Sorting Algorithm Research Articles

Comparative Analysis of Sorting and Searching Algorithms

Comparative Analysis of Sorting and Searching Algorithms

Advanced Active Player Tracking System in Handball Videos Using Multi-Deep Sort Algorithm with GAN Approach

Advanced Active Player Tracking System in Handball Videos Using Multi-Deep Sort Algorithm with GAN Approach

Blockchain event ordering algorithm based on high-dimensional multi-objective differential evolution

Abstract Since the birth of Bitcoin, blockchain technology has been widely used in many fields, such as finance, supply chain management, smart contracts, etc.and has been highly valued for its decentralized and tamper-proof characteristics. With the expansion of application scenarios, blockchain faces inefficient data processing challenges, particularly in event sequencing and processing. Developing efficient event sequencing algorithms is a research priority to enhance the performance of blockchain systems. This study addresses the efficiency problem in blockchain event sequencing by introducing a high-dimensional multi-objective differential evolution strategy to improve blockchain technology’s performance in various fields. This paper uses the NSGA-III-WA algorithm to efficiently sort blockchain events by combining differential evolution strategies. Compared to the traditional sorting algorithm, this algorithm reduces latency by 30% and improves memory usage by about 20% when dealing with events of the same size, ensuring sorting accuracy. By optimizing the weight vector adjustment strategy, the convergence speed and distribution uniformity of the algorithm and the solution can be optimized. In this paper, the algorithm can effectively improve the efficiency and performance of blockchain event processing, which is critical in optimizing blockchain systems.

Advanced Model of Parallel Sorting Algorithm with Ranking

Advanced Model of Parallel Sorting Algorithm with Ranking

Matrix Reordering for Noisy Disordered Matrices: Optimality and Computationally Efficient Algorithms.

Motivated by applications in single-cell biology and metagenomics, we investigate the problem of matrix reordering based on a noisy disordered monotone Toeplitz matrix model. We establish the fundamental statistical limit for this problem in a decision-theoretic framework and demonstrate that a constrained least squares estimator achieves the optimal rate. However, due to its computational complexity, we analyze a popular polynomial-time algorithm, spectral seriation, and show that it is suboptimal. To address this, we propose a novel polynomial-time adaptive sorting algorithm with guaranteed performance improvement. Simulations and analyses of two real single-cell RNA sequencing datasets demonstrate the superiority of our algorithm over existing methods.

Correlation Analysis of International Student Exchange and the Enhancement of China’s International Cultural Communication Power Based on the Subsumption Sorting Algorithm

Abstract International students are a bridge between Chinese and foreign cultures, but they still face multiple dilemmas in Chinese cultural communication due to different cultural backgrounds and values. In this paper, we utilize the subsumption sorting algorithm to sort the amount of cultural communication of international students’ exchanges, which is dynamically switched by a combination of two methods: back-block forward interpolation and header exchange. The D-S monopolistic competition model is used to construct the theoretical model of international student exchange that affects China’s international cultural communication power. The CES utility function is used to construct China’s international cultural communication network, which calculates the total amount of communication culture of cross-cultural exchanges between international students. In the end, an analysis of 85 international student samples revealed a correlation between international student exchanges and China’s international cultural communication. The results show that the correlation coefficient between international student exchanges and China’s international cultural communication is 0.305 p > 0.05, indicating that international student exchanges have a positive promotion effect on China’s international cultural communication. This study examines the general law of international cultural communication, which is crucial in promoting Chinese culture worldwide.

Severe Convective Storms in Limited Instability Organized by Pattern and Distribution

Abstract Severe convection occurring in high-shear, low-CAPE (HSLC) environments is a common cool-season threat in the southeastern United States. Previous studies of HSLC convection document the increased operational challenges that these environments present compared to their high-CAPE counterparts, corresponding to higher false-alarm ratios and lower probability of detection for severe watches and warnings. These environments can exhibit rapid destabilization in the hours prior to convection, sometimes associated with the release of potential instability. Here, we use self-organizing maps (SOMs) to objectively identify environmental patterns accompanying HSLC cool-season severe events and associate them with variations in severe weather frequency and distribution. Large-scale patterns exhibit modest variation within the HSLC subclass, featuring strong surface cyclones accompanied by vigorous upper-tropospheric troughs and northward-extending regions of instability, consistent with prior studies. In most patterns, severe weather occurs immediately ahead of a cold front. Other convective ingredients, such as lower-tropospheric vertical wind shear, near-surface equivalent potential temperature (θe) advection, and the release of potential instability, varied more significantly across patterns. No single variable used to train SOMs consistently demonstrated differences in the distribution of severe weather occurrence across patterns. Comparison of SOMs based on upper and lower quartiles of severe occurrence demonstrated that the release of potential instability was most consistently associated with higher-impact events in comparison to other convective ingredients. Overall, we find that previously developed HSLC composite parameters reasonably identify high-impact HSLC events. Significance Statement Even when atmospheric instability is not optimal for severe convective storms, in some situations they can still occur, presenting increased challenges to forecasters. These marginal environments may occur at night or during the cool season, when people are less attuned to severe weather threats. Here, we use a sorting algorithm to classify different weather patterns accompanying such storms, and we distinguish which specific patterns and weather system features are most strongly associated with severe storms. Our goals are to increase situational awareness for forecasters and to improve understanding of the processes leading to severe convection in marginal environments.

