The mechanism of erosion of a riverbank is not easy to analyze and each sediment particle is under influence of number of forces. Among all these forces, force of cohesion between the particles plays a very dominant a...The mechanism of erosion of a riverbank is not easy to analyze and each sediment particle is under influence of number of forces. Among all these forces, force of cohesion between the particles plays a very dominant and significant role, and, till date, not much progress has been made to analyze this force in a deterministic manner. A particle is bound to its neighboring particles under this force of cohesion. In this paper, the analysis of forces acting on a particle on a riverbank has been made with a model called the Truncated Pyramid Model. A particle requires a certain velocity to escape from the riverbank and determination of the escape velocity can pave the way for finding out other parameters like entrainment rate, erosion coefficient and so on. Calculation and estimation of riverbank erosion rate is an important aspect of river basin management. In this paper it has been shown that the escape velocity is dependent on certain micro-level parameters like inter-particle distance and volume of the water bridge between two adjacent particles. Also, for saline water the particle requires less velocity to escape compared to the pure-water scenario. The findings of the present paper exactly fall in line with the results of another paper where the researchers showed that cohesive force between the particles decreases as water turns from pure to impure.展开更多
An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Techniqu...An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared to the original data and traditional SMOTE. The proposed method (NR-Clustering SMOTE) improves accuracy by 15.34% on the Pima dataset and 20.96% on the Haberman dataset compared to SMOTE-LOF. Compared to Radius-SMOTE, this method increases accuracy by 3.16% on the Pima dataset and 13.24% on the Haberman dataset. Meanwhile, compared to RN-SMOTE, the accuracy improvement reaches 15.56% on the Pima dataset and 19.84% on the Haberman dataset. This research result implies that the proposed method experiences consistent performance improvement compared to traditional SMOTE and its latest variants, such as SMOTE-LOF, Radius-SMOTE, and RN-SMOTE, in solving imbalanced health data with class binaries.展开更多
Both acceleration and pseudo-acceleration response spectra play important roles in structural seismic design.However,only one of them is generally provided in most seismic codes.Therefore,many studies have attempted t...Both acceleration and pseudo-acceleration response spectra play important roles in structural seismic design.However,only one of them is generally provided in most seismic codes.Therefore,many studies have attempted to develop conversion models between the acceleration response spectrum(SA)and the pseudo-acceleration response spectrum(PSA).Our previous studies found that the relationship between SA and PSA is affected by magnitude,distance,and site class.Subsequently,we developed an SA/PSA model incorporating these effects.However,this model is suitable for cases with small and moderate magnitudes and its accuracy is not good enough for cases with large magnitudes.This paper aims to develop an efficient SA/PSA model by considering influences of magnitude,distance,and site class,which can be applied to cases not only with small or moderate magnitudes but also with large ones.For this purpose,regression analyses were conducted using 16,660 horizontal seismic records with a wider range of magnitude.The magnitude of these seismic records varies from 4 to 9 and the distances vary from 10 to 200 km.These ground motions were recorded at 338 stations covering four site classes.By comparing them with existing models,it was found that the proposed model shows better accuracy for cases with any magnitudes,distances,and site classes considered in this study.展开更多
Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamen...Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamental importance in both science and technology.We describe a ranging scheme based on chirped pulse interferometry.In contrast to the traditional spectral interferometry,the local oscillator is strongly chirped which is able to meet the measurement pulses at arbitrary distances,and therefore,the dead zones can be removed.The distances can be precisely determined via two measurement steps based on the time-of-flight method and synthetic wavelength interferometry,respectively.To overcome the speed limitation of the optical spectrum analyzer,the spectrograms are stretched and detected by a fast photodetector and oscilloscope and consequently mapped into the time domain in real time.The experimental results indicate that the measurement uncertainty can be well within±2μm,compared with the reference distance meter.The Allan deviation can reach 0.4μm at 4 ns averaging time and 25 nm at 1μs and can achieve 2 nm at 100μs averaging time.We also measured a spinning disk with grooves of different depths to verify the measurement speed,and the results show that the grooves with about 150 m∕s line speed can be clearly captured.Our method provides a unique combination of non-dead zones,ultrafast measurement speed,high precision and accuracy,large ambiguity range,and only one single comb source.This system could offer a powerful solution for field measurements in practical applications in the future.展开更多
This study aims to investigate the minimum required seismic gap distance based on the avoidance of shear failure for reinforced concrete(RC)buildings with potential floor-to-column pounding.Twenty different adjacent m...This study aims to investigate the minimum required seismic gap distance based on the avoidance of shear failure for reinforced concrete(RC)buildings with potential floor-to-column pounding.Twenty different adjacent models reflecting low and mid-rise buildings were created.Dynamic analyses were performed by selecting 11 earthquake record pairs compatible with the Turkish Building Earthquake Code(TBEC-2018).Two different cases were considered to determine the minimum required seismic gap distance.In the first case(named as Case-1),the gap distances between neighboring buildings were determined to avoid collisions during each acceleration record.The required distances calculated from the analyses were compared with the minimum seismic gap requirements of the TBEC-2018.The outcomes indicate that theαcoefficient recommended in TBEC-2018 for adjacent buildings with a potential floor-to-column pounding is sufficient for adjacent buildings with a period ratio of 1 to 1.5.The gap distances in the first case were then reduced by an iterative process to determine the distance at which the shear demand equals the shear strength(named as Case-2).The calculated gap distances to prevent shear failure(Case-2)are approximately 6%to 19%lower than the distances determined for avoidance of pounding(Case-1).展开更多
