bluuebunny/crossref_metadata_2025 huggingface dataset:
Portuguese media representations of nuclear facilities in Almaraz, Spain: beyond borders and risk perception (Representaciones en los medios portugueses de las plantas nucleares en Almaraz, España: más allá de las fronteras y la percepción del riesgo)
Authors: Batel Susana , Pataco Lúcia
Published: October 2019

The attitudes and beliefs behind people’s responses to nuclear facilities has been since the 1970s one of the main concerns of environmental psychology and related disciplines. However, analyses have mainly focused on (1) understanding how risk perception and the lack of procedural and distributive justice in the relationship between local communities and authorities and developers impact those attitudes and beliefs, and (2) the perceptions of publics living within the same borders as the facilities. Less attention has been given to how the deployment of nuclear facilities affects communities beyond the border, and, relatedly, can be impacted upon by other intergroup relations and processes, such as more symbolic dimensions of justice. This paper aims to offer a preliminary exploration of how those intergroup processes might play a role in people’s attitudes and beliefs regarding nuclear energy, based on an analysis of the Portuguese media representations of nuclear facilities in Almaraz, Spain. The implications of these analyses for both energy policy and environmental psychology will be discussed.
Risk perception and organizational capacity building in the Azores (Percepción del riesgo y desarrollo organizacional de capacidades de las Azores)
Authors: Morgado-Pereira Sofia , Paim-Pacheco Mariana , Estrela-Rego Isabel
Published: October 2019

At an organizational level, effective communication and coordination are vital elements of capacity building to foster disaster resilience. The aim of this study is to verify differences in volcanic hazard risk perception and knowledge of Civil Protection agents with responsibilities in disaster management in the Azores, assuming that these can influence communication. Risk perception and knowledge were evaluated on a convenience sample of 373 participants. Results indicate moderate levels of volcanic risk perception, lack of knowledge and significant differences in the risk perception of agents from the Civil Protection System. Questions on the efficacy of risk communication between agents, the dissemination of information pertaining to volcanic risk, the dissemination of information on emergency and preparedness measures implemented and on the forms of communication between Civil Protection agents were raised. This study can be regarded as a first effort to analyse the capacity of public officials in the Azores to deal with a volcanic event and points to areas to enhance if resilience is to be promoted.
Optimal phase estimation with photon-number difference measurement using twin-Fock states of light*
Authors: Xu J H , Wang J Z , Chen A X , Li Y , Jin G R
Published: October 2019

Quantum phase measurement with multiphoton twin-Fock states has been shown to be optimal for detecting equal numbers of photons at the output ports of a Mach–Zehnder interferometer (i.e., the so-called single-fringe detection), since the phase sensitivity can saturate the quantum Cramér–Rao lower bound at certain values of phase shift. Here we report a further step to achieve a global phase estimation at the Heisenberg limit by detecting the particle-number difference (i.e., the

J
^

z

measurement). We show the role of experimental imperfections on the ultimate estimation precision with the six-photon twin-Fock state of light. Our results show that both the precision and the sensing region of the

J
^

z

measurement are better than those of the single-fringe detection, due to combined contributions of the measurement outcomes. We numerically simulate the phase estimation protocol using an asymptotically unbiased maximum likelihood estimator.
Optical-induced dielectric tunability properties of DAST crystal in THz range*
Authors: Xu De-Gang , Zhu Xian-Li , Wang Yu-Ye , Li Ji-Ning , He Yi-Xin , Pang Zi-Bo , Cheng Hong-Juan , Yao Jian-Quan
Published: October 2019

The optical-induced dielectric tunability properties of DAST crystal in THz range were experimentally demonstrated. The DAST crystal was grown by the spontaneous nucleation method (SNM) and characterized by infrared spectrum. With the optimum wavelength of the exciting optical field, the transmission spectra of the DAST crystal excited by 532 nm laser under different power were measured by terahertz time-domain spectroscopy (THz-TDS) at room temperature. The transmitted THz intensity reduction of 26 % was obtained at 0.68 THz when the optical field was up to 80 mW. Meanwhile, the variation of refractive index showed an approximate quadratic behavior with the exciting optical field, which was related to the internal space charge field of photorefractive phenomenon in the DAST crystal caused by the photogenerated carrier. A significant enhancement of 13.7 % for THz absorption coefficient occurred at 0.68 THz due to the photogenerated carrier absorption effect in the DAST crystal.
Metabasin dynamics of supercooled polymer melt*
Authors: Li Jian , Zhang Bo-Kai
Published: October 2019

