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The paper describes the stages of paper production, considers the structure of a paper-making machine. Questions related to the proof and use of the Pontryagin’s maximum principle in the theory of optimal control are considered. Optimal paper web weight control system based on the Pontryagin’s maximum principle is presented. Adaptive learning methods for modeling nonlinear systems represent some of the latest advances in adaptive algorithms and machine learning techniques designed to model and identify nonlinear systems. Real-world problems always involve a certain degree of non-linearity, which makes linear models a suboptimal choice. This article may be of interest to research engineers and practitioners in the study and application of control systems using adaptive regulators. This book serves as an essential resource for researchers, graduate students and doctoral students working in the field of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, and computational intelligence. This book may also be of interest to the industry market and practitioners working with a wide range of nonlinear systems.

The design engineering is one of essential work in modern manufacturing environment. The optimization is principal technique to be used widely for searching the solution. However, primary process of optimization is to know the relation between design input parameters and target output. In this work, an artificial neural network (ANN) approach as an intelligent algorithm is proposed to construct the relation and also provides it in form of mathematic modeling. Even though the ANN modeling is so call a backblock due to difficulty to understand complicated equations, it is simply constructed by automate iteration process. A case of paper helicopter is used as an example of the application. The classical 2k Factorial design is used to provide an experiment plan to create training and testing data. 93 experiments are carried out. The architecture of ANN is set according to lowest Mean square error (MSE) of training and testing procedure. The result of 5-10-1 architecture has shown ability to accurately predict output, landing time, with MSE of 0.012. With such a highly quantitative accuracy of results, the developed model using the neural network approach can be used for finding the suitable input parameters to achieve a desired target output. In this case, the design of dimension (A) Depth of cut wing is 1.3 cm., (B) Length of wing is 12.9 cm., (C) Length of body is 9.0, (D) Width of body is 2.0 cm., and (E) Depth of cut body is 0 cm. yield the lowest area of a paper helicopter that can meet the target landing time, 2.85 + 5% second.

This article introduces the use of PCI software production day draw satellite is projective like production process, analyzes the key technologies in the production, summarizes the Suggestions to improve the quality of results, strengthen quality control method is proposed, for the day draw satellite orthogonal projection as mass production work has carried on the beneficial exploration.

The article deals with the issues and methods of teaching translation and interpretation of scientific and technical papers to engineering students from a linguistic point of view. The authors describe the concept and special features of technical translation as a professional activity compared to different kinds of translation. The paper analyzes stylistic, lexical and phraseological, and grammatical peculiarities of scientific and technical papers. Moreover, the authors suggest the main techniques of translating scientific and technical papers such as direct and indirect translation methods.

The contributions on technology are summarized.

A total of 14 contributions were presented in the Theory and Modelling sessions at EC-17. One Theory and Modelling paper was included in the ITER ECRH and ECE sessions each. Three papers were in the area of nonlinear physics discussing parametric processes accompanying ECRH. Eight papers were based on the quasi-linear theory of wave heating and current drive. Three of these addressed the application of ECCD for NTM stabilization. Two papers considered scattering of EC waves by edge density fluctuations and related phenomena. In this summary, we briefly describe the highlights of these contributions. Finally, the three papers concerning modelling of various aspects of ECE are reported in the ECE session.

The paper based on the analysis of the working conditions of railway transport shows that, ceteris paribus, an increase in actual durability and mean time before failure of rolling stock units is obtained through maintenance of wheelsets, especially during logistic processes on nonmechanized humps. One of the main causes for the service life decrease of wheelsets is brake damage. To eliminate such brake damage on highways, on-board braking dis-tance regulators mounted on the locomotive are used. In the hump yards, using such systems is not possible, since under marshalling, cars are detached from the locomotive. In this regard, an industrial challenge turns up to design a similar in purpose braking distance regulator for humps through skidding. To solve this problem, we developed a method of controlling the speed of cars to be sorted, which complements the widely used technology of the shoe braking and avoids the formation of one-way sliders. The paper presents a skid adjuster, which excludes brake damage to the rolling stock wheels by the slides on the humps using the shoe braking techniques. The motion equation of the rolling stock equipped with a skid adjuster on the hump tracks is developed. In the result of this study, an equation of car motion in the system of “rolling stock Hughes regulator way” allowing to enter the working elements of Hughes controller to an existing and debugged algorithm of any slides with minimal change it.