A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which...A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which have nice spectral properties.This article mainly studies the conjecture proposed by Shijin et al.on the distance compatibility of the direct product of signed graphs,and provides necessary and sufficient conditions for the distance compatibility of the direct product of signed graphs.Some further questions regarding distance compatibility are also posed.展开更多
The distance distributions between two site-specifically anchored spin labels in a protein,measured by pulsed electron-electron double resonance(PELDOR or DEER),provide rich sources of structural and conformational re...The distance distributions between two site-specifically anchored spin labels in a protein,measured by pulsed electron-electron double resonance(PELDOR or DEER),provide rich sources of structural and conformational restraints on the proteins or their complexes.The rigid connection of the nitroxide spin label to the protein improves the accuracy and precision of distance measurement.We report a new spin labelling approach by formation of thioester bond between nitroxide(NO)spin label,NOAI(NO spin labels activated by acetylimidazole),and a protein thiol,and this spin labeling method has demonstrated high performance in DEER distance measurement on proteins.The results showed that NOAI has shorter connection to the protein ligation site than 2,2,5,5-tetramethyl-pyrroline-1-oxyl methanethiosulfonate(MTSL)and 3-maleimido-proxyl(M-Prox)in the respective protein conjugate and produces narrower distance distributions for the tested proteins including ubiquitin(Ub),immunoglobulin-binding b1 domain of streptococcal protein G(GB1),and second mitochondria-derived activator of caspases(Smac).The NOAI protein conjugate connected by a thioester bond is resistant to reducing reagent and offers highfidelity DEER distance measurements in cell lysates.展开更多
This study presents an efficient feature selection method based on the Gower distance to enhance the accuracy and efficiency of standard classifiers on high-dimensional medical datasets.High-dimensional data poses sig...This study presents an efficient feature selection method based on the Gower distance to enhance the accuracy and efficiency of standard classifiers on high-dimensional medical datasets.High-dimensional data poses significant challenges for traditional classifiers due to feature redundancy or being irrelevant.The proposed method addresses these challenges by partitioning the dataset into blocks,calculating the Gower distance within each block,and selecting features based on their average similarity.Technically,the Gower distance normalizes the absolute difference between numerical features,ensuring that each feature contributes equally to the distance calculation.This normalization prevents features with larger scales from overshadowing those with smaller scales.This process facilitates the identification of features that exhibit high harmony and are the most relevant for classification.The proposed feature selection strategy significantly reduces dimensionality,retains the most relevant features,and improves model performance.Experimental results show that the accuracy for the classifiers including k-nearest neighbors(KNN),naive Bayes(NB),decision tree(DT),random forest(RF),support vector machine(SVM),and logistic regression(LR)was increased by 4.38%-7.02%.Besides,the reduction in the feature set size contributes to a considerable decrease in computational complexity and thus faster diagnosis speed.The execution time was averagely reduced by 77.82%for all samples and 76.45%for one sample.These results demonstrate that the proposed feature selection method shows enhanced performance on both prediction accuracy and diagnostic speed,making it a promising tool for real-time clinical decision-making and improving patient care outcomes.展开更多
Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the spe...Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.展开更多
This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar ...This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.展开更多
This paper aims to elucidate the seismic characteristics of the Three Gorges Reservoir area after impoundment and investigate the seismic source migration.Based on the seismic data analysis from the Badong segment in ...This paper aims to elucidate the seismic characteristics of the Three Gorges Reservoir area after impoundment and investigate the seismic source migration.Based on the seismic data analysis from the Badong segment in the Three Gorges Reservoir area,we assessed the local temporal and spatial variations in the frequent earthquakes.Correlation analysis was conducted to investigate the relationship between changes in reservoir water levels and the occurrence of reservoir-induced earthquakes.Additionally,we examined the regularity of earthquake occurrences at the exact location during different periods.Based on the fault mechanics principles,a formula was derived to estimate the length of open and wing-shaped rupture at the hypocenter under the influence of pore or excess pore water pressure.The results reveal that reservoir-induced seismicity demonstrates short-term cycles characterized by alternating"active periods"and"quiet periods,"as well as long-term cycles with the combined periods.The probability of earthquakes occurring within one year at the epicentre is relatively high and decreases after four years.The derived formula can be utilized to estimate the seismic migration distance at the epicentre in the short term.These research findings provide valuable insights for analyzing the regularity of reservoir-induced earthquake activities and understanding the mechanism of seismic source migration.展开更多
