A Portfolio Selection Method Based on Pattern Matching with Dual Information of Direction and Distance

Pattern matching method is one of the classic classifications of existing online portfolio selection strategies. This article aims to study the key aspects of this method—measurement of similarity and selection of similarity sets, and proposes a Portfolio Selection Method based on Pattern Matching with Dual Information of Direction and Distance (PMDI). By studying different combination methods of indicators such as Euclidean distance, Chebyshev distance, and correlation coefficient, important information such as direction and distance in stock historical price information is extracted, thereby filtering out the similarity set required for pattern matching based investment portfolio selection algorithms. A large number of experiments conducted on two datasets of real stock markets have shown that PMDI outperforms other algorithms in balancing income and risk. Therefore, it is suitable for the financial environment in the real world.

Exact Graph Pattern Matching:Applications,Progress and Prospects

Graph pattern matching(GPM)can be used to mine the key information in graphs.Exact GPM is one of the most commonly used methods among all the GPM-related methods,which aims to exactly find all subgraphs for a given query graph in a data graph.The exact GPM has been widely used in biological data analyses,social network analyses and other fields.In this paper,the applications of the exact GPM were first introduced,and the research progress of the exact GPM was summarized.Then,the related algorithms were introduced in detail,and the experiments on the state-of-the-art exact GPM algorithms were conducted to compare their performance.Based on the experimental results,the applicable scenarios of the algorithms were pointed out.New research opportunities in this area were proposed.

A Retrospective Analysis of the Patterns and Outcomes of Tile B and Tile C Pelvic Fractures in Cameroon

Background: Pelvic fractures constitute about 2% - 8% of all fractures. This incidence may rise up to 25% in poly-traumatised patients. These fractures have a high mortality rate due to the fact that they occur usually as a result of high energy trauma, and most of the injured are poly-traumatised with concomitant haemodynamic instability. The aim of this study is to describe the patterns of injury and complications of unstable pelvic fractures treated in a level III hospital in Cameroon. Methodology: This was a hospital based retrospective analysis of files of patients admitted and treated for unstable pelvic fractures at the Regional Hospital Limbe within a period of 10 years (from 1st of January 2009 to 31st of December 2018). Results: A total of 139 cases of pelvic fractures were identified, amongst which 77 were unstable;68 were finally analyzed. The ages ranged from 18 to 80 years with a mean of 39 ± 5 years. The age group from 20 - 40 years was most represented (58.88%, n = 40). There were 45 males and 23 females giving a sex-ratio of 2:1. Road traffic injuries accounted for most of the cases (73.53%, n = 50). Forty-five (66.2%) were classified Tile B and 23 (33.82%) were Tile C, and 15 cases were open fractures (22.06%). Associated lesions were recorded in 30 cases, fractures of the lower extremity being the most common (33.33%, n = 10). Most of the cases were definitively treated surgically (80.89%, n = 55). The most common complications were surgical site infections (23.64%, n = 13). Conclusion: Unstable pelvic fractures are relatively common. Young males in the age group 20 - 40 years are the most affected, and the most common cause of injury was road traffic accident. Surgical site infections, pressure ulcers, severe anaemia and thrombo-embolism are common complications.

Performance analysis and optimal design for well patterns in anisotropic formations

The mechanism of the effects of anisotropic permeability on well patterns and reservoir development are investigated by coordinate transformation, fluid flow analysis, and reservoir development concepts. Anisotropy of permeability has reconstructive effects on well patterns. The originally designed flooding units are broken up, and new pattern units are made up of the wells that belong to different original units. The behavior possesses strong randomness, and leads to a complicated relationship among the injection and production wells, and unpredictable productivity of the formations. To prevent the break-up of well patterns, well lines should be either parallel or perpendicular to the maximum principal direction of the anisotropic permeability （i.e. the fracture direction）. To optimize the development effects ofanisotropic formations, the latitudinal and longitudinal well spacing of the well network are calculated from the principal values of the anisotropic permeability.