We employ molecular dynamic simulation to investigate metabasin dynamics for supercooled polymer melt. We find that, in a small system, the α-relaxation process is composed of a few crossing events that the monomers hops from one metabasin to another. Each crossing event is very rapid and involves a democratic movement of many particles, whereas such collective motion is not string-like. Evaluation on the contributions of metabasin exploration and democratic movement shows that the structural relaxation is mostly governed by the latter. Our calculated results show that the metabasin–metabasin transitions are not the main reason of spatially dynamical heterogeneity. It is different from the binary Lennard–Jones mixture model in which the metabasin–metabasin transitions are relevant for the spatially dynamical heterogeneity.
Controllable laning phase for oppositely driven disk systems*
Authors: Liu Lin , Li Ke , Zhou Xiao-Lin , He Lin-Li , Zhang Lin-Xi
Published: October 2019

A two-dimensional binary driven disk system embedded by impermeable tilted plates is investigated through nonequilibrium computer simulations. It is well known that a binary disk system in which two particle species are driven in opposite directions exhibits jammed, phase separated, disordered, and laning states. The presence of tilted plates can not only advance the formation of laning phase, but also effectively stabilize laning phase by suppressing massively drifting behavior perpendicular to the driving force. The lane width distribution can be controlled easily by the interplate distance. The collective behavior of driven particles in laning phase is guided by the funnel-shaped confinements constituted by the neighboring tilted plates. Our results provide the important clues for investigating the mechanism of laning formation in driven system.
Thickness-modulated in-plane Bi2O2Se homojunctions for ultrafast high-performance photodetectors*
Authors: Hong Cheng-Yun , Huang Gang-Feng , Yao Wen-Wen , Deng Jia-Jun , Liu Xiao-Long
Published: October 2019

Bi2O2Se thin film could be one of the promising material candidates for the next-generation electronic and optoelectronic applications. However, the performance of Bi2O2Se thin film-based device is not fully explored in the photodetecting area. Considering the fact that the electrical properties such as carrier mobility, work function, and energy band structure of Bi2O2Se are thickness-dependent, the in-plane Bi2O2Se homojunctions consisting of layers with different thicknesses are successfully synthesized by the chemical vapor deposition (CVD) method across the terraces on the mica substrates, where terraces are created in the mica surface layer peeling off process. In this way, effective internal electrical fields are built up along the Bi2O2Se homojunctions, exhibiting diode-like rectification behavior with an on/off ratio of 102, what is more, thus obtained photodetectors possess highly sensitive and ultrafast features, with a maximum photoresponsivity of 2.5 A/W and a lifetime of 4.8 μs. Comparing with the Bi2O2Se uniform thin films, the photo-electric conversion efficiency is greatly improved for the in-plane homojunctions.
Ultra-high voltage 4H-SiC gate turn-off thyristor for low switching time*
Authors: Liu Qing , Pu Hong-Bin , Wang Xi
Published: October 2019

An ultra-high voltage 4H-silicon carbide (SiC) gate turn-off (GTO) thyristor for low switching time is proposed and analyzed by numerical simulation. It features a double epitaxial p-base in which an extra electrical field is induced to enhance the transportation of the electrons in the thin p-base and reduce recombination. As a result, the turn-on characteristics are improved. What is more, to obtain a low turn-off loss, an alternating p+/n+ region formed in the backside acts as the anode in the GTO thyristor. Consequently, another path formed by the reverse-biased n+–p junction accelerates the fast removal of excess electrons during turn-off. This work demonstrates that the turn-on time and turn-off time of the new structure are reduced to 37 ns and 783.1 ns, respectively, under a bus voltage of 8000 V and load current of 100 A/cm2.
Influence of the Thermodynamic Characteristics of the Combustion Process on Vehicle Emissions in Spark-Ignition Engines
Authors: Smolenskaya N M , Smolenskii V V
Published: October 2019

The paper deals with the influence of the thermodynamic characteristics of the combustion process on toxicity in spark-ignition engines using the example of the UIT-85 single-cylinder unit. The studies were conducted on compressed natural gas and compressed natural gas with the addition of hydrogen gas. Also shown is the relationship of exhaust toxicity with the flame conductivity characteristic, reflecting the intensity of the combustion process in the flame front.
Cyber and Physical Systems Technology Classification for Production Activity of the Industry 4.0 Smart Factory
Authors: Zakoldaev D A , Korobeynikov A G , Shukalov A V , Zharinov I O
Published: October 2019

The task is to create a company of new type (a smart factory) for the Industry 4.0. A smart factory is for production cycle of the item designing manufacturing. A smart factory is equipped with cyber and physical equipment controlled with computerized system which is a part of the company digital infrastructure. Cyber and physical production apply innovative production technologies for the item life cycle supported in a smart factory. There is a scheme of informative technologies classification in automatic production of the Industry 4.0. The classification is done with technological operation done in the company with the technology of each type. There is a scheme of informative technologies distribution in the Industry 4.0 smart factory by components of production infrastructure. The role and place of each informative technology of the Industry 4.0 smart factory is described.
Influence of Bio-organic Additives on the Ability of Yeast to Provide Biotransformation of Pesticides in Apple Must
Authors: Panasyuk A L , Kuzmina E I , Kharlamova L N , Babaeva M V , Romanova I P
Published: October 2019