This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy ess...This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.展开更多
1 Exploring Transylvania,with its promises of ancient buildings,wall‑guarded churches and fantastic castles,is a genuine treat for nature lovers,but since October 2022,a new social project,Via Transilvanica,aims to in...1 Exploring Transylvania,with its promises of ancient buildings,wall‑guarded churches and fantastic castles,is a genuine treat for nature lovers,but since October 2022,a new social project,Via Transilvanica,aims to invite active travelers to explore the essence of Romanian culture.展开更多
In this paper,cosmic distance duality relation(CDDR)is probed without considering any background cosmological model.The only a priori assumption is that the Universe is described by the Friedmann–Lema?tre–Robertson...In this paper,cosmic distance duality relation(CDDR)is probed without considering any background cosmological model.The only a priori assumption is that the Universe is described by the Friedmann–Lema?tre–Robertson–Walker(FLRW)metric.The strong gravitational lensing data is used to construct the dimensionless comoving distance function d(z)and latest type Ia supernovae Pantheon+data is used to estimate luminosity distances at the corresponding redshifts z.Using the distance sum rule along null geodesics of the FLRW metric,the CDDR violation is probed in both flat and non-flat spacetime by considering two parametrizations forη(z),the function generally used to probe the possible deviations from CDDR.The results show that CDDR is compatible with the observations at a very high level of confidence for linear parametrization in a flat Universe.In a non-flat Universe too,CDDR is valid within the 1σconfidence interval with a mild dependence ofηon the curvature density parameterΩK.The results for nonlinear parametrization also show no significant deviation from CDDR.展开更多
Virtual coupling(VC) is an emerging technology for addressing the shortage of rail transportation capacity. As a crucial enabling technology, the VC-specific acquisition of train information, especially train followin...Virtual coupling(VC) is an emerging technology for addressing the shortage of rail transportation capacity. As a crucial enabling technology, the VC-specific acquisition of train information, especially train following distance(TFD), is underdeveloped.In this paper, a novel method is proposed to acquire real-time TFD by analyzing the vibration response of the front and following trains, during which only onboard accelerometers and speedometers are required. In contrast to the traditional arts of train positioning, this method targets a relative position between two adjacent trains in VC operation, rather than the global positions of the trains. For this purpose, an adaptive system containing three strategies is designed to cope with possible adverse factors in train operation. A vehicle dynamics simulation of a heavy-haul railway is implemented for the evaluation of feasibility and performance. Furthermore, a validation is conducted using a set of data measured from in-service Chinese high-speed trains. The results indicate the method achieves satisfactory estimation accuracy using both simulated and actual data. It has favorable adaptability to various uncertainties possibly encountered in train operation. Additionally, the method is preliminarily proven to adapt to different locomotive types and even different rail transportation modes. In general, such a method with good performance, low-cost, and easy implementation is promising to apply.展开更多
Coal mine underground reservoir(CMUR) technology mitigates water scarcity in China's coal-rich western regions but lacks tailored solutions for steeply inclined coal seams.This study develops a novel framework of ...Coal mine underground reservoir(CMUR) technology mitigates water scarcity in China's coal-rich western regions but lacks tailored solutions for steeply inclined coal seams.This study develops a novel framework of steeply inclined coal mine underground reservoirs(SICMUR),which is a paradigm shift from conventional CMUR that the coal seam itself serves as the reservoir floor,challenging conventional designs due to depth-dependent permeability and mechanical constraints.Triaxial mechanical-seepage tests on Xinjiang Wudong coal samples(100,200,300 m depths) revealed a 3.5 MPa triaxial strength increase per 100 m depth and a 58-fold post-peak permeability surge at 300 versus 100 m.Similar model simulations revealed mining-induced stress redistribution and significant deformation effects,particularly subsidence and water-conducting fractures during lower coal seam mining.Results indicate a minimum 40 m safety distance between reservoirs and lower coal seams.Critical construction parameters were investigated for Wudong mine SICMUR as collapse zone heights(9.9–12.31 m) and waterconducting fracture zone heights(31.96–37.40 m).This work systematically bridges SICMUR concepts to field implementation,offering a framework for water preservation in steeply inclined mining while addressing safety concerns,providing a new approach for water reservation in steeply inclined coal mining.展开更多
When high-temperature steam is used as a medium to pyrolyze organic-rich shale,water steam not only acts as heat transfer but also participates in the chemical reaction of organic matter pyrolysis,thus affecting the g...When high-temperature steam is used as a medium to pyrolyze organic-rich shale,water steam not only acts as heat transfer but also participates in the chemical reaction of organic matter pyrolysis,thus affecting the generation law and release characteristics of gas products.In this study,based on a long-distance reaction system of organic-rich shale pyrolysis via steam injection,the effects of steam temperature and reaction distance on gas product composition are analyzed in depth and compared with other pyrolysis processes.The advantages of organic-rich shale pyrolysis via steam injection are then evaluated.The volume concentration of hydrogen in the gas product obtained via the steam injection pyrolysis of organic-rich shale is the highest,which is more than 60%.The hydrogen content increases as the reaction distance is extended;however,the rate of increase changes gradually.Increasing the reaction distance from 800 to 4000 mm increases the hydrogen content from 34.91%to 69.68%and from 63.13%to 78.61%when the steam temperature is 500℃ and 555℃,respectively.However,the higher the heat injection temperature,the smaller the reaction distance required to form a high concentration hydrogen pyrolysis environment(hydrogen concentration>60%).When the steam pyrolysis temperature is increased from 500℃ to 555℃,the reaction distance required to form a high concentration of hydrogen is reduced from 3800 to 800 mm.Compared with the direct retorting process,the volume concentration of hydrogen obtained from high-temperature steam pyrolysis of organic-rich shale is 8.82 and 10.72 times that of the commonly used Fushun and Kivite furnaces,respectively.The pyrolysis of organic-rich shale via steam injection is a pyrolysis process in a hydrogen-rich environment.展开更多