The parameters of electrical network modes often do not meet the requirements of Russian GOST 32144-2013 and the guidelines of Vietnam. In the actual operating conditions while there is the non-sinusoidal mode in electrical networks voltage and current harmonics are present. Harmonics result in overheating and damage of power transformers since they cause additional active power losses. Additional losses lead to the additional heat release, accelerating the process of insulating paper, transformer oil and magnetic structure deterioration consequently shortening the service life of a power transformer. In this regard there arises a need to develop certain scientific methods that would help demonstrate that low power quality, for instance could lead to a decrease in the electrical equipment service life. Currently we see a development of automated systems for continuous monitoring of power quality indices and mode parameters of electrical networks. These systems could be supplemented by characteristics calculating programs that give out a warning upon detection of the adverse influence of voltage and current harmonics on various electrical equipment of both electric power providers and electric power consumers. A software program presented in the article may be used to predict the influence of voltage and current harmonics on power transformers.

The amount of documents increases so fast. Those documents exist not only in a paper based but also in an electronic based. It can be seen from the data sample taken by the SpringerLink publisher in 2010, which showed an increase in the number of digital document collections from 2003 to mid of 2010. Then, how to manage them well becomes an important need. This paper describes a new method in managing documents called as inverted files system. Related with the electronic based document, the inverted files system will closely used in term of its usage to document so that it can be searched over the Internet using the Search Engine. It can improve document search mechanism and document save mechanism.

This paper proposes a modelling approach for simulating mechanical ventilators for intensive care units (ICUs) The shortage of ventilators during the coronavirus disease 2019 (COVID-19) pandemic has focused attention on their design and performance The proposed modelling approach consists in using the Mathworks® Simulink software tool and the SimScape Fluids (gas) library, so as to use well-established subroutines to simulate all the pneumatic components of typical ventilators for ICUs, such as the pressure reducing valves, pressure relief valves, check valves, tanks, ON\OFF and proportional directional valves, etc The patient is simulated by setting the values of lung compliance and pressure losses occurring in the trachea The proposed modelling approach is used in this paper to simulate a pneumatic scheme employed in some commercial ventilators The model allows a very accurate prediction of fundamental parameters, such as the inspiratory flow rate, the inspiratory pressure, the end-expiratory pressure Since the software interface is user-friendly, it can easily be used by manufacturers to correctly choose the geometrical and operating parameters of the components during the design stage or to assess different scenarios © 2020 The Authors, published by EDP Sciences

In this paper, we discuss a particular class of Nash games, where the participants of the game (the players) are divided into two groups (leaders and followers) according to their position or influence on the other players. Moreover, we consider the case, when the leaders’ and/or the followers’ game can be described as a potential game. This is a subclass of Nash games that has been introduced by Monderer and Shapley in 1996 and has beneficial properties to reformulate the bilevel Nash game. We develope necessary and sufficient conditions for Nash equilibria and present existence and uniqueness results. Furthermore, we discuss some Examples to illustrate our results. In this paper, we discussed analytical properties for multi-leader follower potential games, that form a subclass of hierarchical Nash games. The application of these theoretical results to various fields of applications are a future research topic. Moreover, they are meant to serve as a starting point for the developement of efficient numerical solution methods for multi-leader-follower games.

This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar reconstruction tasks in the LHC. In this paper, a multihead attention message passing network is used to classify the relationship between detector hits by labelling graph edges, determining whether hits were produced by the same underlying particle, and if so, the particle type. The trained model is 84% accurate overall, and performs best on the EM shower and muon track classes. The model's strengths and weaknesses are discussed, and plans for developing this technique further are summarised., 7 pages, 3 figures, submitted to the 25th International Conference on Computing in High-Energy and Nuclear Physics

Food safety is a matter of national importance, and it is important to establish and improve a whole process food safety supervision system with high standard. Along with the advent of the era of big data, to achieve this goal requires not only the reform and optimization of the old regulatory approach needs to establish the idea of information-based supervision, and actively apply big data technology to food safety testing. In this paper, we introduce the current situation of food safety in society, analyse the shortcomings of current food safety supervision and the challenges faced in the era of big data, discuss the feasibility of using big data for food safety testing with big data technology as the core, and give the design idea of establishing a corresponding food safety subject database. This paper takes food safety testing as the foothold and innovatively combines big data with food safety testing, with a view to providing reference for food safety regulatory authorities and promoting the healthy development of the food industry.