The problem of food safety is the most important state and scientific priority, aimed at preserving and improving the health of the population, the production of high quality and safe products. The deterioration of food quality is primarily due to the chemization of agriculture in order to increase production. The use of pesticides to control weeds, diseases and pests increases yields, but these substances accumulate in the soil, and through it in crops. In addition to the negative impact on human health, there is also a negative role of pesticides in the technological processes of food production, for example, in winemaking pesticides adversely affect the activity of fermentation and the physiological state of yeast. Industrial yeast used in the technological processes of alcoholic fermentation of grape or apple musts to wines consume organochlorine pesticides as a source of carbohydrate food and lower the level of their concentration depending on the initial content. The article presents results of studies of the influence of bio-organic additives on the ability of yeast to provide biotransformation of pesticides in apple must.
Mathematical Modeling and Information Technologies in the Management of Tractor Maintenance Operations
Authors: Myalo O V , Solomkin A P , Prokopov S P , Soyunov A S
Published: October 2019

Obtaining the greatest amount of crop with the lowest labor and material costs in agriculture is possible by reducing the operating costs of the equipment used. Reducing the machine and tractor fleet cost is possible only if high performance machines are provided with a sufficient level of reliability of the equipment used. In order to ensure trouble-free machines operation during the stressful agricultural period, it is necessary to determine the level of technical equipment maintenance sufficient to prevent sudden failures and to perform the necessary maintenance and repair operations for the units outside the stressful agricultural period. The article presents an algorithm for calculating the incorrect determination probability of the failure-free tractor operation. Using the probabilistic characteristics of the errors measurement distribution according to the normal law and the tractor reliability indicators according to the Weibull law, it is possible to determine the risks associated with the tractor operation during busy agricultural periods. The obtained mathematical models were used while computer program algorithm writing for planning the maintenance and repair of the agro-industrial complex enterprises fleet.
Prospects of Using of Chemicals in Environmentally safe Disinfection of Liquid Waste from Livestock Enterprises
Authors: Limarenko N V , Krasnova E V , Pudeyan L A , Baryshnikova O E
Published: October 2019

The prospective types of impacts on liquid waste from livestock enterprises during their disinfection were considered. The analysis of chemical reagents, providing the maximum prolonged bactericidal effect, the minimum pathogenicity of the reaction by-products and the minimum cost of the reagent and its production technology was carried out. The kinetic models of disinfection used in the evaluation of the bactericidal productivity of chemical reagents were considered. The basic parameters of liquid waste from livestock enterprises were formulated to take into account the specificity and preservation of nutrient properties, which significantly improves the level of environmental management and environmental safety.
Usage of Gray Cast Iron for Hardening of Agricultural Machines’ Soil-Tilling Implement
Authors: Sankina O V , Sankin A S , Logov A A
Published: October 2019

Research of gray cast iron was established to study physical-mechanical properties in microstructure while apply a layer on steel basis of work tool’s soil-tilling. Gray cast iron went through preliminary heat treatment, where gray cast iron hardening with temperature of 750…1050 °C with following water quenching. Research program including: comparison analysis of reference specimen and specimens which were went through heat treatment. Researching material was applied on work tool’s soil-tilling with two methods: arc surfacing and elcetrosparck surfacing. Microstructure of welding layer after arc welding and electrospark welding was studied. Therefore was found out that elecrosparck method gave opportunity to obtain wear resistant layer for a few run, also structure and basis of gray cast iron doesn’t change. Coarse graining doesn’t spot in pad weld, which is beneficial for properties. Measurement of welding layer’s hardness is bigger than base metal and there is no softening of basis. Field tests of hardened products which have shown that to use effectively gray cast iron with heat treatment for hardening, because quality and coating thickness is meeting the requirements of abrasive resistance and there are no spotted significant changes of geometrical dimension for soil-tilling implement.
The Geokhod Bar Working Body With a Diameter of 1.8 m Characteristic Point Determination
Authors: Aksenov Vladimir V , Yu Sadovets Vladimir , Rezanova Elena V , Pashkov Dmitriy A
Published: October 2019

In the article the geokhod bar working body characteristic point with a graphical method is determined. The research relevance has been considered. The information about the geokhods’ working bodies operating peculiarities is given. For the research objectives and tasks setting the geokhod bar working body characteristic point condition is defined. The 1.8 m diameter geokhod with a bar working body use conditions have been determined.On the ground of the research results the graph of changes of the geohod bar working body cutting force axial projection (PO.CV
) was constructed depending on the distance x by which the point is remote from the axis of rotation, as well as the geohod bar working body cutting force radial projection (RIO.CV
) dependence on the range from x to R
g..The geokhod bar working body characteristic point has been foundin a graphical manner, i.e. it is the interception point of graphs of changes in the cutting force axial projection (PO.CV
) in the range from 0 to x at a distance from the point rotation axis over a distance x and the cutting force radial projection (RIO.CV
) within the range from x to R
g at a distance from the point rotation axis over a distance x.
Processes of Extraction of Non-Ferrous and Precious Metals from Alternative Sources of Raw Materials
Authors: Issa Bashar , Aleksandrova T A
Published: October 2019