This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for ar...This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for arrhythmia detection.The proposed classifier leverages the Chi-square distance as a primary metric,providing a specialized and original approach for precise arrhythmia detection.To optimize feature selection and refine the classifier’s performance,particle swarm optimization(PSO)is integrated with the Chi-square distance as a fitness function.This synergistic integration enhances the classifier’s capabilities,resulting in a substantial improvement in accuracy for arrhythmia detection.Experimental results demonstrate the efficacy of the proposed method,achieving a noteworthy accuracy rate of 98% with PSO,higher than 89% achieved without any previous optimization.The classifier outperforms machine learning(ML)and deep learning(DL)techniques,underscoring its reliability and superiority in the realm of arrhythmia classification.The promising results render it an effective method to support both academic and medical communities,offering an advanced and precise solution for arrhythmia detection in electrocardiogram(ECG)data.展开更多
In this article,multiple attribute decision-making problems are solved using the vague normal set(VNS).It is possible to generalize the vague set(VS)and q-rung fuzzy set(FS)into the q-rung vague set(VS).A log q-rung n...In this article,multiple attribute decision-making problems are solved using the vague normal set(VNS).It is possible to generalize the vague set(VS)and q-rung fuzzy set(FS)into the q-rung vague set(VS).A log q-rung normal vague weighted averaging(log q-rung NVWA),a log q-rung normal vague weighted geometric(log q-rung NVWG),a log generalized q-rung normal vague weighted averaging(log Gq-rung NVWA),and a log generalized q-rungnormal vagueweightedgeometric(logGq-rungNVWG)operator are discussed in this article.Adescription is provided of the scoring function,accuracy function and operational laws of the log q-rung VS.The algorithms underlying these functions are also described.A numerical example is provided to extend the Euclidean distance and the Humming distance.Additionally,idempotency,boundedness,commutativity,and monotonicity of the log q-rung VS are examined as they facilitate recognizing the optimal alternative more quickly and help clarify conceptualization.We chose five anemia patients with four types of symptoms including seizures,emotional shock or hysteria,brain cause,and high fever,who had either retrograde amnesia,anterograde amnesia,transient global amnesia,post-traumatic amnesia,or infantile amnesia.Natural numbers q are used to express the results of the models.To demonstrate the effectiveness and accuracy of the models we are investigating,we compare several existing models with those that have been developed.展开更多
Let G be a strongly connected directed weighted graph with vertex set{v_(1),v_(2),...,v_(n)},in which each edge e is assigned with an arbitrary nonzero weight w(e).For any two vertices v_i,v_(j )of G,the distance d_(i...Let G be a strongly connected directed weighted graph with vertex set{v_(1),v_(2),...,v_(n)},in which each edge e is assigned with an arbitrary nonzero weight w(e).For any two vertices v_i,v_(j )of G,the distance d_(ij )from v_(i)to v_(j)is defined as dij=P∈P(v_(i),v_(j))min∑w(e) where P(v_(i),v_(j)) denotes the set consisting of all the directed paths from v_(i)to v_(j)in G.Given a nonzero indeterminant q,following the definitions from Yan and Yeh (Adv.Appl.Math.,2007),and Bapat et al.(Linear Algebra Appl.,2006),one can define the exponential distance matrix of G as F^(q)_(G)=(q^(dij))_(n×n),and define the q-distance matrix of G as D_(G)^(q)=(d_(ij)^(q))_(n×n)with d_(ij)^(q)={1-q^(dij)/1-q,if q≠1,dij,if q=1,extending the original definitions only for the undirected unweighted connected graphs.One of the remarkable results about the distance matrices of graphs is due to the Graham-HoffmanHosoya theorem (J.Graph Theory,1977).In this paper,we present some Graham-HoffmanHosoya type theorems for the exponential distance matrix F_(G)^(q)and q-distance matrix D_(G)^(q),extending all the known Graham-Hoffman-Hosoya type theorems.展开更多
文摘The mechanism of erosion of a riverbank is not easy to analyze and each sediment particle is under influence of number of forces. Among all these forces, force of cohesion between the particles plays a very dominant and significant role, and, till date, not much progress has been made to analyze this force in a deterministic manner. A particle is bound to its neighboring particles under this force of cohesion. In this paper, the analysis of forces acting on a particle on a riverbank has been made with a model called the Truncated Pyramid Model. A particle requires a certain velocity to escape from the riverbank and determination of the escape velocity can pave the way for finding out other parameters like entrainment rate, erosion coefficient and so on. Calculation and estimation of riverbank erosion rate is an important aspect of river basin management. In this paper it has been shown that the escape velocity is dependent on certain micro-level parameters like inter-particle distance and volume of the water bridge between two adjacent particles. Also, for saline water the particle requires less velocity to escape compared to the pure-water scenario. The findings of the present paper exactly fall in line with the results of another paper where the researchers showed that cohesive force between the particles decreases as water turns from pure to impure.