Optimization of integrated geological-engineering design of volume fracturing with fan-shaped well pattern

According to the variable toe-to-heel well spacing, combined with the dislocation theory, discrete lattice method, and finite-element-method(FEM) based fluid-solid coupling, an integrated geological-engineering method of volume fracturing for fan-shaped well pattern is proposed considering the geomechanical modeling, induced stress calculation, hydraulic fracturing simulation, and post-frac productivity evaluation. Besides, we propose the differential fracturing design for the conventional productivity-area and the potential production area for fan-shaped horizontal wells. After the fracturing of the conventional production area for H1 fan-shaped well platform, the research shows that the maximum reduction of the horizontal principal stress difference in the potential productivity-area is 0.2 MPa, which cannot cause the stress reversal, but this reduction is still conducive to the lateral propagation of hydraulic fractures. According to the optimized fracturing design, in zone-Ⅰ of the potential production area, only Well 2 is fractured, with a cluster spacing of 30 m and an injection rate of 12 m^(3)/min per stage;in zone-Ⅱ, Well 2 is fractured before Well 3, with a cluster spacing of 30 m and an injection rate of 12 m^(3)/min per stage. The swept area of the pore pressure drop in the potential production area is small, showing that the reservoir is not well developed. The hydraulic fracturing in the toe area can be improved by, for example, properly densifying the fractures and adjusting the fracture distribution, in order to enhance the swept volume and increase the reservoir utilization.

POINT PATTERN MATCHING ALGORITHM BASED ON POINT PAIR TOPOLOGICAL CHARACTERISTICS AND SPECTRAL MATCHING

Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.

Carving Thumbnail/s and Embedded JPEG Files Using Image Pattern Matching

Images (typically JPEG) are used as evidence against cyber perpetrators. Typically the file is carved using standard patterns. Many concentrate on carving JPEG files and overlook the important of thumbnail in assisting forensic investigation. However, a new unique pattern is used to detect thumbnail/s and embedded JPEG file. This paper is to introduce a tool call PattrecCarv to recognize thumbnail/s or embedded JPEG files using unique hex patterns (UHP). A tool called PattrecCarv is developed to automatically carve thumbnail/s and embedded JPEG files using DFRWS 2006 and DFRWS 2007 datasets. The tool successfully recovers 11.5% more thumbnails and embedded JPEG files than PredClus.

Experimental evaluation on well pattern adaptability of ultra-low permeability reservoir using sandstone flat model

As for ultra-low permeability reservoir,the adaptability of common nine-spot well pattern is studied through large-scale flat models made by micro-fractured natural sandstone outcrops.Combined with non-linear porous flow characteristics,the concept of dimensionless pressure sweep efficiency and deliverability index are put forward to evaluate the physical models' well pattern adaptability.Through experiments,the models' pressure distribution is measured and on which basis,the pressure gradient fields are drawn and the porous flow regions of these models are divided into dead oil region,non-linear porous flow region,and quasi-linear porous flow region with the help of twin-core non-linear porous flow curve.The results indicate that rectangular well pattern in fracture reservoirs has the best adaptability,while the worst is inverted nine-spot equilateral well pattern.With the increase of drawdown pressure,dead oil region decreases,pressure sweep efficiency and deliverability index increase; meantime,the deliverability index of rectangular well pattern has much more rational increase.Under the same drawdown pressure,the rectangular well pattern has the largest pressure sweep efficiency.

Spectral matching algorithm based on nonsubsampled contourlet transform and scale-invariant feature transform

A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix （or matching result） reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.

New multi-pattern matching algorithm

The traditional multiple pattern matching algorithm, deterministic finite state automata, is implemented by tree structure. A new algorithm is proposed by substituting sequential binary tree for traditional tree. It is proved by experiment that the algorithm has three features, its construction process is quick, its cost of memory is small. At the same time, its searching process is as quick as the traditional algorithm. The algorithm is suitable for the application which requires preprocessing the patterns dynamically.