The presence of precious metals in electronic waste such as gold, silver, platinum and palladium, as well as non-ferrous metals (copper, nickel, zinc, tin, etc.) make it attractive for recycling. In industry, both hydrometallurgical and pyrometallurgical methods are used to extract valuable metals from electronic waste. Universal method for processing of electronic scrap waste does not exist nowadays.
The Assessment of the Level of Pollution of Slime Pits with Heavy Metals
Authors: Nemtsova O A , Romantsov I I , Avdeeva I I , Tkachenko P N , Nekhorosheva A V
Published: October 2019

In drilling and running oil and gas wells the great amount of toxic waste is formed and in the surface of the lithosphere and hydrosphere the great amount of different chemical elements and compounds access, they are needed to be isolated from the environment. The most useful way of isolation is their utilization in the slime pits on the wells territory. Heavy metals are dangerous waste in the drilling slime; they accumulate in soil and under some conditions they in form water-soluble parts and migrate in to the soil. The aim of this paper is to organize the chemical and analytical research of the amount of heavy metals in the drilling slime, and research the mechanism of their spreading on different depth and square in the slime pits typical for the oil site placed in KHANTY-Ugra.
The Structure of Training Program and Advanced Training of Enterprise Managers in Order to Ensure Environmental Safety
Authors: Abanina E N , Sergeenko Yu S , Devyatov O V , Yu Ganyukhina O , Nikitenko Yu M
Published: October 2019

Large, medium-sized and small enterprises have violation of environmental requirements and negative impact on the environment quality through emissions, discharges, waste generation. The authors suppose that one of the causes of a high degree environmental pollution in the course of economic activity by enterprises is the lack of a system for training managers and specialists in specific courses with binding studying regulatory documents on environmental safety. The article analyzes the reasons for necessary development of a compulsory program of training and advanced training of business managers in order to ensure environmental safety. The dependence of the level and complexity of preparation on the level of environmental hazard of the enterprise is shown. In order to ensure environmental safety it is necessary to define the purpose and objectives of training programs for managers. At the end, the authors present the developed model structure of the training program and advanced training of enterprise managers in order to ensure environmental safety.
Ecological Safety of Progressive Technologies in the Life Cycle
Authors: Grafkina M V , Sviridova E Y , Pitryuk A V
Published: October 2019

The article is devoted to the analysis of the implicative (according to the “What-If?” principle) interaction of all decisions on the organization and implementation of technological processes and providing them with material and energy resources, machines, units, equipment, technological equipment, technological structures and materials at various stages of the life cycle response in the environment, which allows you to identify and formulate recommendations for improving the environmental safety of technological processes in the life cycle.
Environmental Monitoring as an Information System to Ensure Environmental Safety of a Region (as Exemlified in Kemerovo Region)
Authors: Sheveleva O B , Slesarenko E V , Vagina N D , Kudrevatykh N V , Mamzina T F
Published: October 2019

the particularities of the environmental situation in the industrialized region with the predominant economic activity “Mining” are described in the article. Environmental monitoring of such basic components as the quality of atmospheric air and water, as well as investments into the environmental renovation and protection is recognized as an information system for ensuring the environmental safety of regions. As a result of the monitoring, the main discrepancies between the financial support of environmental renovation measures and the results of anthropogenic impact of coal mining enterprises on the environment were identified; attention was focused on the need to improve the efficiency of funds allocated for environmental protection and rational use of natural resources. The information system of environmental monitoring used by the coal-mining company SUEK, which today is a set of measures aimed at assessing the negative impact of the enterprise’s activities on the environment of the region and eliminating its consequences, was considered. The system of environmental renovation measures developed and implemented by the Company, their effectiveness, along with adequate funding, allows the company to become one of the industry leaders in social accountability and corporate sustainability.
Automation of Processes in Dairy Cattle Production
Authors: Ivanova I , Trotsenko I , Trotsenko V
Published: October 2019

The priority direction of modern animal husbandry is the creation of smart farms, which are managed through the use of automated systems and IT. However, not all farms use new technologies, so this article analyzes the efficiency of milk production in the conditions of the leading enterprises of the Omsk region, located in different climatic conditions, with traditional technology, and then introduced elements of a smart farm. In the course of the study in the conduct of traditional technology of milk production in large numbers were identified violations of animal identification, there was an increase in the duration of the open period and there were lower rates of purity and grade of milk. The introduction of elements of a smart farm at the same enterprises allowed to avoid errors in the identification of animals, to improve the analyzed indicators and to increase milk production.
Improvement of Adhesion Strength of the Sprayed Material
Authors: Kornilovich S A , Redreev G V , Vorobyov D A , Zakharov S V
Published: October 2019