基金funded by Universitas Negeri Malang,contract number 4.4.841/UN32.14.1/LT/2024.
文摘An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared to the original data and traditional SMOTE. The proposed method (NR-Clustering SMOTE) improves accuracy by 15.34% on the Pima dataset and 20.96% on the Haberman dataset compared to SMOTE-LOF. Compared to Radius-SMOTE, this method increases accuracy by 3.16% on the Pima dataset and 13.24% on the Haberman dataset. Meanwhile, compared to RN-SMOTE, the accuracy improvement reaches 15.56% on the Pima dataset and 19.84% on the Haberman dataset. This research result implies that the proposed method experiences consistent performance improvement compared to traditional SMOTE and its latest variants, such as SMOTE-LOF, Radius-SMOTE, and RN-SMOTE, in solving imbalanced health data with class binaries.
基金National Natural Science Foundation of China under Grant No.52278135。
文摘Both acceleration and pseudo-acceleration response spectra play important roles in structural seismic design.However,only one of them is generally provided in most seismic codes.Therefore,many studies have attempted to develop conversion models between the acceleration response spectrum(SA)and the pseudo-acceleration response spectrum(PSA).Our previous studies found that the relationship between SA and PSA is affected by magnitude,distance,and site class.Subsequently,we developed an SA/PSA model incorporating these effects.However,this model is suitable for cases with small and moderate magnitudes and its accuracy is not good enough for cases with large magnitudes.This paper aims to develop an efficient SA/PSA model by considering influences of magnitude,distance,and site class,which can be applied to cases not only with small or moderate magnitudes but also with large ones.For this purpose,regression analyses were conducted using 16,660 horizontal seismic records with a wider range of magnitude.The magnitude of these seismic records varies from 4 to 9 and the distances vary from 10 to 200 km.These ground motions were recorded at 338 stations covering four site classes.By comparing them with existing models,it was found that the proposed model shows better accuracy for cases with any magnitudes,distances,and site classes considered in this study.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC2204601)the National Natural Science Foundation of China(Grant Nos.11925503 and 12275093)+1 种基金the Natural Science Foundation of Hubei Province(Grant No.2021CFB019)the State Key Laboratory of Applied Optics(Grant No.SKLAO2022001A10).
文摘Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamental importance in both science and technology.We describe a ranging scheme based on chirped pulse interferometry.In contrast to the traditional spectral interferometry,the local oscillator is strongly chirped which is able to meet the measurement pulses at arbitrary distances,and therefore,the dead zones can be removed.The distances can be precisely determined via two measurement steps based on the time-of-flight method and synthetic wavelength interferometry,respectively.To overcome the speed limitation of the optical spectrum analyzer,the spectrograms are stretched and detected by a fast photodetector and oscilloscope and consequently mapped into the time domain in real time.The experimental results indicate that the measurement uncertainty can be well within±2μm,compared with the reference distance meter.The Allan deviation can reach 0.4μm at 4 ns averaging time and 25 nm at 1μs and can achieve 2 nm at 100μs averaging time.We also measured a spinning disk with grooves of different depths to verify the measurement speed,and the results show that the grooves with about 150 m∕s line speed can be clearly captured.Our method provides a unique combination of non-dead zones,ultrafast measurement speed,high precision and accuracy,large ambiguity range,and only one single comb source.This system could offer a powerful solution for field measurements in practical applications in the future.
文摘This study aims to investigate the minimum required seismic gap distance based on the avoidance of shear failure for reinforced concrete(RC)buildings with potential floor-to-column pounding.Twenty different adjacent models reflecting low and mid-rise buildings were created.Dynamic analyses were performed by selecting 11 earthquake record pairs compatible with the Turkish Building Earthquake Code(TBEC-2018).Two different cases were considered to determine the minimum required seismic gap distance.In the first case(named as Case-1),the gap distances between neighboring buildings were determined to avoid collisions during each acceleration record.The required distances calculated from the analyses were compared with the minimum seismic gap requirements of the TBEC-2018.The outcomes indicate that theαcoefficient recommended in TBEC-2018 for adjacent buildings with a potential floor-to-column pounding is sufficient for adjacent buildings with a period ratio of 1 to 1.5.The gap distances in the first case were then reduced by an iterative process to determine the distance at which the shear demand equals the shear strength(named as Case-2).The calculated gap distances to prevent shear failure(Case-2)are approximately 6%to 19%lower than the distances determined for avoidance of pounding(Case-1).