Методика выбора алгоритмов оптимизации живучести энергетических инфраструктур

The article considers one of the most difficult tasks of studying the resilience of energy infrastructures – finding effective combinations of measures to increase resilience. To solve this problem, the article describes an approach that considers it as a problem of structural-parametric optimization of energy infrastructures, which is built according to a two- or three-level scheme. The approach described in the article adds another layer to the middle of the above scheme, which checks the efficiency of the selected equipment under extreme conditions created by a given set of large disturbances. The main disadvantage that the approach inherits from the structural-parametric optimization of energy infrastructures is a high computational complexity of the multilevel optimization scheme. However, the unacceptable calculation time can be explained by the selection of inappropriate optimization algorithms. In the papers concerning the structural-parametric optimization of energy infrastructures publ in the literature, the question of comparing optimization algorithms with each other is clearly not raised. Therefore, this article proposes a three-stage methodology for selecting optimization algorithms, according to which, before solving a specific problem of optimizing the resilience of energy infrastructures, first test the algorithms, and then choose the best one based on a multi-criteria analysis of the test results. To apply the methodology, it is necessary to develop a special lightweight version of the task of optimizing resilience and prepare a testbed for organizing and conducting test computational experiments. The application of the methodology is demonstrated by the example of choosing heuristic methods for finding optimal solutions from the PaGMO library used at the external level of the resilience optimization scheme of the Unified Gas Supply System of Russia. In total, five popular evolutionary algorithms were tested, the most suitable of which turned out to be a genetic sorting algorithm without NSGA-II dominance.

Probabilistic Modeling for Conditional Statements

A new mathematical framework is proposed in this study to comprehend the impact of program architecture on input random variables, the IF statement was the main topic. The primary idea that is theoretically and experimentally supported in this study is that the part of the joint pmf of a collection of random variables that represents the condition will be shifted to the part that represents the action. After sorting two random variables, the framework is used with four random variables, and the theoretically produced results were realistically validated. The study's equations can be applied to assessing probabilistic models of various sorting algorithms or other intricate program structures. This may also result in future investigations formalizing more precise execution time expectations.

Guidelines for the use of flow cell sorting in diagnosis and monitoring of acute leukemia

Flow cell sorting is an advanced laboratory technique that combines the analytical capabilities of flow cytometry with the ability to isolate pure cell populations from heterogeneous samples. It has tremendous potential both for fundamental research and laboratory diagnosis. For example, the combination of cell sorting and molecular genetic studies can be used to clarify ambiguous results of acute leukemia immunophenotyping obtained both at diagnosis and during minimal residual disease monitoring. These guidelines are based on years of experience in incorporating cell sorting into the diagnostic and monitoring processes at the Leukemia Immunophenotyping Laboratory of the Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology. They include methods used for the confirmation of flow cytometry data depending on the type of leukemia, the stage of a flow cytometry assay and previous therapy. They also describe cell sorting algorithms for disease diagnosis and the specifics of sample preparation for cell sorting in different molecular genetic studies.

Approximate sorting and its applications in I/O model

Sorting is a fundamental component in many different applications including web indexing engines, geographic information systems, data mining and database systems. However, the existing optimal algorithms still cause huge costs when the input data becomes very large. Thus, the approximate sorting for big data is considered in this paper. The goal of approximate sorting for big data is to generate an approximate sorted result, but using less CPU and I/O cost. For big data, we consider the approximate sorting and applications for approximate sorted results in I/O model.The quality of approximate sorting results is usually measured by the distance metrics on permutation space. However, the existing metrics on permutation space are not available for external approximate sorting algorithms. Thus, we propose a new kind of metric named External metric, which ignores the errors and dislocations that happened in each I/O block. The External metric of Spearman's footrule metric is named as External Spearman's footrule metric (short as ESP metric), which is analyzed in this paper.Furthermore, to facilitate a better evaluation of the approximate sorted result, we propose a new metric, named as errors, which directly states the number of dislocation of the elements. The External errors are also considered in this paper.Then, according to the rate-distortion relationship under these two metrics, the lower bound of these two metrics on external approximate sorting problem with t I/O operations is proved. We propose a k-passes external approximate sorting algorithm, named as EASORT, and prove that EASORT is asymptotically optimal under ESP metric.Finally, we consider the applications on approximate sorting results. An index for the approximate sorted result is proposed. The single and range query on approximate sorted result using this index are also analyzed. Further, the sort-merge join on two relations, where one of the relations is approximate sorted or both relations are approximate sorted, are all discussed in this paper.