This paper introduces the development course of cryosurgery, mechanism, advantages and disadvantages, application scope, the analysis of the current world advanced the development of cryogenic surgical instruments and its principle and performance, found that at present, the development of the cryoablation equipment mainly for the treatment of diseases such as cancer such heavy research, thus ignore the crowd larger quantity of the treatment of skin disease research. cryopen are introduced in this paper to solve small pathological tissues such as skin disease treatment. we study a new type of freezing and melting equipment, named cryopen. at the same time, the simulation of treating abnormal skin is completed effectively. The results show that cryopen is very good for the treatment of abnormal skin. The future development of small cryoablation equipment is also put forward.

Nuclear fuel cycle scenario study can be of benefit for decision-making in nuclear industry development. However, due to the lack of knowledge about the future, many scenario studies are subject to uncertainties. As a result, some parameters may be disrupted. Energy production of an entire nuclear fleet of interest is such a parameter. Its disruptive decline has a strong impact on the results of scenario studies. Resilience study against disruption of decline in energy production is required to anticipate possible failures of scenario studies. In such a resilience study, a large number of scenario trajectory simulations with different modes of decline are expected. It is too difficult to set the values of all scenario parameters in each trajectory manually. As a solution, a method is proposed in this paper to reduce the number of input parameters. A set of rules has been implemented as an intermediate layer between the decision-makers and the scenario code to drive the evolution of a nuclear fleet. In this case, a trajectory can be fully characterized by a few parameters. This method has been applied to a simplified academic nuclear fleet with two different modes of decline in energy production. The simulation results showed that the developed method is feasible. One should note that the scenario model in this paper is only used for academic purposes and does not correspond to any industrial strategy or policy.

The paper considers possible aspects of unmanned aerial vehicles (UAVs) to predict and prevent dangerous situations associated with floods, waterlogging, and stream rise in the territories of settlements in modern conditions. Besides, a historical analysis of such cataclysms was carried out for the period from 2019 to 2020, which deserves the special attention of scientists. The relevance of the paper is undoubted, since the symbiosis of nature and man gives rise to destructive phenomena against the background of an incorrect interaction of these two units. The paper is divided into 5 main sections, which include: introduction, history of floods, possible use of UAVs in water accidents, and further actions after the work of UAVs is done and the conclusions.

Sentiment classification is one of the hottest research areas among the Natural Language Processing (NLP) topics. While it aims to detect sentiment polarity and classification of the given opinion, requires a large number of aspect extractions. However, extracting aspect takes human effort and long time. To reduce this, Latent Dirichlet Allocation (LDA) method have come out recently to deal with this issue.In this paper, an efficient preprocessing method for sentiment classification is presented and will be used for analyzing user’s comments on Twitter social network. For this purpose, different text preprocessing techniques have been used on the dataset to achieve an acceptable standard text. Latent Dirichlet Allocation has been applied on the obtained data after this fast and accurate preprocessing phase. The implementation of different sentiment analysis methods and the results of these implementations have been compared and evaluated. The experimental results show that the combined uses of the preprocessing method of this paper and Latent Dirichlet Allocation have an acceptable results compared to other basic methods.