The effective way of enhancing resistance to deterioration of the parts is the change of surface properties due to coating with the required properties. Since the deposition process takes place at an elevated temperature, it is necessary to ensure the absence of phase and structural transformations in the metal, mixing of materials, changes in the chemical composition of the coating. The use of plasma spraying at the transport management facility showed a sufficiently high quality of the coating. However, the metallographic analysis showed the presence of discontinuities at the interface in the form of pores, oxide film and sections of decarburized steel. In the case of the process of melting–spraying, the overheating areas of the base metal are formed, which leads to disadvantages similar to the deposition process. To ensure the minimal thermal impact on the part, the thermal field calculations are required. For this purpose, the time of local melting of the part by a single-phase plasma jet was calculated. The temperature field of a part in which heat is transferred by thermal conductivity, the solution of the differential equation of thermal conductivity is described. The boundary conditions of three genera are formulated. The first kind is the distribution of temperature on the enclosing surfaces. The second kind – the task on the surface of the part of the heat flux density. The third kind – setting the temperature of the medium, which acts as a plasma jet, washing the surface of the part, and the intensity of heat exchange. The mathematical model of melting of the product is constructed. The formula for calculating the reflow time is derived. The temperature distribution expressions for the molten and solid zones are obtained by the solution of the problem with moving boundaries by the Fourier’s method. On the basis of theoretical calculations it is proposed to increase the strength of the sprayed layer with the base to apply the process of plasma spraying with preliminary local melting by periodic exposure to a single-phase plasma jet.
Investigation of Effect of Electron Beam Surface Treatment of Titanium Alloy Ingots on Structure and Properties of Melted Metal
Authors: Akhonin S V , Pikulin O M
Published: October 2019

Based on accumulated experience of application of concentrated power sources for elimination of defects of ingot surface layer it is shown that remelting of surface layer of treated ingot provokes evaporation of alloying elements with high vapor pressure form a liquid pool, i.e. change of composition of treated layer in relation to ingot base. This can indicate the possible change of metal structure since it is determined by content of alloying elements.

Ingots of wrought titanium alloys VT3-1, VT-6, VT20, VT22 of 400 and 600 mm diameter and up to 2 m length made by EBM were melted by electron beam for investigation of effect of electron beam treatment of a surface layer on composition, structure and properties of metal of the treated layer. The investigations of mass concentration of alloying elements, penetration depth, macro and microstructure of melted metal layer of treated ingots were carried out.

The results of carried works showed that electron beam treatment allows efficient elimination of defects of the surface layer of titanium alloy ingots to 12 mm depth, content of alloying elements corresponds to grade composition, reduction is observed in content of alloying elements, in which vapor pressure is higher than in the alloy base, and respectively rise of content of alloying elements with vapor pressure is lower than in the alloy base. There is insignificant increase of content of interstitial impurities, i.e. oxygen and nitrogen, which do not have obvious effect on mechanical properties of treated metal. It is determined that macrostructure of metal in the treated layer of titanium alloy ingots is characterized with absence of pores and discontinuities, crystals close to equiaxial, the melted layer is formed by finer crystals in comparison with the rest part of the ingot, elongated in solidification direction, i.e. to ingot center. Solidification rates of more than 50 mm/min in the melted layer of titanium alloy ingots provoke two times refining of α-colonies and α-lamellas of ingot grains in comparison with the ingot base.
Laser Welding in Different Spatial Positions of T-joints of Austenitic Steel
Authors: Bernatskyi A V , Berdnikova O M , Klochkov I M , Sydorets V M , Chinakhov D A
Published: October 2019

It has been selected the most industry perspective laser welding technological implementations of the welded T-joints made of fine-sheeted heat resisting steel AISI 321 by identifying the influence of technological parameters on formation quality, level of mechanical properties and structural peculiarities of the welded T-joints obtained by laser welding in different spatial positions.
Influence of the Thermal-force Effect on the Process of High-temperature Synthesis of the Ni3Al Intermetallic Compound
Authors: Ovcharenko V E , Akimov K O , Boyangin E N , Baohai Yu
Published: October 2019

In this work, the intermetallic compound Ni3Al was obtained by high-temperature synthesis under pressure at various values of the preliminary pressure on the initial powder mixture (3Ni+Al). The study of pressure-time and displacement-time diagrams gave a coherent picture of the synthesis passage over time. It was found that an increase of preliminary pressure leads to a decreasing of the powder compacts porosity. In this regard, the smallest displacement of the press plunger after initiating the synthesis reaction in the powder compact was observed at the highest value of the preliminary pressure on the compact. The role of preliminary pressure on the initial powder mixture in the process of the grain structure formation of the Ni3Al intermetallic compound synthesized under pressure was determined.
Semi-supervised Soft Sensor Modeling Method for Crude Furfuryl Alcohol Distillation Process Based on Cosine Similarity-Discount
Authors: Li L H , Dai Y S
Published: October 2019