Improved A-Star Path Planning Algorithm in Obstacle Avoidance for the Fixed-Wing Aircraft

The flight management system is a basic component of avionics for modern airliners. However, the airborne flight management system needs to be improved and relies on imports; path planning is the key to the flight management system. Based on the classical A* algorithm, this paper proposes an improved A* path planning algorithm, which solves the problem of low planning efficiency and following a non-smooth path. In order to solve the problem of the large amount of data calculation and long planning time of the classical A* algorithm, a new data structure called a “value table” is designed to replace the open table and close table of the classical A* algorithm to improve the retrieval efficiency, and the Heap sort algorithm is used to optimize the efficiency of node sorting. Aiming at the problem that the flight trajectory is hard to follow, the trajectory smoothing optimization algorithm combined with turning angle limit is proposed. The gray value in the digital map is added to the A* algorithm, and the calculation methods of gray cost, cumulative cost, and estimated cost are improved, which can better meet the constraints of obstacle avoidance. Through the comparative simulation verification of the algorithm, the improved A* algorithm can significantly reduce the path planning time to 1% compared to the classical A* algorithm; it can be seen that the proposed algorithm improves the efficiency of path planning and the smoother planned path, which has obvious advantages compared to the classical A* algorithm.

Single-Instruction-Multiple-Data Instruction-Set-Based Heat Ranking Optimization for Massive Network Flow

In order to cope with the massive scale of traffic and reduce the memory overhead of traffic statistics, the traffic statistics method based on the Sketch algorithm has become a research hotspot for traffic statistics. This paper studies the problem of the top-k flow statistics based on the Sketch algorithm and proposes a method to estimate the flow heat from massive network traffic using the Sketch algorithm and identify the kth flow with the highest heat by using a bitonic sort algorithm. In view of the performance difficulties of applying multiple hash functions in the implementation of the Sketch algorithm, the Single-Instruction-Multiple-Data (SIMD) instruction set is adopted to improve the performance of the Sketch algorithm so that SIMD instructions can process multiple fragments of data in a single step, implement multiple hash operations at the same time, compare and sort multiple flow tables at the same time. Thus, the throughput of the execution task is improved. Firstly, the elements of data flow are described and stored in the form of vectors, while the construction, analysis, and operation of data vectors are realized by SIMD instructions. Secondly, the multi-hash operation is simplified into a single vector operation, which reduces the CPU computing resource consumption of the Sketch algorithm. At the same time, the SIMD instruction set is used to optimize the parallel comparison operation of the flow table in a bitonic sort algorithm. Finally, the SIMD instruction set is used to optimize the functions in the Sketch algorithm and top-k sorting algorithm program, and the optimized code is tested and analyzed. The experimental results show that the time consumed by the advanced vector extensions (AVX)-instructions-optimized version has a significant reduction compared to the original version. When the length of KEY is 96 bytes, the instructions consumed by multiple hash functions account for less in the entire Sketch algorithm, and the time consumed by the optimized version of AVX is about 67.2% of that in the original version. As the length of KEY gradually increases to 256 bytes, the time consumed by the optimized version of AVX decreases to 53.8% of the original version. The simulation results show that the AVX optimization algorithm is effective in improving the measurement efficiency of network flow.

A minority of final stacks yields superior amplitude in single-particle cryo-EM

Cryogenic electron microscopy (cryo-EM) is widely used to determine near-atomic resolution structures of biological macromolecules. Due to the low signal-to-noise ratio, cryo-EM relies on averaging many images. However, a crucial question in the field of cryo-EM remains unanswered: how close can we get to the minimum number of particles required to reach a specific resolution in practice? The absence of an answer to this question has impeded progress in understanding sample behavior and the performance of sample preparation methods. To address this issue, we develop an iterative particle sorting and/or sieving method called CryoSieve. Extensive experiments demonstrate that CryoSieve outperforms other cryo-EM particle sorting algorithms, revealing that most particles are unnecessary in final stacks. The minority of particles remaining in the final stacks yield superior high-resolution amplitude in reconstructed density maps. For some datasets, the size of the finest subset approaches the theoretical limit.