Microclimate for cultural heritage plays a fundamental role in the degradation process of artefacts exhibited in museums. Generally, the Indoor Air Quality (IAQ) monitoring inside museums is based on conventional measurements of thermo-hygrometry parameters and longtime averaged measurements of atmospheric pollutants’ concentration. Unfortunately, all these approaches require electric supply and are usually characterized by a noticeable visual impact on the exhibition space, which clearly negatively affects the visitors’ experience. This paper intends to revisit and discuss a methodology (and its test application on field, to estimate the risk of damage of three artefacts displayed in an old museum of Palermo – Italy) perhaps prematurely underestimated that could usefully be re-proposed in particular contexts in which it is necessary to be careful to be as less invasive as possible, as in the case of museums housed in buildings of particular historical-cultural prestige. The discussed approach uses a non-destructive (or minimally invasive, at least) technique consisting in using two types of coupons, bi-metallic and marble ones, that allows an off-line monitoring of the indoor air aggressiveness inside museums, while avoiding consuming electricity and undesirable visual impacts on the site. Specifically, the estimated coupon damage is regarded as gauge to air aggressiveness, in order to provide an early warning of the risk of damage for the artefacts made of materials similar to those which the coupons are made of. Based on the considerations reported in the paper, the indirect evaluation of the air chemical aggressiveness through the assessment of the bi-metallic and marble coupons’ erosion seems to still candidates itself as a feasible method to be applied in complex exhibition scenes.

The application of artificial intelligence in environmental design has entered a stage of rapid development, artificial intelligence in environmental design tools, methods, expression, as well as the expansion of design content, the richness of design language and other aspects have produced a wide range of changes. From the perspective of artificial intelligence in environmental design, this paper discusses the future trend and possible revolutionary changes of artificial intelligence in environmental design. This paper combs the application of artificial intelligence in environmental design, analyzes the design works with wide influence, and discusses the value and significance of artificial intelligence in applied environmental design, as well as its possible future development trend. The application of artificial intelligence in environmental design is a great change from design means to design content. From the interactive ability, virtual ability, to the integration of big data, all are new opportunities and challenges brought by the ability of artificial intelligence to environmental design. In response to such changes, environmental art design practitioners should establish a more systematic, three-dimensional and data-based design activity system and a broader design theory system.

Recent achievements in high-performance computing significantly narrow the performance gap between single and multi-node computing, and open up opportunities for systems with remote shared memory. The combination of in-memory storage, remote direct memory access and remote calls requires rethinking how data organized, protected and queried in distributed systems. Reviewed models let us implement new interpretations of distributed algorithms allowing us to validate different approaches to avoid race conditions, decrease resource acquisition or synchronization time. In this paper, we describe the data model for mixed memory access with analysis of optimized data structures. We also provide the result of experiments, which contain a performance comparison of data structures, operating with different approaches, evaluate the limitations of these models, and show that the model does not always meet expectations. The purpose of this paper to assist developers in designing data structures that will help to achieve architectural benefits or improve the design of existing distributed system.

Under the guidance of the new strategic objectives of the power grid company, it is necessary to inject innovative vitality into personnel training, capital investment, and technological progress in order to achieve the goal of increasing the value of power grid companies. This paper analyzes the coupling relationship of “innovation chain, talent chain, technology chain, capital chain and value chain”, and establishes the evaluation index system of “five chain” integration effectiveness. Then, the traditional Analytic Hierarchy Process (AHP) is improved, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model is constructed. Finally, three provincial power grid companies are selected for example analysis, and the innovation effectiveness ranking of each company is obtained, which verifies the effectiveness of the model proposed in this paper.

In nowadays the pneumatic controlled systems are widely used in industrial applications where valves must be operated, where there is a fire ignition risk, or in different automation systems where a positioning action is desired. The paper presents the experimental results of a pneumatic actuator controlled by a proportional control valve. The goal of the paper is to compare the experimental results with the numerical simulation results and to improve the mathematical model associated with the experiment.

Companies are under increasing pressure from customers, competitors, limited resources, etc. These conditions oblige companies to permanently improve their organizational structure and the activities of all system’s flows. The paper analyses the types of Kanban systems, in the broader context of the enterprise systems. The most important reference architectures were analysed (with the emphasis on the modules dedicated to flow description) and the standards that allow the activity modelling of a manufacturing enterprises. Starting from this context, the paper describes three models of Kanban systems that are specific to companies with different information systems development. Models are: Push production with withdrawal Kanban; Pull production with withdrawal Kanban and production Kanban triggered by Kanban board; Pull production with withdrawal Kanban and production Kanban triggered by the dispatch to the customers. The models are graphically described using Value Stream Map (VMS) symbols. These models are useful in the development and improvement of production flows.

