Results Of Similar Calculations Research Articles

Genome Characterization of the Novel Lytic Enterobacter cloacae Phage vB_EclM_Q7622.

Enterobacter cloacae is a widespread opportunistic pathogen that causes urinary tract infection. The abuse of antibiotics enabled multidrug-resistant strains to spread. Bacteriophage therapy is a naturally, safe, and efficient alternative treatment technology against multi-resistant bacteria. In this study, a virulent phage vB_EclM_Q7622 (Q7622) was isolated from the sewage of Jiangcun poultry market in Guangzhou city. Transmission electron microscopy indicated that Q7622 had an icosahedral head (97.8 ± 5.6nm in diameter) and a short, contractile tail (113.7 ± 4.5nm). Its double-stranded DNA genome is composed of 173,871bp with a GC content of 40.02%. It possesses 297 open reading frames and 9 tRNAs. No known virulence and resistance genes were detected, indicated that phage Q7622 could be used for pathogens prevention and control safely. Comparative genomic and phylogenetic analysis showed that Q7622 was highly similar to the phages vB_EclM_CIP9 and vB_EhoM-IME523. The highest nucleotide similarity between Q7622 and the similar phages in NCBI calculated by pyANI and VIRIDIC were 94.9% and 89.1% with vB_EhoM-IME523 respectively, below 95%. Thus, according to the result of nucleotide similarity calculation results, Q7622 was a novel virulent Enterobacter cloacae phage strain of the genus Kanagawavirus.

Case-based reasoning for shipwreck emergency salvage scheme assisted decision

Shipwrecks that adversely affect the marine ecological environment and the passage of vessels should be recovered urgently. The formulation of emergency salvage plans is still based on experts’ judgment. Therefore, this paper proposes an assisted decision model for the emergency salvage plan for wrecks based on case reasoning. This paper uses the Improved Game Theory (IGT) method to calculate the combined weight of multiple subjective and objective methods to overcome the one-sidedness of a single method to determine the weight. To further improve the sensitivity of the interval similarity calculation, this paper improves the method of interval similarity calculation in shipwreck cases. Based on the comparison and analysis of multiple methods based on the real shipwreck salvage case, the standard deviation of the case similarity obtained by the model method in this paper is 0.134, which is the highest compared with the classical algorithm, which shows that the similarity calculation results of this paper are reasonable and have a higher degree of discrimination. This method can provide decision support for the formulation of a marine emergency salvage plan for shipwrecks.

Reservoir Permeability Prediction Based on Analogy and Machine Learning Methods: Field Cases in DLG Block of Jing’an Oilfield, China

Abstract Reservoir permeability, generally determined by experimental or well testing methods, is an essential parameter in the oil and gas field development. In this paper, we present a novel analogy and machine learning method to predict reservoir permeability. Firstly, the core test and production data of other 24 blocks (analog blocks) are counted according to the DLG block (target block) of Jing’an Oilfield, and the permeability analogy parameters including porosity, shale content, reservoir thickness, oil saturation, liquid production, and production pressure difference are optimized by Pearson and principal component analysis. Then, the fuzzy matter element method is used to calculate the similarity between the target block and analog blocks. According to the similarity calculation results, reservoir permeability of DLG block is predicted by reservoir engineering method (the relationship between core permeability and porosity of QK-D7 in similar blocks) and machine learning method (random forest, gradient boosting decision tree, light gradient boosting machine, and categorical boosting). By comparing the prediction accuracy of the two methods through the evaluation index determination coefficient (R2) and root mean square error (RMSE), the CatBoost model has higher accuracy in predicting reservoir permeability, with R2 of 0.951 and RMSE of 0.139. Finally, the CatBoost model is selected to predict reservoir permeability of 121 oil wells in the DLG block. This work uses simple logging and production data to quickly and accurately predict reservoir permeability without coring and testing. At the same time, the prediction results are well applied to the formulation of DLG block development technology strategy, which provides a new idea for the application of machine learning to predict oilfield parameters.

Key Information Extraction Algorithm of Different Types of Digital Archives for Cultural Operation and Management.