In view of the dynamic time variation and multirate data problems in crude furfuryl alcohol distillation process, too few samples of modeling data caused poor generalization ability of soft sensor model and reduced the accuracy of soft sensor model prediction. To solve this problem, this paper proposes a semi-supervised soft sensor modeling method based on cosine similarity-discount(SSSMI-COSD). By calculating the cosine similarity between labeled and unlabeled samples in the same time interval, and combining with the proposed constraints, the data clustering between labeled and unlabeled samples is realized. In addition, in order to avoid the ill-conditioned problem caused by high-dimensional input variables, the clustered data are fused by discount factor value (DFV). An actual data of a crude furfuryl alcohol distillation process (CFADP) simulation experiment were carried out. The results show that the proposed SSSMI-COSD method can effectively improve the soft sensor model prediction accuracy for a crude furfuryl alcohol distillation process.
The Car-Following Model Based on Fuzzy Inference Controller
Authors: Li Guanzhen , Zhu Wenxing
Published: October 2019

Many existing researches mostly establish a theoretical car-following model from a perspective of statistical physics, but the vehicle driver is the decision-maker of driving behaviors. When modeling the micro-behavior of the vehicle, the driver’s driving intention and decision-making basis need to be considered. In order to consider human factors more in microscopic traffic simulation, this paper uses fuzzy inference technology as the basis, selects the headway distance, ideal speed difference, and reasonable spacing difference as the input variables of the control system, considering the free running and car-following state of the vehicle, constructs fuzzy rules and establishes a car-following model.
Research and Implementation of Intelligent ERP Platform for SMEs Based on Cloud Computing
Authors: Wen Yong
Published: October 2019

According to the characteristics and business needs of small and medium-sized business management, the paper analyzes and designs the functions and performance of ERP platform, applies Internet of Things and artificial intelligence technology, and builds a dynamic mobile intelligent SME ERP platform through business database, rule database and knowledge database. The platform adopts three-tier B/S architecture, uses MySql as the back-end database, uses Java to encode, implements financial management, supply chain management, manufacturing, human resource management and other functional modules, and finally carries out platform testing. The implementation results show that the intelligent SME ERP greatly reduces the workload of business personnel and improves the efficiency of real-time dynamic management of enterprises.
An Improved Location Model for Pedestrian Detection
Authors: Zou Tengtao , Cao Chen , Yang Shangming
Published: October 2019

Pedestrian detection in complex scenes has always been a research difficulty in computer vision. The performance of current methods was seriously degraded when the pedestrian is occluded or the size of pedestrians are too small, etc. In this paper, we propose a novel approach based on location model for the detection of multiple pedestrians, which aims to improve the efficiency of algorithms in complex scenarios. In the model, a fully convolutional neural networks for the classification of pedestrian and non-pedestrian are trained to learn pedestrian features first. Then trained model are used to search for pedestrian regions, and the regions where pedestrian may be present will be activated and marked with boxes. Finally, we fine tune the boxes to overlap them with the ground truth more precisely. Compared with the current methods on two pedestrian datasets, experimental results demonstrate the comparable performance of our approach in term of miss rates.
A Glucose Prediction Model based on Variational Mode Decomposition and Least Squares Support Vector Regression
Authors: Wen S , Li H R , Han H H , Yu X
Published: October 2019

Online prediction of subcutaneous glucose concentration plays a critical role in glucose management for type 1 diabetes. In this work, a new method combining Variational Mode Decomposition (VMD) and Least Squares Support Vector Regression (LSSVR) is proposed with three main stages to improve the prediction accuracy. Firstly, the time series of blood glucose are decomposed into different frequency series by VMD method. Secondly, the LSSVR model is trained to predict each subsequence. Finally, the predicted sequences are reconstructed to obtain the overall glucose predictions. The experimental results demonstrate the effectiveness and accuracy of the proposed model for short term glucose prediction.
Deep Neural Networks in the View of Ecological Holism
Authors: Yue Qiang , Yue Xun
Published: October 2019

In the view point of ecological holism, deep neural networks can be view as a machine cognitive agent with overall multi-level nested structure, the representation learning and problem-solving ability of machine cognitive agent with multi-modal perception function is also the results from the perception and judgment of ambient situation environment. In the paper, a machine cognitive method based on ecological holism was deconstructed. Then, two core questions to characterize learnability of AlphaGo were answered, one is how to explain the characteristics of the hierarchical gradient and update parameters between different layers of networks? Two is how to understand the effective ability to choose the drop sampling at the strongest level of game of Go. These core controlling structural and functional roles proposed in this study may be further improved to a new type of artificial intelligence law of machine cognitive system.
Knowledge-oriented Hierarchical Neural Network for Sentiment Classification
Authors: Wang Yanliu , Li Pengfei
Published: October 2019

