently find the smallest alphabet size for a solution string. In this paper, we show several new observations concerning this problem. Namely, we show that: 1) For any positive integer n, there exists a full binary ordered tree T with n leaves, s.t. the smallest alphabet size of a solution string for T is ⌊n2⌋+1. 2) For any full binary ordered tree T with n leaves, there exists a solution string w over an alphabet of size at most ⌊n2⌋+1. 3) For any full binary ordered tree T, there exists a solution string w over an alphabet of size at most h+1, where h is the height of T. 4) For any complete binary ordered tree T with 2k leaves, there exists a solution string w over an alphabet of size at most 4.

A comparative investigation on in-situ and laboratory standard test of the potential induced degradation of crystalline silicon photovoltaic modules

Abstract Potential induced degradation (PID) is one of the genuinely critical concerns of a sustainable power generation from a PV system. Generally, the PID behavior of a PV module is tested in the laboratory according to the IEC standard before installation into a plant. On the other hand, an electroluminescence imaging is a reliable technique to identify the different types of PV cell defects which cause the degradation of the PV modules. The aim of this research is to investigate the PID behavior of similar PV modules in both the real on-site test and the laboratory standard test conditions. This will facilitate the outcome of the tangible indoor PID test results with more ease and reliability. It has been observed from the EL images of the on-site degraded PV module that a performance degradation happens due to different types of PV cell defects, such as, localized shunting, cracks, front contact grid interruptions, etc. The maximum power versus EL mean intensity shows a linear relationship which predicts the quantitative performance analysis of a PV module from an EL imaging process. The PID of a PV module has been found in a negative voltage stress condition in both the on-site and the laboratory tests. The shunt resistance gradually decreases as a consequence of the negative voltage stress only. The on-site degradation levels of the Pmax, Voc, Isc, and FF are 46.5, 7.15, 30.4, and 17.35% respectively after a duration of nearly 11 years of a negative voltage stress generated from a 240 V string size. In a laboratory PID test, the Pmax, Voc, Isc, and FF are degraded due to a negative voltage stress with a value of 6.83%, 1.9%, 1.5%, and 3.5% respectively.

Investigation of the potential induced degradation of on-site aged polycrystalline PV modules operating in Malaysia

On-site investigation of PID behavior of PV module has been carried out under typical Malaysian climate. A quantitative degradation measurement process of PV module through EL imaging has been introduced. PID has been observed only for the negative voltage stress in this p-type polycrystalline Si PV module. The negative end PV module degrades 42% due to 9 years field aging under a negative voltage stress from the 240 V string size. While positive end PV module is degraded near about 17% over the same period due to normal field aging. Shunt resistance of negative-end module has been found 75% lower than that of the positive-end module. Module crack propagation is found to be accelerated due to onsite cyclic high voltage stress. PID at higher string size has been estimated from the leakage current of brand new same PV module. The estimated PID of PV module under 600 V stress is 72.84%.

Working String Axial Force in L-Shaped Oil Well

The bottom section of a L-shaped well warps upward, so it is a different type against normal horizontal well and should be designed carefully. With regard to the peculiar geometry of borehole, in this paper, the working string axial force is calculated and the feasibility of string running in and out the hole is discussed. String buckling and bottom sticking are considered. This papers suggested that the tip-tilted section makes string tripping in more difficult, while makes tripping out easier; during tripping out, the ratio between the increase of hook load and sticking force is a certain value; string buckling begins at the kick of point firstly and at the target secondly during tripping in; the friction caused by buckling in the L-shaped well is more obvious than in normal horizontal well; the smaller the string size is, the shorter the largest extending length will be.

Xkcd-repeats: A new taxonomy of repeats defined by their context diversity

The context in which a substring appears is an important notion to identify – for example – its semantic meaning. However, existing definitions from stringology fail to model the context explicitly. We introduce here xkcd-repeats, a new family of repeats characterized by the number of different symbols at the left and right of their occurrences. These repeats include as special extreme cases the well-known classes of maximal and super-maximal repeats.We give sufficient and necessary condition to bound their number linearly in the size of the original string, and show an optimal algorithm that computes them in linear time – given a suffix array –, independent of the size of the alphabet, as well as two other algorithms that are faster in practice.We extend this in two ways: first we show how to generalize the notion of context. Instead of reducing it to the single symbol before and after an occurrence, we propose the notion of unbounded context, while keeping linear representation and computing time. Secondly, we provide a general framework which allows to compute these (and other) repeats incrementally; opening the door to streaming application.

Decision making for choosing the optimum production scenario for a sector model of South Pars gas field based on single well modeling

Optimum production from a hydrocarbon field takes place when technical parameters are optimized with respect to the operational and economic constraints. Well control parameters have an important role in making decisions for choosing efficient production scenario in a reservoir. Among the economical constraints cost of drilling and completion of wells, transportation and refinery costs and price of oil and gas can be named. In this paper, using single well model, the design of experiments and multi criteria decision making, determination of optimum production scenario based on a sector of South Pars gas field is addressed. Flow rate, well spacing, minimum wellhead pressure, production string size, deviation of wells and type of stimulation are decision parameters that are considered in this study. Economic indices chosen for economic analysis are net present value, internal rate of return and plateau time. First using the design of experiments and response surface methodology, proxy models are generated to predict economic indices for production scenarios and after validation of them, they are used for economic analysis and choosing the best scenario based on multi-criteria decision making.