In order to improve the effect of key information extraction from digital archives, a key information extraction algorithm for different types of digital archives is designed. Preprocess digital archive information, taking part of speech and marks as key information. Self-organizing feature mapping network is used to extract the key information features of digital archives, and the semantic similarity calculation results are obtained by combining the feature extraction results. Combine with mutual information collection, take that word with the highest mutual information value as the collection cent, traverse all keywords, and take the central word as the key information of digital archives to complete the extraction of key information. Experiments show that the recall rate of the algorithm ranges from 96% to 99%, the extraction accuracy of key information of digital archives is between 96 and 98%, and the average extraction time of key information of digital archives is 0.63 s. The practical application effect is good.

Design and Implementation of Road Traffic Responsibility Identification System based on Semantic Understanding and Similar Cases

<p>The deep integration of deep learning and the judicial field has led to the continuous development of judicial intelligence. Judicial intelligence can not only assist judicial practitioners to improve their work efficiency, but also better serve the public and promote judicial convenience. Liability determination is the main basic task of judicial intelligence, but with the increase in the number of cases, staff will spend a lot of time dealing with similar cases, reducing work efficiency and consuming energy, so this paper combines natural language processing technology, Recommendation strategy and deep learning, research and implement a road traffic responsibility identification system based on semantic understanding and similar cases. To a certain extent, it can assist sentencing decision-making and standardize judgment standards. This paper firstly studies and analyzes related technologies, then identifies similar cases, uses triples to extract text keywords, and then uses gensim library and text2vec library to calculate text similarity, and then uses D-S evidence theory to compare the above two methods. The fusion of the similarity calculation results, and combined with the road traffic responsibility identification system for application, in which the main function of the evidence theory is to complete the similar case recommendation and similarity calculation through the case description. The establishment of a road traffic responsibility identification system has the important value of improving the predictability of judicial activities and realizing formal and substantive justice.</p> <p> </p>

A Correlation Analysis of Geomagnetic Field Characteristics in Geomagnetic Perceiving Navigation.

It is well-known that geomagnetic fields have multiple components or parameters, and that these geomagnetic parameters are related to each other. In this paper, a parameter selection method is proposed, and this paper mainly discusses the correlation of geomagnetic field parameters for geomagnetic navigation technology. For the correlation analysis between geomagnetic parameters, the similarity calculation of the correlation coefficient is firstly introduced for geomagnetic navigation technology, and the grouped results are obtained by data analysis. At the same time, the search algorithm (Hex-path algorithm) is used to verify the correlation analysis results. The results show the same convergent state for the approximate correlation coefficient. In other words, the simulation results are in agreement with the similarity calculation results.

SISTEM PAKAR DIAGNOSA KERUSAKAN MOTOR KAWASAKI KLX150 MENGGUNAKAN METODE CASE-BASED REASONING DENGAN ALGORITMA 3W-JACCARD

In this day and age, motorbikes have an important role in transportation facilities, motorbike users are increasingly dense, especially in the city of Semarang, which is not accompanied by information media. The lack of media information regarding damage to the motorbike makes it difficult for someone to know the cause of the damage to the motorbike, not to mention the Kawasaki KLX150 which happens a lot of engine damage. For this reason, the expert system diagnoses motor damage by knowing the type of motor damage, after that diagnostics and alternative solutions to the problem are carried out. With this, the method and algorithm used is Case-Based Reasoning (CBR) using the Similarity 3W-Jaccard calculation, this second method and algorithm can be used to diagnose damage from the symptoms in the database. Each symptom has a weighted value of each, including a value of 5 (five) for severe symptoms, relating to engine and electrical parts, a value of 3 (three) for moderate symptoms, relating to braking and chains, a value of 1 (one) mild symptom, relating to with the indicator on the speedometer. The system will display 5 (five) types of damage calculated using the 3W-Jaccard Algorithm sorted by the highest value. The revision process will appear if the similarity calculation results are less than 0.6 (zero point six) because it is considered that the results are not sufficiently similar to the solution to be repaired, it needs to be reviewed and will be entered into the review table, then the expert will find a solution.