Greenhouse is an important part of facility agriculture and a typical application scenario of modern agricultural technology. The greenhouse environment has the characteristics of nonlinearity, strong coupling, large inertia, and multiple disturbances. There are many environmental factors and it is a typical complex system [7]. In smart greenhouses, control commands are mostly triggered by complex events with multi-dimensional information. In this paper, by building the aggregation structure of complex events in the greenhouse, the technology is applied in the greenhouse as a whole. The core innovations of this paper are as follows: through the analysis of the information transmission process in the greenhouse, combined with the characteristics of the scene, a CEP information structure with predictive modules is formed, which is conducive to the popularization and application of CEP technology in the agricultural field. Pointed out the importance of extreme conditions in the prediction of the greenhouse environment for model evaluation. By improving the loss function in the machine learning algorithm, the prediction performance of a variety of algorithms under this condition has been improved. Applying CEP technology to intelligent greenhouse control scenarios, a set of practical complex event processing systems for greenhouse control has been formed.

This paper takes the teaching area unit space of primary and secondary schools as the main research object, analyzes, discusses and studies the reasonable use size of teaching unit space, commonly used space combination mode and internal detail design of education space, analyzes the actual use of various space units, and discusses the advantages and disadvantages of different design methods. Finally, from the perspective of teachers and students, combined with the analysis of specific project cases, this paper puts forward the optimization design strategy of school teaching unit space in line with the use requirements and architectural aesthetics.

This paper sums up six features and three functions as the characteristics of graduation design, which is the last link of undergraduate education. And through the analysis of each link in the graduation design process, this paper gives an improvement method for the graduation design based on these characteristics. Finally, an application example of this improvement in our university is given.

The utilization of regenerative braking energy is of great significance to the energy saving of subway. Therefore, this paper proposes an optimization method for scheduling and control integration, which not only adjusts the timetable but also optimizes the speed curves of trains. When there is a train braking, this method will try to find a train that accelerates to absorb the regenerative energy generated by the braking train. Firstly, this paper establishes the timetable energy saving optimization model, based on which the speed curves will be optimized. Furthermore, we design a scheduling optimization algorithm based on genetic algorithm, and optimizes speed curves of trains by binary search method to obtain a good solution. Finally, simulations are given using the real data of Beijing Metro Line 4 to evaluate the proposed method, and the results show that the integrated scheduling and control optimization method can reduce energy consumption by 15.18%. In the random disturbance simulations, the proposed method shows good robustness, which makes it possible to apply this method to the real subway operations.

Crowdsourcing logistics mode is the product of sharing economy by integrating idle resources to reduce the operating cost and improve the efficiency of enterprises. Taking the service quality of crowdsourcing logistics as the research object, this paper analyzes the key influencing factors of the service quality of crowdsourcing logistics, and constructs a crowdsourcing logistics service quality evaluation index system with 4 first level indicators and 15 second level indicators. At the same time, by using AHP and entropy weight method, The paper select dada and Renren express to evaluate their service quality. Through the case analysis of the two express companies’ service quality, the paper draw the conclusion that safety is still the most concerned factor in the evaluation of crowdsourcing logistics service quality at this stage.

The electricity consumption pattern is being increased day by day. Currently, network operators are moving towards renewable energy resources and applying demand response programs. However, the small and medium scale consumers and producers are needed to be aggregated and participate in the electricity markets as a unique resource. This paper proposes an optimization-based community model for aggregating the small scales consumers and producers. The model includes a central controller, which is considered as an aggregator, and several local community managers to keep the network balanced locally. Furthermore. real-time simulation approach and several real devices as hardware-in-the-loop are used to validate the system under practical challenges. The results of the paper reveal a gap between the simulation and experimental results and prove the performance of system in real-time mode using actual devices., This work has received funding from Portugal 2020 under SIMOCE project, from H2020 project DOMINOES, and from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project UIDB/00760/2020, and CEECIND/02887/2017.

Nowadays, the international society began to see clearly the impact of neglecting the environmental aspect in our lives, especially the issue of global warming. This paper aims in the first degree to minimize the carbon emission by vehicles and in doing so help to reduce the pollution ratio that is increasing day by day. In the home care sector, a patient requires from a health structure offering home care services one or many services to be done at home. For this purpose a health staff is mobilized to provide these services and must be done optimally. Many papers dealing with this kind of problems are suggesting that the way to optimize the problem encountered efficiently is to use the resources put in place to minimize the total travelled distance, but in this perspective, the study prioritizes the reduction and minimizing the fuel consumption. To answer all this questions, an exploration and an investigation of the problems addressed in the literature is performed, after that a mathematical formulation of the problem and two metaheuristics methods are proposed to resolve this problem. In the end, a comparison of the results of the two methods is presented.