Sentiment classification aims to classify the sentimental polarities of given texts. Lexicon-based approaches utilize lexical resources to explore the opinions according to some specific rules, whose effectiveness strongly depends on the goodness of the lexical resources and the rules. Traditional machine-learning methods tightly rely on feature engineering and external NLP toolkits with unavoidable errors. Deep learning models strongly rely on a large amount of labelled data to train their numerous parameters, which often suffer from overfitting issue since it is difficult to obtain sufficient training data. To address the issues, we design a model that combines Knowledge-oriented Convolutional Neural Network (K-CNN) and bidirectional Gated Recurrent Neural Network (biGRU) in a hierarchical way for sentiment classification. Firstly K-CNN is used to capture the n-gram features in sentences. Sentiment word filters are constructed in the knowledge-oriented channel of K-CNN based on the linguistic knowledge from SentiWv ordNet, which can capture the sentiment lexicons and alleviate overfitting effectively. Then biGRU with attention mechanism is utilized to model the sequential relations between sentences and obtain the document-level representation based on the relevance of each sentence to the final sentiment classification. Experiments on two datasets show that our model outperforms other classical deep neural network models.
Research on Tourism Destination Attraction Based on Deep Learning
Authors: Li Shanshan , Qiu Canhua , Jiang Mingming
Published: October 2019

Mining and analyzing online travel reviews and travel information is playing an increasingly important role in the tourism industry. Accurately capturing the uniqueness and attractiveness of the tourist destinations recorded in the travel notes is the key to tourism analysis and application. The current way to obtain the attraction of tourism is easy to cause bias due to the use of simple statistical methods. This paper proposes a model based on deep learning, which uses Bert pre-training method, based on Transformer, and mines travel notes through Attention to find the attraction point. The model can understand the chapter-level semantics of travel notes based on the context, so much so that the extracted features are closer to the meaning of the text. It also exhibits good performance in generating unique labels of tourist destinations and similar tourism clusters. The experimental results are consistent with the facts, the validity of the model is also proved.
Artificial Intelligence Promotes the Evolution of English Writing Evaluation Model
Authors: Su Zheqian , Miao Liu , Man Jiang
Published: October 2019

On the background of “Internet +” era, the domestic higher education is showing the trend of artificial intelligence. The reliability and scientificity of computer intelligent evaluation are further carried out, and the mode of intelligent evaluation and data analysis in optimizing the precise teaching of English writing is explored, which can lay a foundation for the large-scale use of the technology. Based on data-driven theory, this study further analyzed the role of AI in promoting in-depth learning by comparing AI writing review model with manual review model.
Study on Low Characteristic Formulation Optimization of Solid Propellant Based on Improved Particle Swarm Optimization
Authors: Zhao Jiu-Ling
Published: October 2019

The combustion product of solid propellant produces strong plume flow field downstream of nozzle outlet, which improves plume characteristics, reduces plume characteristic signals, and improves stealth characteristics and survivability of missile. In this paper, an intelligent algorithm is proposed to optimize the formulation of solid propellant with low characteristic signal. An improved multi-objective particle swarm optimization algorithm is used to solve the formulation optimization model, and several feasible formulations for realizing low characteristic signal are obtained. On this basis, considering the energy performance, a formula screening method is given to calculate various characteristic signals and energy properties of the feasible formulation. The comprehensive measurement can not only take into account the optimization target requirements of propellant energy performance and plume characteristic signals, solve the conflict problem of reducing multiple characteristic signals, but also improve the efficiency of formulation design, and provide a reference for formulation designers.
A Novel Multi-information Fusion Algorithm Based on Population for Wind Power System
Authors: Wang Yufeng , Xu Chunyu
Published: October 2019

Reserve capacity optimization of power system plays an important role in large-scale Wind Power System. In this paper, a novel multi-information fusion algorithm based on population (MIFA-P) is proposed, which can balance the problem of reserve capacity optimization. MIFA-P determines the type of optimization problem by counting the maximum number of projections on the principal characteristic axis of the optimal individuals of the current population. Therefore, the corresponding class of evolutionary algorithm is chosen to solve the problem. In the process of evolution, each evolutionary algorithm achieves the organic integration through sharing population information. Finally, the validity and applicability of MIFA-P algorithm for large-scale decision variable black box optimization problem are verified by solving a practical scenario optimization problem of reserve capacity distribution in power system after wind power integration.
Grey Level Co-occurrence Matrix (GLCM) as a Radiomics Feature for Artificial Intelligence (AI) Assisted Positron Emission Tomography (PET) Images Analysis
Authors: Tamal Mahbubunnabi
Published: October 2019