DYNAMIC PRODUCTION PREDICTION AND PARAMETER IDENTIFICATION FOR GAS WELL WITH VERTICAL FRACTURE

In order to devoid the hard work and factitious error in selecting charts while analyzing and interpreting hydraulic fracturing fracture parameters, on the basis of the non-Darcy flow factor, this paper put out the non-Darcy flow mathematical model of real gas in the formation and fracture, established the production history automatic matching model to identify fracture parameters, and offered the numerical solutions of those models, which took the variation of fracture conductivity in production process. These results offered a precise and reliable method to understand formation, analyze and evaluate the fracturing treatment quality of gas well.

Location estimation of autonomous driving robot and 3D tunnel mapping in underground mines using pattern matched LiDAR sequential images

In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous driving robot continuously detects the wall of the tunnel in the horizontal direction using the light detection and ranging(Li DAR)sensor and performs pattern matching by recognizing the shape of the tunnel wall.The proposed method was designed to measure the heading of the robot by fusion with the inertial measurement units sensor according to the pattern matching accuracy;it is combined with the encoder sensor to estimate the location of the robot.In addition,when the robot is driving,the vertical direction of the underground mine is scanned through the vertical Li DAR sensor and stacked to create a 3D map of the underground mine.The performance of the proposed method was superior to that of previous studies;the mean absolute error achieved was 0.08 m for the X-Y axes.A root mean square error of 0.05 m^(2)was achieved by comparing the tunnel section maps that were created by the autonomous driving robot to those of manual surveying.

Does the Belt and Road Initiative Promote Value Chain Connection Between China and the Silk Road Countries?

The global value chains have become the core skeleton of the global economy.As a large-scale international cooperation initiative,the Belt and Road Initiative(BRI hereafter)may have a significant impact on the global economic landscape.In this context,the spatiotemporal pattern and evolution of the value chain connection of the Silk Road countries and whether the BRI will promote the value chain connections between China and these countries are important research questions for understanding the changing global economic landscape.This paper employs input-output analysis,network analysis and difference-in-differences based on Propensity Score Matching(PSM-DID)to conduct an in-depth quantitative study of these questions.The results show that,first,the overall value chain connection between China and the Silk Road countries has been rising since 2001.From the perspective of geographical distribution,Southeast Asia is the highest value chain connection region with China,and the growth in the central and eastern Europe is the most significant,whereas the central Asia is the lowest value connection region.From the perspective of complex network analysis,China’s position in the network of value flow among the Silk Road countries has been increasing continuously,and it has been in the lead position since 2008.Besides,the implementation of the BRI has had a significant positive influence on the overall value chain connection between China and the Silk Road countries,but this positive influence is limited to the central and eastern Europe region,whereas it is not significant in other regions.Finally,this paper suggests that to promote the development of value chain connection,the Silk Road countries need to develop more specific policies related to value chains.Policymakers need to be able to correctly identify the comparative advantages of the region and the types of value chains that are compatible with them and then find suitable partners and formulate targeted promotion policies.

A Novel Mathematical Model for Similarity Search in Pattern Matching Algorithms

Modern applications require large databases to be searched for regions that are similar to a given pattern. The DNA sequence analysis, speech and text recognition, artificial intelligence, Internet of Things, and many other applications highly depend on pattern matching or similarity searches. In this paper, we discuss some of the string matching solutions developed in the past. Then, we present a novel mathematical model to search for a given pattern and it’s near approximates in the text.