Design and Implementation of English Intelligent Communication Platform Based on Similarity Algorithm

Intelligent communication processing in English aims to obtain effective information from unstructured text data using various text processing techniques. Text vector representation and text similarity calculation are important fundamental tasks in the whole field of natural language processing. In response to the shortcomings of existing sentence vector representation models and the singularity of text similarity algorithms, improved models and algorithms are proposed based on a thorough study of related domain technologies. This paper presents an in-depth and comprehensive study of text vectorization representation and text similarity calculation algorithms in the field of natural language processing. The existing text vectorized representation models and text similarity computation algorithms are described, and their shortcomings are summarized to provide a basis for the background and significance of this paper, as well as to provide ideas for improvement directions. It is experimentally verified that the sentence vector model proposed in this paper achieves higher accuracy than the SIF sentence vector model for text classification tasks. In the task of text similarity computation, it achieves better results in three evaluation metrics: accuracy, recall, and F1 value. The algorithm also improves the computational efficiency of the model to a certain extent by removing feature words with low feature contribution. The algorithm first improves the deficiencies of the traditional word-shift distance algorithm by defining multifeature fusion weights and realizes a text similarity calculation algorithm based on multifeature weighted fusion with better similarity calculation results. Then, a linear weighting model is constructed to further combine the similarity calculation results of the hierarchical pooled IIG-SIF sentence vectors to realize the multimodel fusion text similarity calculation algorithm.

System Design of Cloud Search Engine Based on Rich Text Content

In order to improve the search performance of rich text content, a cloud search engine system based on rich text content is designed. On the basis of traditional search engine hardware system, several hardware devices such as Solr index server, collector, Chinese word segmentation device and searcher are installed, and the data interface is adjusted. On the basis of hardware equipment and database support, this paper uses the open source Apache Tika framework to obtain the metadata of rich text documents, implements word segmentation according to the rich text content and semantics, and calculates the weight of each keyword. Input search keywords, establish a text index, use BM25 algorithm to calculate the similarity between keywords and text, and output the search results of rich text according to the similarity calculation results. The experimental results show that the design system has high recall rate, high throughput, and the construction time of each data item index in different files is short, which improves the search efficiency and search accuracy.

Global Calculations of Beta-Decay Properties Based on the Fayans Functional

An effective approximation to a fully self-consistent global description of beta-decay properties of nuclei within the theory of finite Fermi systems is presented. It is based on describing the ground state properties within the energy density functional proposed by Fayans and coauthors (DF3) and on the continuum quasiparticle random-phase approximation (CQRPA). The accuracy of global DF3 $$+$$ CQRPA calculations is analyzed. For more than 200 (quasi)spherical nuclei with $$Z=18$$ to 51 having half-lives in the range of $$T_{1/2}<5$$ s, the experimental half-lives and delayed neutrons emission probabilities are described within a factor of two and three, respectively. A comparison is performed with the results of similar calculations based on state-of-the-art self-consistent models : the relativistic spherical RHB $$+$$ RQRPA approach and deformed finite-amplitude method (FAM) and HFB $$+$$ QRPA approaches, as well as the interacting shell model. A detailed analysis of beta-decay properties in the nickel isotopic chain that were obtained in various calculations allows us for determining basic mechanisms responsible for the sudden shortening of the half-lives that was found experimentally at RIKEN for isotopes heavier than the doubly magic $${}^{78}$$ Ni nucleus. These are the contributions of first-forbidden (FF) transitions and multiphonon configurations and spin inversion of the respective ground states. The acceleration effect in question is highly sensitive to the balance of the contributions of Gamow–Teller (GT) and FF transitions to the total beta-decay rate. It is shown that, in nickel isotopes, the ratio of these contributions takes different values before and after the neutron-shell crossing at $$N=50$$ .