Дослідження ефективності деяких детермінованих методів передобробки сортування даних

To verify the hypothesis about decrease in time of sorting by algorithms of different computational complexity experiments have been conducted. Several ideas on deterministic preprocessing of data arrays for sorting algorithms have been tested. The following algorithms are proposed: quick preprocessing – prediction of the index of an element in a sorted array and permutation, preprocessing with memory - prediction and permutation with memorization of previously set elements, preprocessing with reordering – reverting sequences of elements sorted in reverse order. Also proposed block variations of quick and preprocessing with memory, which are performed for parts of the array of a given length. It has been defined that the higher efficiency of preprocessing is achieved by using with sorting algorithms, which are significantly accelerated on sorted (or almost sorted) arrays of data. Block preprocessing methods can be performed faster due to the possibility of avoiding cache misses, but show a lower percentage of array sorting. Experiments were conducted to evaluate the effectiveness of various sorting algorithms after and together with the proposed preprocessing methods.

Comparative Analysis of OpenMP and MPI Parallel Computing Implementations in Team Sort Algorithm

Tim Sort is a sorting algorithm that combines Merge Sort and Binary Insertion Sort sorting algorithms. Parallel computing is a computational processing technique in parallel or is divided into several parts and carried out simultaneously. The application of parallel computing to algorithms is called parallelization. The purpose of parallelization is to reduce computational processing time, but not all parallelization can reduce computational processing time. Our research aims to analyse the effect of implementing parallel computing on the processing time of the Tim Sort algorithm. The Team Sort algorithm will be parallelized by dividing the flow or data into several parts, then each sorting and recombining them. The libraries we use are OpenMP and MPI, and tests are carried out using up to 16 core processors and data up to 4194304 numbers. The goal to be achieved by comparing the application of OpenMP and MPI to the Team Sort algorithm is to find out and choose which library is better for the case study, so that when there is a similar case, it can be used as a reference for using the library in solving the problem. The results of research for testing using 16 processor cores and the data used prove that the parallelization of the Sort Team algorithm using OpenMP is better with a speed increase of up to 8.48 times, compared to using MPI with a speed increase of 8.4 times. In addition, the increase in speed and efficiency increases as the amount of data increases. However, the increase in efficiency that is obtained by increasing the processor cores decreases.

Virtual network embedding method based on node delay perception

AbstractWireless virtual network uses software defined network and network function virtualisation technologies to create multiple logically isolated virtual networks on a physical wireless network. Wireless virtual network can improve the utilisation of wireless resources to meet the requirements of different services. Delay is an important performance indicator, which has strict requirements for delay‐sensitive services such as video conferencing and online games. In this study, a virtual network embedding method based on node delay perception (VNE‐NDP) is proposed, which considers both the node and link resources as well as the embedding delay requirements of virtual networks. The virtual network embedding method based on node delay perception consists of two phases: virtual node embedding and virtual link embedding. In the virtual node embedding phase, a physical node sorting method based on node delay perception (PNS‐NDP) is proposed. In PNS‐NDP, the node deployment delay is introduced into the node sorting algorithm for the first time. The authors select candidate physical nodes for each virtual node according to their resource availability and delay performance, which can greatly reduce the VN embedding delay without sacrificing too much other performance. In the virtual link embedding phase, a shortest path algorithm with bandwidth and link deployment delay constraints to find feasible physical paths for each virtual link is used. In addition, the VN embedding (VNE) deployment time is set as a new evaluation index. Simulation results show that compared with other VNE methods, VNE‐NDP can achieve higher success rate, revenue‐to‐expenditure ratio, and lower deployment delay.

A diminished sciatic nerve structural integrity is associated with distinct peripheral sensory phenotypes in individuals with type 2 diabetes