Positron Emission Tomography (PET) allows tumour microenvironment to be studied in vivo with high sensitivity and specificity. Inter- and intra-tumour morphological and phenotypic heterogeneity or pattern provided by PET images are of critical importance. The traditional practice of visual interpretation of these images are not sufficient enough to extract all the information embedded in the images. On the other hand, simultaneous development of automated and reproducible analysis methodologies makes it possible to extract large amount of quantitative features from these images which is termed as radiomics. Analysis of these radiomics feature using artificial intelligence (AI) can significantly improve individualized treatment selection and monitoring. Grey level co-occurrence matrix (GLCM), a member of texture based radiomics feature family is widely used as a biomarker of heterogeneity and can provide information of the tumour microenvironment. The GLCM can subsequently be used for artificial intelligence (AI) assisted tumour diagnosis, monitoring of progression and treatment planning as well as for monitoring response to therapeutic intervention. This aim of the study was to investigate the accuracy and robustness of PET based GLCM in varying image acquisition and analysis conditions using phantom data. It has been observed that GLCM based textural features (e.g., correlation, entropy, homogeneity, energy contrast and dissimilarity) are not only dependent on the volume but also on the quantization level. They are also dependent on signal-to-noise ratio (SNR) and image contrast. The dependencies of these features to the varying imaging conditions are also not linear and cannot always be directly related. To use these GLCM derived textural features as biomarkers for AI assisted analysis, all the information regarding the textural features should always be included along with the changes in volumes and contrast of the PET images in the training dataset.
Unsupervised Learning of Depth and Visual Odometry using Photometric Calibration
Authors: Yu Tianhong
Published: October 2019

Depth and visual odometry estimation are two essential parts in SLAM systems. Compared with traditional algorithms, supervised learning methods have shown promising results in single view depth estimation and visual odometry estimation. However, they require large amounts of labeled data. Recently, some unsupervised approaches to estimate depth and odometry via minimizing photometric error draw great attention. In this paper, we present a novel approach to learn depth and odometry via unsupervised learning. Our method ameliorates the original photometric loss to enhance the robustness to illumination change in real scenarios. In addition, we propose a new structure of Pose-net and Explainability-net to achieve rotation-sensitive odometry results and more accurate explainability masks. The experimental results have demonstrated that our approach achieves better performance than existing unsupervised methods in both depth and odometry results.
Research on Intrusion Detection and Target Recognition System Based on Deep Learning
Authors: Hu Xianwei , Li Tie , Wu Zongzhi , Gao Xuan
Published: October 2019

Intrusion target detection and recognition are of great significance to security protection of oil and gas fields. An intrusion detection system is built with the integration of infrared image acquisition module, infrared image processing module, moving target detection module and recognition module. Traditional target recognition algorithm highly relies on manual design feature extraction algorithm, which requires designer to have adequate prior knowledge, and cannot avoid the influence of subjective factors of people. Intrusion detection and target recognition system are proposed based on deep learning, which uses neural network algorithm. Deep learning model is built through feature extraction and training of acquired images of intrusion objects, and thus subsequent invasion objects are detected and recognized. Intrusion detection is achieved through simulation of human brain, which boasts of more intelligent recognition process and more accurate recognition results compared with traditional recognition method. According to applications in real scenario, the system proposed has better detection and recognition results and great practical value.
Research on Action Recognition Method Based on Weighted DTW Algorithm
Authors: Zhang Zhen , Zhang Ya
Published: October 2019

Action recognition technology is an important part of artificial intelligence. In order to improve the rate of action recognition, this paper designs an action recognition method based on Weighted DTW algorithm. Firstly, the Kinect2.0 is used to obtain the three-dimensional data of the human joint points. Then the quaternion method is used to define the action sequences. The weight of joint is calculated according to the participation in different types of action. Then the improved DTW algorithm is used to design the action recognition experiment. The experimental results show that the action recognition algorithm designed in this paper has better recognition rate and timeliness than traditional DTW algorithm and F-DTW algorithm.
A Case Study on Three-Dimensional Single-Beacon Localization for Autonomous Underwater Vehicles
Authors: Yu Huapeng , Han Chao
Published: October 2019

Circular trajectory is most frequently used when an autonomous underwater vehicle calibrates positions of underwater acoustic beacons or corrects its own navigation errors using beacons. However, the space-time effect on control and navigation data processing and the impact of the angle of attack on three-dimensional localization performance of AUVs have rarely been mentioned in previous studies. To improve the three dimensional localization performance of AUVs with a single-beacon aiding, methods for space-time trade-offs from a control perspective and determination of the optimal angle of attack are investigated in this study. Through theoretical deduction aided with numerical simulation, concerned quantitative values with their corresponding preconditions are given, and some general conclusions which can greatly improve the navigation capability of AUVs have been made.