Effects of various types of reflectors on the 99Mo production in the VVER-Ts reactor targets

The effects from introducing various types of reflectors in the VVR-Ts reactor core on the 99Мо production were analyzed. Earlier the effects of only the beryllium reflector on the VVR-Ts reactor core characteristics, such as reactivity margin, neutron flux in experimental channels, and activity of the accumulated 99Мо, were calculated. The calculations are based on a generated precision model of the core which comprises one experimental channel where targets are irradiated for the 99Мо production. The model was built using the SCALE code. The code allows a fairly broad range of calculations to be performed, from criticality estimation to radiological assessment tasks. As the result of the computational analysis of the model, such characteristics were obtained as the effective multiplication factor, the power density in the 99Мо production targets, the neutron flux in the target raw material, and the quantity of the produced 99Мо after 120 hours of irradiation. The data was compared with the results of similar calculations of the VVR-Ts reactor core parameters. Further, the list of the materials used extensively as the reactor core reflector or moderator was formed based on reference literature. A number of models were obtained and analyzed on its basis, in which the water space on the core periphery was substituted for the investigated materials.

E-Commerce User Type Recognition Based on Access Sequence Similarity

ABSTRACT In order to measure the similarity of non-equal length and non-numerical sequence effectively, in this paper, the access sequence similarity calculation method was proposed based on the characteristics of e-commerce user access sequence. The sliding window method was improved by increasing the similarity calculation of nodes and optimizing the sliding similarity calculation method. The key factor of Edit Distance on Real Sequences was optimized. It mainly includes the calculation method of increasing the similarity of nodes and optimizing the calculation method of sliding similarity; the calculation method of subcost in the editing distance of real sequences is optimized. Then, the optimized Edit Distance on Real Sequences was embedded into the improved sliding window method to replace the original distance calculation method. Based on the access sequence similarity calculation results, the clustering algorithm was used to get the e-commerce users type. The experimental results showed the following facts: The improved access sequence similarity algorithm can measure the similarity of non-numerical and non-equal length sequences more accurately; based on the similarity of access sequences, it is possible to divide the types of e-commerce users more effectively, besides the e-commerce users are mainly composed of young men, users’ online time shows obvious fragmentation characteristics, their online browsing behavior obeys long tail distribution, they still primarily buy hot items, and the e-commerce users can be divided into six categories.

О численной оценке эффективных характеристик периодических ячеистых структур с использованием балочных и оболочечных конечных элементов с помощью CAE Fidesys

Развитие аддитивных технологий (3D-печати) сделало возможным изготовление деталей и изделий регулярной пористой и ячеистой структуры (с целью облегчения конструкции). При этом характерный размер ячейки намного меньше масштаба целого изделия. Численные прочностные и смежные с ними расчёты подобных конструкций требуют предварительной оценки эффективных характеристик такой ячеистой структуры. В данной статье представлена методика численной оценки эффективных упругих характеристик регулярных ячеистых структур, основанная на численном решении краевых задач теории упругости на ячейке периодичности. К ячейке последовательно прикладываются различные периодические граничные условия в виде связей, наложенных на перемещения противоположных граней ячейки. Для каждого вида граничных условий решается краевая задача теории упругости, полученное в результате решения которой поле напряжений осредняется по объёму. Эффективные свойства ячеистого материала оцениваются в виде обобщённого закона Гука.В работе рассматриваются композиционные материалы на основе жёсткого решётчатого каркаса, заполненного более мягким материалом. Расчёты проводятся методом конечных элементов с помощью отечественной CAE-системы «Фидесис». При этом в ряде расчётов для моделирования решётчатого каркаса используются конечные элементы балочного типа. В некоторых расчётах, помимо каркаса и матрицы, учитывается наличие тонкого слоя связующего между ними. Этот слой моделируется при помощи конечных элементов оболочечного типа.Приводятся графики сравнения результатов расчётов композиционных материалов с решётчатым каркасом с моделированием каркаса балочными элементами и результатов аналогичных расчётов, в которых каркас моделируется трёхмерными конечными элементами. Также приводятся графики сравнения результатов расчётов, в которых слой связующего моделируется оболочечными элементами, с результатами аналогичных расчётов, в которых связующее моделируется трёхмерными элементами. Графики показывают, что при достаточно тонких элементах каркаса (либо при достаточно тонком слое связующего) результаты получаются довольно близкими, что подтверждает применимость балочных и оболочечных элементов для численного решения таких задач.