基金Supported by the National Natural Science Foundation of China(Grant No.12071260)。
文摘A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which have nice spectral properties.This article mainly studies the conjecture proposed by Shijin et al.on the distance compatibility of the direct product of signed graphs,and provides necessary and sufficient conditions for the distance compatibility of the direct product of signed graphs.Some further questions regarding distance compatibility are also posed.
基金supported by National Natural Science Foundation of China(22161142018,21991081,22177056,and 22174074)the Ministry of Science and Technology of China(2021YFA1600304).
文摘The distance distributions between two site-specifically anchored spin labels in a protein,measured by pulsed electron-electron double resonance(PELDOR or DEER),provide rich sources of structural and conformational restraints on the proteins or their complexes.The rigid connection of the nitroxide spin label to the protein improves the accuracy and precision of distance measurement.We report a new spin labelling approach by formation of thioester bond between nitroxide(NO)spin label,NOAI(NO spin labels activated by acetylimidazole),and a protein thiol,and this spin labeling method has demonstrated high performance in DEER distance measurement on proteins.The results showed that NOAI has shorter connection to the protein ligation site than 2,2,5,5-tetramethyl-pyrroline-1-oxyl methanethiosulfonate(MTSL)and 3-maleimido-proxyl(M-Prox)in the respective protein conjugate and produces narrower distance distributions for the tested proteins including ubiquitin(Ub),immunoglobulin-binding b1 domain of streptococcal protein G(GB1),and second mitochondria-derived activator of caspases(Smac).The NOAI protein conjugate connected by a thioester bond is resistant to reducing reagent and offers highfidelity DEER distance measurements in cell lysates.
文摘This study presents an efficient feature selection method based on the Gower distance to enhance the accuracy and efficiency of standard classifiers on high-dimensional medical datasets.High-dimensional data poses significant challenges for traditional classifiers due to feature redundancy or being irrelevant.The proposed method addresses these challenges by partitioning the dataset into blocks,calculating the Gower distance within each block,and selecting features based on their average similarity.Technically,the Gower distance normalizes the absolute difference between numerical features,ensuring that each feature contributes equally to the distance calculation.This normalization prevents features with larger scales from overshadowing those with smaller scales.This process facilitates the identification of features that exhibit high harmony and are the most relevant for classification.The proposed feature selection strategy significantly reduces dimensionality,retains the most relevant features,and improves model performance.Experimental results show that the accuracy for the classifiers including k-nearest neighbors(KNN),naive Bayes(NB),decision tree(DT),random forest(RF),support vector machine(SVM),and logistic regression(LR)was increased by 4.38%-7.02%.Besides,the reduction in the feature set size contributes to a considerable decrease in computational complexity and thus faster diagnosis speed.The execution time was averagely reduced by 77.82%for all samples and 76.45%for one sample.These results demonstrate that the proposed feature selection method shows enhanced performance on both prediction accuracy and diagnostic speed,making it a promising tool for real-time clinical decision-making and improving patient care outcomes.
基金Supported by the National Natural Science Foundation of China(Grant Nos.1177117812171198)+2 种基金the Science and Technology Development Program of Jilin Province(Grant No.20210101467JC)the Technology Program of Jilin Educational Department During the“14th Five-Year”Plan Period(Grant No.JJKH20241239KJ)the Fundamental Research Funds for the Central Universities.
文摘Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.
基金supported in part by the National Nat-ural Science Foundation of China(No.51977012,No.52307080).
文摘This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.
基金supported by the Open Research Fund of Key Laboratory of Geological Hazards on Three Gorges Reservoir Area of China Three Gorges University,the Ministry of Education(2020KDZ12)the National Natural Science Foundation Joint Funded Project of China(U2034203),the National Natural Science Foundation Joint Funded Project of China(U22A20600)+2 种基金the Hubei Key Laboratory of Disaster Prevention and Mitigation of China Three Gorges University(2022KJZ08)Natural Science Research Program of Yichang City in 2023(A23-2-047)Scientific Research Program of Hubei Provincial Department of Education in 2022(B2022567)。
文摘This paper aims to elucidate the seismic characteristics of the Three Gorges Reservoir area after impoundment and investigate the seismic source migration.Based on the seismic data analysis from the Badong segment in the Three Gorges Reservoir area,we assessed the local temporal and spatial variations in the frequent earthquakes.Correlation analysis was conducted to investigate the relationship between changes in reservoir water levels and the occurrence of reservoir-induced earthquakes.Additionally,we examined the regularity of earthquake occurrences at the exact location during different periods.Based on the fault mechanics principles,a formula was derived to estimate the length of open and wing-shaped rupture at the hypocenter under the influence of pore or excess pore water pressure.The results reveal that reservoir-induced seismicity demonstrates short-term cycles characterized by alternating"active periods"and"quiet periods,"as well as long-term cycles with the combined periods.The probability of earthquakes occurring within one year at the epicentre is relatively high and decreases after four years.The derived formula can be utilized to estimate the seismic migration distance at the epicentre in the short term.These research findings provide valuable insights for analyzing the regularity of reservoir-induced earthquake activities and understanding the mechanism of seismic source migration.