There are a large number of distribution network construction projects with different types, and a large number of complex data relationships are generated in the construction process. This paper combs the key management and control indicators of distribution network construction projects, and constructs the management and control index system of each stage of the project. Based on Apriori algorithm, this paper studies the relationship between the key management and control indicators, and provides reference for the management and control of distribution network construction.

Prefabricated construction becomes an increasingly important construction mode especially for buildings that require a short construction time. The construction of Huoshenshan Hospital shows how efficient prefabricated construction could be. In order to provide a clearer blueprint for how to improve time performance in prefabricated construction, this paper identifies 13 important critical success factors associated with time performance and groups them into five categories—project planning and design, supply chain, techniques, teamwork, and external influences. The findings of this paper provide a better understanding of time management in prefabricated construction, which can help to develop appropriate strategies to improve productivity.

This paper proposes a hybrid financial time series forecast model based on LSTM and LightGBM, namely LSTM_LightGBM model. Use the LightGBM model to train the processed stock historical data set, and save the training results. Then the opening price, closing price, highest price, lowest price, trading volume and adjusted closing price are separately input into the LSTM model for prediction. The prediction result of each attribute is used as the test set of the prediction after LightGBM training. Constantly adjust the parameters of each model, and finally get the optimal stock price forecast model. The model is validated with the rise and fall of AAPL stock. Through the comparison of evaluation index root mean square error RMSE, mean absolute error MAE, prediction accuracy Accuracy and f1_score. It is found that the LSTM_LightGBM model exhibits stable and better prediction performance in the stock prediction. That is to say, the LSTM_LightGBM model proposed in this paper is stable and feasible in the stock price fluctuation forecast.

This paper presents the concept of building full-fledged sea convoys, which include unmanned ships. Advantages of this approach to combining unmanned ships over those where the ship is considered as a separate unit are considered. The scheme of distribution (combining) of computing power inside the convoy is given. In this paper, a scheme is considered when the crew is present only on the lead ship. However, this does not mean that all other ships in the convoy should be only unmanned. It doesn’t matter when considering this concept. The paper also proposes an algorithm for determining obstacles using optical sensors. The aspects of information security in such convoys are also considered. Particular attention is paid to the investigation of computer incidents on unmanned ships.

A single-server queueing system with negative customers is considered in this paper. One positive customer will be removed from the head of the queue if any negative customer is present. The distribution of the interarrival time for the positive customer is assumed to have a rate that tends to a constant as time t tends to infinity. An alternative approach will be proposed to derive a set of equations to find the stationary probabilities. The stationary probabilities will then be used to find the stationary queue length distribution. Numerical examples will be presented and compared to the results found using the analytical method and simulation procedure. The advantage of using the proposed alternative approach will be discussed in this paper.

This paper deals with study of wind energy conversion system when it is interconnected with the grid. Main objective of the paper is to improve the quality of the power when wind energy system is linked with the non-linear loads. In this work DSTATCOM (FACTS Device) is used as a shunt active controller which used to reduce harmonics, when grid is interconnected with the non-linear load. In this work a new methodology is proposed i.e., Fuzzy Logic technique is integrated in the control circuit of DSTATCOM that helps to compare the reference voltage and output voltage of grid in order to minimize the error and improve power quality