Point of Interest Matching between Different Geospatial Datasets

Point of interest (POI) matching finds POI pairs that refer to the same real-world entity, which is the core issue in geospatial data integration. To address the low accuracy of geospatial entity matching using a single feature attribute, this study proposes a method that combines the D–S (Dempster–Shafer) evidence theory and a multiattribute matching strategy. During POI data preprocessing, this method calculates the spatial similarity, name similarity, address similarity, and category similarity between pairs from different geospatial datasets, using the multiattribute matching strategy. The similarity calculation results of these four types of feature attributes were used as independent evidence to construct the basic probability distribution. A multiattribute model was separately constructed using the improved combination rule of the D–S evidence theory, and a series of decision thresholds were set to give the final entity matching results. We tested our method with a dataset containing Baidu POIs and Gaode POIs from Beijing. The results showed the following—(1) the multiattribute matching model based on improved DS evidence theory had good performance in terms of precision, recall, and F1 for entity-matching from different datasets; (2) among all models, the model combining the spatial, name, and category (SNC) attributes obtained the best performance in the POI entity matching process; and (3) the method could effectively address the low precision of entity matching using a single feature attribute.

Link prediction in recommender systems with confidence measures.

The link prediction aims at predicting missing or future links in networks, which provides theoretical significance and extensive applications in the related field. However, the degree of confidence in the prediction results has not been fully discussed in related works. In this article, we propose a similarity confidence coefficient and a confidence measure for link prediction. The former is used to balance the reliability of similarity calculation results, which might be untrustworthy due to the information asymmetry in the calculation, and also makes it easier to achieve the optimal accuracy with a smaller number of neighbors. The latter is used to quantify our confidence in the prediction results of each prediction. The experimental results based on the Movie-Lens data set show that prediction accuracy is improved when the similarity between the nodes is corrected by the similarity confidence coefficient. Second, the experiments also confirm that the confidence degree of the link prediction results can be measured quantitatively. Our research indicates that the confidence level on each prediction is determined by the amount of data used in the corresponding calculation, which can be measured quantitatively.

Link prediction in recommender systems based on multi-factor network modeling and community detection

Link prediction provides methods to estimate potential connections in complex networks, which has theoretical and practical significance for personalized recommendation and various other applications. Traditional collaborative filtering and other similar approaches have not utilized sufficient information on the community structure of networks. Therefore, this paper presents a link prediction model based on complex network modeling and community detection. In the approach, complex networks are constructed by considering the similarity among users' preference for genre selection, the similarity among users' rating distribution, and the similarity among items based on users' ratings. And the similarity calculation results are taken as weight of links as well as objects are considered as nodes in networks. On this basis, the community detection results can be obtained, and link prediction is performed with the community information considered. Multi-factor community detection based on node similarity improves the prediction process effectively and increases accuracy in our experiments. The result infers that users' behaviors, including rating an item and selecting an item over others, indicate a hidden community structure in the system, which can be used for link prediction and even for better understanding of complex systems.

Calculations of oxygen and humidity influence on properties of pernigraniline base polyaniline oligomers

In spite of extensive investigation and applications, influence of oxygen (O), and humidity on polyaniline (PANI) behaviour is not well understood. For this reason we have performed semi-empirical quantum mechanics, and ab-initio calculations of the pernigraniline base (PNB) PANI oligomers, of various lengths, before and after approach of H2O, O2, and hydroxyl (OH−) group, and attachment of OH− and O to various molecular positions. Structure, charge and electrostatic potential distribution, relevant energies and enthalpies, infrared and electronic spectra of the PNB tetramer equilibrium conformation, and their changes induced by specific OH−, and O attachments are determined. These results provide identification of the most probable positions for O2 and H2O approach to PNB_PANI, enthalpies of OH− and O attachments to them, changes of molecular properties induced by the attachments, and infrared and electronic modes that are most suitable for the attachments detection. The results are compared to the existing experimental data, and the results of similar calculations, and implications for the PNB_PANI applications are notified.