文摘This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.
文摘1 Exploring Transylvania,with its promises of ancient buildings,wall‑guarded churches and fantastic castles,is a genuine treat for nature lovers,but since October 2022,a new social project,Via Transilvanica,aims to invite active travelers to explore the essence of Romanian culture.
文摘In this paper,cosmic distance duality relation(CDDR)is probed without considering any background cosmological model.The only a priori assumption is that the Universe is described by the Friedmann–Lema?tre–Robertson–Walker(FLRW)metric.The strong gravitational lensing data is used to construct the dimensionless comoving distance function d(z)and latest type Ia supernovae Pantheon+data is used to estimate luminosity distances at the corresponding redshifts z.Using the distance sum rule along null geodesics of the FLRW metric,the CDDR violation is probed in both flat and non-flat spacetime by considering two parametrizations forη(z),the function generally used to probe the possible deviations from CDDR.The results show that CDDR is compatible with the observations at a very high level of confidence for linear parametrization in a flat Universe.In a non-flat Universe too,CDDR is valid within the 1σconfidence interval with a mild dependence ofηon the curvature density parameterΩK.The results for nonlinear parametrization also show no significant deviation from CDDR.
基金supported by the National Natural Science Foundation of China(52222217,52388102,52372435)the Major Science and TechnologyProject of China Energy(GJNY-22-7)
文摘Virtual coupling(VC) is an emerging technology for addressing the shortage of rail transportation capacity. As a crucial enabling technology, the VC-specific acquisition of train information, especially train following distance(TFD), is underdeveloped.In this paper, a novel method is proposed to acquire real-time TFD by analyzing the vibration response of the front and following trains, during which only onboard accelerometers and speedometers are required. In contrast to the traditional arts of train positioning, this method targets a relative position between two adjacent trains in VC operation, rather than the global positions of the trains. For this purpose, an adaptive system containing three strategies is designed to cope with possible adverse factors in train operation. A vehicle dynamics simulation of a heavy-haul railway is implemented for the evaluation of feasibility and performance. Furthermore, a validation is conducted using a set of data measured from in-service Chinese high-speed trains. The results indicate the method achieves satisfactory estimation accuracy using both simulated and actual data. It has favorable adaptability to various uncertainties possibly encountered in train operation. Additionally, the method is preliminarily proven to adapt to different locomotive types and even different rail transportation modes. In general, such a method with good performance, low-cost, and easy implementation is promising to apply.
基金supported by Beijing Natural Science Foundation (No.8254049)the National Natural Science Foundation of China (No.52374139)the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project (No.2024ZD1004505)。
文摘Coal mine underground reservoir(CMUR) technology mitigates water scarcity in China's coal-rich western regions but lacks tailored solutions for steeply inclined coal seams.This study develops a novel framework of steeply inclined coal mine underground reservoirs(SICMUR),which is a paradigm shift from conventional CMUR that the coal seam itself serves as the reservoir floor,challenging conventional designs due to depth-dependent permeability and mechanical constraints.Triaxial mechanical-seepage tests on Xinjiang Wudong coal samples(100,200,300 m depths) revealed a 3.5 MPa triaxial strength increase per 100 m depth and a 58-fold post-peak permeability surge at 300 versus 100 m.Similar model simulations revealed mining-induced stress redistribution and significant deformation effects,particularly subsidence and water-conducting fractures during lower coal seam mining.Results indicate a minimum 40 m safety distance between reservoirs and lower coal seams.Critical construction parameters were investigated for Wudong mine SICMUR as collapse zone heights(9.9–12.31 m) and waterconducting fracture zone heights(31.96–37.40 m).This work systematically bridges SICMUR concepts to field implementation,offering a framework for water preservation in steeply inclined mining while addressing safety concerns,providing a new approach for water reservation in steeply inclined coal mining.
基金Basic research program of Shanxi Province(20210302124136 and 20210302123177)National Key R&D Program of China(2019YFA0705501)+1 种基金Key R&D and promotion projects in Henan Province(212102310010)National Natural Science Foundation of China(52104144,U23B2088).