Aims/hypothesisQuantitative sensory testing (QST) allows the identification of individuals with rapid progression of diabetic sensorimotor polyneuropathy (DSPN) based on certain sensory phenotypes. Hence, the aim of this study was to investigate the relationship of these phenotypes with the structural integrity of the sciatic nerve among individuals with type 2 diabetes.MethodsSeventy-six individuals with type 2 diabetes took part in this cross-sectional study and underwent QST of the right foot and high-resolution magnetic resonance neurography including diffusion tensor imaging of the right distal sciatic nerve to determine the sciatic nerve fractional anisotropy (FA) and cross-sectional area (CSA), both of which serve as markers of structural integrity of peripheral nerves. Participants were then assigned to four sensory phenotypes (participants with type 2 diabetes and healthy sensory profile [HSP], thermal hyperalgesia [TH], mechanical hyperalgesia [MH], sensory loss [SL]) by a standardised sorting algorithm based on QST.ResultsObjective neurological deficits showed a gradual increase across HSP, TH, MH and SL groups, being higher in MH compared with HSP and in SL compared with HSP and TH. The number of participants categorised as HSP, TH, MH and SL was 16, 24, 17 and 19, respectively. There was a gradual decrease of the sciatic nerve’s FA (HSP 0.444, TH 0.437, MH 0.395, SL 0.382; p=0.005) and increase of CSA (HSP 21.7, TH 21.5, MH 25.9, SL 25.8 mm2; p=0.011) across the four phenotypes. Further, MH and SL were associated with a lower sciatic FA (MH unstandardised regression coefficient [B]=−0.048 [95% CI −0.091, −0.006], p=0.027; SL B=−0.062 [95% CI −0.103, −0.020], p=0.004) and CSA (MH β=4.3 [95% CI 0.5, 8.0], p=0.028; SL B=4.0 [95% CI 0.4, 7.7], p=0.032) in a multivariable regression analysis. The sciatic FA correlated negatively with the sciatic CSA (r=−0.35, p=0.002) and markers of microvascular damage (high-sensitivity troponin T, urine albumin/creatinine ratio).Conclusions/interpretationThe most severe sensory phenotypes of DSPN (MH and SL) showed diminishing sciatic nerve structural integrity indexed by lower FA, likely representing progressive axonal loss, as well as increasing CSA of the sciatic nerve, which cannot be detected in individuals with TH. Individuals with type 2 diabetes may experience a predefined cascade of nerve fibre damage in the course of the disease, from healthy to TH, to MH and finally SL, while structural changes in the proximal nerve seem to precede the sensory loss of peripheral nerves and indicate potential targets for the prevention of end-stage DSPN.Trial registrationClinicalTrials.gov NCT03022721Graphical

An Artificial Physarum polycephalum Colony for the Electric Location-Routing Problem

Electric vehicles invented for environmental sustainability are prone to adverse impacts on environmental sustainability due to the location and construction of their charging facilities. In this article, an artificial Physarum polycephalum colony is proposed to solve the novel challenging problem. First, the electric location-routing problem is established as a multi-objective network panning model with electric constraints to provide the optimal charging infrastructure layout, electric vehicle maintenance costs, and traffic conditions. The electric facility location problem and vehicle routing problem are integrated by integer programming, which considers the total distance, total time, total cost, total number of electric vehicles, and order fill rate. Second, an artificial Physarum polycephalum colony is introduced to solve the complex electric location-routing problem and includes the two basic operations of expansion and contraction. In the expansion operation, the optimal parent individuals will generate more offspring individuals, so as to expand the population size. In the contraction operation, only individuals with high fitness will be selected to survive through a merge sorting algorithm, resulting in a decrease in population size to the initial value. Through the iterative computing of the two main operations, the proposed artificial Physarum polycephalum colony can finally find the optimal solution to the objective function. Third, a benchmark test is designed for the electric location-routing problem by extracting the real road network from Tokyo, and the experimental results prove the effectiveness and applicability of this work.

The effect of an improved passive bumper on the seismic response of the base-isolated structure: Numerical simulations and optimization design

In this paper, a passive bumper, called Flexible Limit Protective Device (FLPD) which was proposed by the author before, was improved to better control the seismic response of the base-isolated structure when the isolation layer exceeds its limit deformation. To distinguish from the FLPD, the improved FLPD is called a Flexible Energy Dissipating Device (FEDD), and the FEDD has stronger dissipation capacity than the FLPD. Above all, the compression behavior of FEDDs is experimentally investigated and the experiment data of FEDDs are compared to that of FLPDs. Subsequently, the nonlinear model of FEDDs is obtained and verified using the experimental data. This obtained model was used to study the effect on the seismic response of the base-isolated structure (multi-degree-of-freedom system), namely isolator displacement and inter-story drift angle. An elite non-dominated sorting algorithm method (NSGA-II) is applied to optimize the design of FEDDs, the gap between isolators and FEDDs and stiffness of FEDDs. Finally, the seismic response of base-isolated buildings equipped with FEDD with optimal parameters is numerically simulated. The results show that FEDDs with optimal parameters can effectively reduce the isolator displacements, and keep the inter-story drift angle within the safe range when the isolation layer exceeds its limit deformation during earthquakes.