REPRODUCIBILITY OF THE BASIC X-RAY PARAMETERS OF LOWER EXTREMITY DEFORMATIONS IN CHILDREN WITH SKELETAL DYSPLASIA

Introduction: axial deformities in the lower extremities of children lead to an uneven distribution of the load in different compartments of the knee joint, which can contribute to the development of osteoarthritis. Regardless of the cause of their occurrence, the main goal of treatment is the restoration of the mechanical axis. Various calculation methods are used to determine the amount of deformity, its apex and the degree of required correction. The aim: to evaluate the reproducibility of the basic X-ray parameters characterizing the deformities of the lower extremities in the frontal plane in children with skeletal dysplasia based on the calculation of inter-rater reliability.Materials and methods: the article presents calculations of the main angulometric parameters of the knee joint (deviation of the mechanical axis — MAD, distal mechanical angle of the femur — mLDFA, proximal angle of the tibia — MPTA) in 18 patients with skeletal dysplasia (30 lower extremities) that had axial deformities of the lower extremities in the frontal plane at the level of the knee joint. The control group included the results of similar calculations of the angulometric parameters in 19 children (30 lower extremities) with valgus and varus deformities of the knee joint without skeletal dysplasia (idiopathic axial deformations, posttraumatic deformities, malformations of the lower limbs). The estimation of inter-expert reliability was made in the SPSSv. 23.Results: the analysis demonstrated that calculation of reference parameters in children without primary lesion of the growth plate has a high degree of inter-rater reliability: an intra-class correlation coefficient with a 95% confidence interval (ICC [95% CI]) when calculating the reference angles of mMPTA and mLDFA was 0.981% [0.971–0.991] and 0.993% [0.989–0.997] respectively, for MAD 0.996% [0.993–0.998]. When calculating the same parameters in children with skeletal dysplasia, the results differed. Thus, the intra-class correlation coefficient for the deviation of the mechanical axis was 0.861% [0.763–0.926] (which corresponds to the normal reproducibility of this parameter), for mMPTA — 0.586% [0.295–0.781], for mLDFA — 0.796% [0.653–0.892]. This indicates a low reproducibility and may lead to errors in the planning of correction of axial deformities of the lower limbs in children with skeletal dysplasia.Conclusion: when calculating the severity of axial deformities in the lower extremities in children with skeletal dysplasia, the most reproducible parameter is the determination of the deviation of the mechanical axis of the lower extremities as compared to the studied angulometric methods.

Calculations of optical properties of some molecules suitable for coating of nanoparticles for biological applications

Coating of nanoparticles by various molecules is promising way to modify their surfaces and extend their bio-functionality, and infrared (IR), and spectroscopy of electronic transitions at ultraviolet and visible (UV/VIS) wavelengths are suitable techniques to investigate details of their attachment at nanoparticle surface. In the present work structure and optical properties of dextran, chitosan, oleic acid and poly(ethylene glycol) have been investigated by semi-empirical quantum mechanics, and ab initio Hartree–Fock calculations using the HyperChem® software package (http://www.hyper.com). The equilibrium conformations, IR, and UV/VIS spectra of molecules of various lengths, before and after their attachment to the magnetite (111) surface are determined, and IR modes and UV/VIS transitions that change the most upon the molecules attachment identified. The results are compared to the existing experimental data and the results of similar calculations, and possible implications for biological applications of nanoparticles coated with the investigated molecules have been discussed.

Transition amplitudes, polarizabilities, and energy levels within optical wavelength of highly charged ions Sm14+and Sm13+

We discuss the possible search for optical transitions in Sm${}^{13+}$ and Sm${}^{14+}$ using ab initio calculations of differential dynamic polarizability. We calculate dynamic polarizability for $M1$ transition between first and second excited states of Sm${}^{14+}$. Transition amplitudes and energies within the optical range for states that contribute to the polarizability of the mentioned transition are presented. Employing simple analytical formula for polarizability data in the vicinity of a resonance and assuming that several values of the polarizability for different laser frequencies will be measured one can find the accurate position of the resonance. Results of similar calculations of amplitudes and energies of states that contribute to the polarizability of the $M1$ transition between ground and first excited states of Sm${}^{13+}$ are also presented.