文摘When high-temperature steam is used as a medium to pyrolyze organic-rich shale,water steam not only acts as heat transfer but also participates in the chemical reaction of organic matter pyrolysis,thus affecting the generation law and release characteristics of gas products.In this study,based on a long-distance reaction system of organic-rich shale pyrolysis via steam injection,the effects of steam temperature and reaction distance on gas product composition are analyzed in depth and compared with other pyrolysis processes.The advantages of organic-rich shale pyrolysis via steam injection are then evaluated.The volume concentration of hydrogen in the gas product obtained via the steam injection pyrolysis of organic-rich shale is the highest,which is more than 60%.The hydrogen content increases as the reaction distance is extended;however,the rate of increase changes gradually.Increasing the reaction distance from 800 to 4000 mm increases the hydrogen content from 34.91%to 69.68%and from 63.13%to 78.61%when the steam temperature is 500℃ and 555℃,respectively.However,the higher the heat injection temperature,the smaller the reaction distance required to form a high concentration hydrogen pyrolysis environment(hydrogen concentration>60%).When the steam pyrolysis temperature is increased from 500℃ to 555℃,the reaction distance required to form a high concentration of hydrogen is reduced from 3800 to 800 mm.Compared with the direct retorting process,the volume concentration of hydrogen obtained from high-temperature steam pyrolysis of organic-rich shale is 8.82 and 10.72 times that of the commonly used Fushun and Kivite furnaces,respectively.The pyrolysis of organic-rich shale via steam injection is a pyrolysis process in a hydrogen-rich environment.
文摘This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for arrhythmia detection.The proposed classifier leverages the Chi-square distance as a primary metric,providing a specialized and original approach for precise arrhythmia detection.To optimize feature selection and refine the classifier’s performance,particle swarm optimization(PSO)is integrated with the Chi-square distance as a fitness function.This synergistic integration enhances the classifier’s capabilities,resulting in a substantial improvement in accuracy for arrhythmia detection.Experimental results demonstrate the efficacy of the proposed method,achieving a noteworthy accuracy rate of 98% with PSO,higher than 89% achieved without any previous optimization.The classifier outperforms machine learning(ML)and deep learning(DL)techniques,underscoring its reliability and superiority in the realm of arrhythmia classification.The promising results render it an effective method to support both academic and medical communities,offering an advanced and precise solution for arrhythmia detection in electrocardiogram(ECG)data.
基金supported by the National Research Foundation of Korea(NRF)Grant funded by the Korea government(MSIT)(No.RS-2023-00218176)Korea Institute for Advancement of Technology(KIAT)Grant funded by the Korea government(MOTIE)(P0012724)The Competency Development Program for Industry Specialist)and the Soonchunhyang University Research Fund.
文摘In this article,multiple attribute decision-making problems are solved using the vague normal set(VNS).It is possible to generalize the vague set(VS)and q-rung fuzzy set(FS)into the q-rung vague set(VS).A log q-rung normal vague weighted averaging(log q-rung NVWA),a log q-rung normal vague weighted geometric(log q-rung NVWG),a log generalized q-rung normal vague weighted averaging(log Gq-rung NVWA),and a log generalized q-rungnormal vagueweightedgeometric(logGq-rungNVWG)operator are discussed in this article.Adescription is provided of the scoring function,accuracy function and operational laws of the log q-rung VS.The algorithms underlying these functions are also described.A numerical example is provided to extend the Euclidean distance and the Humming distance.Additionally,idempotency,boundedness,commutativity,and monotonicity of the log q-rung VS are examined as they facilitate recognizing the optimal alternative more quickly and help clarify conceptualization.We chose five anemia patients with four types of symptoms including seizures,emotional shock or hysteria,brain cause,and high fever,who had either retrograde amnesia,anterograde amnesia,transient global amnesia,post-traumatic amnesia,or infantile amnesia.Natural numbers q are used to express the results of the models.To demonstrate the effectiveness and accuracy of the models we are investigating,we compare several existing models with those that have been developed.
文摘Let G be a strongly connected directed weighted graph with vertex set{v_(1),v_(2),...,v_(n)},in which each edge e is assigned with an arbitrary nonzero weight w(e).For any two vertices v_i,v_(j )of G,the distance d_(ij )from v_(i)to v_(j)is defined as dij=P∈P(v_(i),v_(j))min∑w(e) where P(v_(i),v_(j)) denotes the set consisting of all the directed paths from v_(i)to v_(j)in G.Given a nonzero indeterminant q,following the definitions from Yan and Yeh (Adv.Appl.Math.,2007),and Bapat et al.(Linear Algebra Appl.,2006),one can define the exponential distance matrix of G as F^(q)_(G)=(q^(dij))_(n×n),and define the q-distance matrix of G as D_(G)^(q)=(d_(ij)^(q))_(n×n)with d_(ij)^(q)={1-q^(dij)/1-q,if q≠1,dij,if q=1,extending the original definitions only for the undirected unweighted connected graphs.One of the remarkable results about the distance matrices of graphs is due to the Graham-HoffmanHosoya theorem (J.Graph Theory,1977).In this paper,we present some Graham-HoffmanHosoya type theorems for the exponential distance matrix F_(G)^(q)and q-distance matrix D_(G)^(q),extending all the known Graham-Hoffman-Hosoya type theorems.