Cancer has been described as a diverse illness with several distinct subtypes that may occur simultaneously. As a result, early detection and forecast of cancer types have graced essentially in cancer fact-finding methods since they may help to improve the clinical treatment of cancer survivors. The significance of categorizing cancer suffers into higher or lower-threat categories has prompted numerous fact-finding associates from the bioscience and genomics field to investigate the utilization of machine learning (ML) algorithms in cancer diagnosis and treatment. Because of this, these methods have been used with the goal of simulating the development and treatment of malignant diseases in humans. Furthermore, the capacity of machine learning techniques to identify important characteristics from complicated datasets demonstrates the significance of these technologies. These technologies include Bayesian networks and artificial neural networks, along with a number of other approaches. Decision Trees and Support Vector Machines which have already been extensively used in cancer research for the creation of predictive models, also lead to accurate decision making. The application of machine learning techniques may undoubtedly enhance our knowledge of cancer development; nevertheless, a sufficient degree of validation is required before these approaches can be considered for use in daily clinical practice. An overview of current machine learning approaches utilized in the simulation of cancer development is presented in this paper. All of the supervised machine learning approaches described here, along with a variety of input characteristics and data samples, are used to build the prediction models. In light of the increasing trend towards the use of machine learning methods in biomedical research, we offer the most current papers that have used these approaches to predict risk of cancer or patient outcomes in order to better understand cancer.

Low- and medium-frequency noise from ship cabins is difficult to control effectively. Excessive noise can seriously affect the acoustic stealth performance of ships. A novel membrane-type acoustic metamaterial is proposed in this paper with light weight and good sound insulation performance at low frequencies. The sound insulation performance of the metamaterial structure is analysed by using the acoustic-solid coupling module in COMSOL software. Then, the ability to change the sound insulation performance of membrane-type acoustic metamaterials with cell structure and material parameters is obtained. The research results in this paper provide powerful technical support for noise control in ship cabins.

In this paper, we extract spectral image features from a hyperspectral image database, and use big data technology to classify spectra hierarchically, to achieve the purpose of efficient database matching. In this paper, the LDMGI (local discriminant models and global integration) algorithm and big data branch definition algorithm are used to classify the features of the hyperspectral image and save the extracted feature data. Hierarchical color similarity is used to match the spectrum. By clustering colors, spectral information can be stored as chain nodes in the database, which can improve the efficiency of hyperspectral image database queries. The experimental results show that the hyperspectral images of color hyperspectral images are highly consistent and indistinguishable, and need to be processed by the machine learning algorithm. Different pretreatment methods have little influence on the identification accuracy of the LDMGI model, and the combined pretreatment has better identification accuracy. The average classification accuracy of the LDMGI model training set is 95.62%, the average classification accuracy of cross-validation is 94.36%, and the average classification accuracy of the test set is 89.62%. Therefore, using big data analysis technology to process spectral features in hyperspectral image databases can improve query efficiency and more accurate query results.

Increasing the production capacity of ports is seen as one of the most significant goals for the development of maritime transport infrastructure, which requires the use of adequate forecasting methods. The problem of choosing methods of management in transport in conditions of instability of cargo flows, non-stationary functioning, the need for digitalization and transformation of processes and technologies is of particular importance. Taking advantage of the process approach in the management of seaport development, such as flexibility and transparency, is becoming an effective way to increase the productivity and efficiency of maritime transport in general. The paper presents the author’s presentation of the peculiarities of the process management of the seaport development. The use of the concept of modularity in managing the development of a seaport through a system of business processes is proposed. A method for assessing the significance of the seaport business processes for achieving its goals from the standpoint of their further optimization is presented. The research results presented in the paper were obtained on the basis of the description and economic and mathematical modeling of the basic business processes that form the process outputs. Using the seaport of Baku as the example, predictive models of cargo flows are described.

This paper describes the development and experimental study of a software and hardware complex designed for studying the conductive tracks of printed circuit boards. In the course of this development, a subminiature eddy-current transducer and a measuring system capable of performing measurements using the newly developed transducer were created. The paper contains descriptions of the main parameters of the developed measuring system, and also presents the results of experiments conducted with various printed circuit boards, both with defect-free and those with artificial model defects. These experiments made it possible to confirm the possibility of using the developed measuring system and eddy-current transducer for controlling the conductive tracks on printed circuit boards and determining their quality.

The construction of index system is the basis of equipment system contribution rate evaluation, and is also one of the main contents of equipment test and appraisal. This paper discusses the concept of systems contribution rate, introduces the evaluation process of system contribution rate of information system equipment, and gives the construction principles and ideas of information system equipment system contribution rate evaluation index system. Then, referring to the theory of operational loop, the evaluation index system of system contribution rate is given from the perspectives of system capability and system effectiveness. The evaluation index of this paper can provide decision support for the development of equipment planning system.