Egg-spot matching in common cuckoo parasitism of the oriental reed warbler: effects of host nest availability and egg rejection

Background: The success of cuckoo parasitism is thought to depend largely on the extent of egg matching between cuckoo and host eggs, since poor-matching cuckoo egg would lead to more frequent egg rejection by the host. In this study, we investigated how egg-spot matching between the Common Cuckoo(Cuculus canorus) and its host, the Oriental Reed Warbler(Acrocephalus orientalis) is affected by the local parasitism rate, nest availability in breeding synchronization and egg rejection.Methods: We used the paired design of parasitized and their nearest non-parasitized nests where breeding occurred simultaneously to compare egg-spot matching. The image analysis was used to compare four eggshell pattern variables, namely spot size, density, coverage on the different areas of egg surface, and the distribution on the whole egg surface. Egg recognition experiments were conducted to test the effect of egg spots on egg rejection by the host.Results: Our results show that much better matching in almost all spot parameters tested on the side of the egg and the spot distribution on the whole egg occurred in parasitized nests than in non-parasitized nests. Matching of spot density between cuckoo and host eggs in parasitized nests increased with the synchronization between temporal availability of nests and the egg-laying period of female cuckoos. Egg recognition experiments in which the warbler eggs were deliberately painted with extra spots led to a significantly higher egg rejection rate(78.3%) than of unpainted eggs.Conclusion: Our data suggest that both the high temporal encounter rate between cuckoo and warbler nests as well as the high egg rejection ability of the host are important factors for egg-spot matching of the cuckoos.

Four Sliding Windows Pattern Matching Algorithm (FSW)

This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts;each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran algorithm (BR). The best time case is calculated and found to be??while the average case time complexity is??.

Enhancing ERS-A Algorithm for Pattern Matching (EERS-A)

Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network security and pattern recognition. This paper has presented a new pattern matching algorithm—Enhanced ERS-A, which is an improvement over ERS-S algorithm. In ERS-A, two sliding windows are used to scan the text from the left and the right simultaneously. The proposed algorithm also scans the text from the left and the right simultaneously as well as making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The shift technique used in the Enhanced ERS-A is the four consecutive characters in the text immediately following the pattern window. The experimental results show that the Enhanced ERS-A has enhanced the process of pattern matching by reducing the number of comparisons performed.

A Fast Multi-Pattern Matching Algorithm for Mining Big Network Data

The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource allocation and provide customized services to users. The first step of analyzing user behaviors is to extract information of user actions from HTTP traffic data by multi-pattern URL matching. However, the efficiency is a huge problem when performing this work on massive network traffic data. To solve this problem, we propose a novel and accurate algorithm named Multi-Pattern Parallel Matching(MPPM) that takes advantage of HashMap in data searching for extracting user behaviors from big network data more effectively. Extensive experiments based on real-world traffic data prove the ability of MPPM algorithm to deal with massive HTTP traffic with better performance on accuracy, concurrency and efficiency. We expect the proposed algorithm and it parallelized implementation would be a solid base to build a high-performance analysis engine of user behavior based on massive HTTP traffic data processing.

Optimizing of large-number-patterns string matching algorithms based on definite-state automata

Because the small CACHE size of computers, the scanning speed of DFA based multi-pattern string-matching algorithms slows down rapidly especially when the number of patterns is very large. For solving such problems, we cut down the scanning time of those algorithms (i.e. DFA based) by rearranging the states table and shrinking the DFA alphabet size. Both the methods can decrease the probability of large-scale random memory accessing and increase the probability of continuously memory accessing. Then the hitting rate of the CACHE is increased and the searching time of on the DFA is reduced. Shrinking the alphabet size of the DFA also reduces the storage complication. The AC++algorithm, by optimizing the Aho-Corasick (i.e. AC) algorithm using such methods, proves the theoretical analysis. And the experimentation results show that the scanning time of AC++and the storage occupied is better than that of AC in most cases and the result is much attractive when the number of patterns is very large. Because DFA is a widely used base algorithm in may string matching algorithms, such as DAWG, SBOM etc., the optimizing method discussed is significant in practice.

Fast Multi-Pattern Matching Algorithm on Compressed Network Traffic

Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.