Methode zur Bestimmung der notwendigen Automatisierung von LKT-Systemen/Determining the necessary automation of storage, commissioning and transport systems

2020 ◽  
Vol 110 (03) ◽  
pp. 141-145
Author(s):  
Maren Müller ◽  
Anke Maria Behrend ◽  
Malte Stonis
Keyword(s):  
Influencing Factors ◽  
Influencing Factor ◽  
Transport Systems ◽  
Selection Of

Die Auswahl von Lager-, Kommissionier- und Transportsystemen (LKT-Systeme) ist aufgrund der hohen Anzahl an zur Verfügung stehenden Systemen am Markt und zu betrachtenden Einflussfaktoren sehr komplex. Ein wichtiger Einflussfaktor ist die Automatisierung. Zur Einordnung der Automatisierungsgrade von LKT-Systemen und zur Bestimmung der individuell notwendigen Automatisierung wird folgend eine Methode vorgeschlagen.   The selection of storage, commissioning and transport systems (sct systems) is very complex due to the large number of available systems on the market and influencing factors. One important influencing factor is automation. To classify the degrees of automation of sct systems and to determine the individually required automation a method is proposed below.

scholarly journals Research on Influencing Factor Selection of Pilot’s Intention

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Haibo Wang ◽  
Ting Pan ◽  
Haiqing Si ◽  
Yao Li ◽  
Naiqi Jiang
Keyword(s):  
Influencing Factors ◽  
Flight Control ◽  
Influencing Factor ◽  
Physical Parameters ◽  
Cognitive State ◽  
Factors Affecting ◽  
Active Safety System ◽  
Factor Sequence ◽  
Automatic Pilot ◽  
Selection Of

The physiological, psychological, and physical characteristics of the pilot will have an impact on flight safety, mainly in the pilot’s intention. In another word, this means the pilot’s psychological experience of flight status under the influence of various factors and the preference for decision-making or behavioral value that is displayed. The pilot’s intention is to reflect the cognitive state that the pilot showed during the maneuvering of the aircraft. The exploration of intention is very important for the study of automatic pilot and flight control active safety system. Also, it is an important concept often involved in the study of human factors in flight, especially the microbehavior of pilots. Pilot’s intention is taken as the study object in this paper; physiological-psychological-physical parameters are obtained through analyzing their influencing factors from the simulating flight experiments designed. The random forest analysis method is used to rank the main influencing factors affecting the pilot’s intention, and the factor sequence is formed. The results provide a good foundation for further research on the pilot’s intention identification.

Selection of effective wax (deposition) inhibitors to oil production and transportation at the Kondinskoye oil field

2020 ◽  
pp. 120-127
Author(s):  
E. N. Skvortsova ◽  
O. P. Deryugina
Keyword(s):  
Laboratory Tests ◽  
Initial Dosage ◽  
Oil Production ◽  
Oil Field ◽  
Transport Systems ◽  
Asphaltene Precipitation ◽  
Wax Deposition ◽  
Selection Of ◽  
Pilot Tests

The article discusses the results of a study on the selection of wax inhibitors that can be used at the Kondinskoye oil field during transportation and dehydration of the emulsion.Asphaltene precipitation is one of the most serious issues in oil production. The experiment was conducted in order to select the most effective wax inhibitors. We have carried out laboratory tests to choose the most effective wax inhibitor in the conditions of oil production, collection, preparation and external transport systems at the Kondinskoye oil field. Based on the data obtained, wax inhibitor-2, wax inhibitor-4, and wax inhibitor-6 have shown the best results in ensuring the efficiency of inhibition, which should be at least 70 %, and, therefore, they can be allowed to pilot tests. The recommended initial dosage of inhibitors according to the results obtained during pilot tests should be at least 500 g/t of oil.

scholarly journals Extracting relationship between air pollution and precipitation using spatio-temporal analysis in Tehran metropolis

2019 ◽  
Vol 2 ◽  
pp. 1-7
Author(s):  
Shokouh Dareshiri ◽  
Mohammadreza Sahelgozin ◽  
Maryam Lotfian ◽  
Jens Ingensand
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Regression Model ◽  
Influencing Factors ◽  
Polynomial Regression ◽  
Human Life ◽  
Pearson Correlation ◽  
Influencing Factor ◽  
Polynomial Equation ◽  
Temporal Analysis

<p><strong>Abstract.</strong> Precipitation is one of the main stages of the water cycle, and it is required for the organisms to survive on the planet. In contrast, air pollution is a phenomenon that has greatly affected the human life nowadays. Population growth, development of factories and increasing number of fossil fuel vehicles are the most influencing factors on air pollution. In addition to understand nature of precipitation and air pollution, finding relationship between these two phenomena is necessary to make appropriate policies for reducing air pollution. Furthermore, studying trends of precipitation and air pollution in the past, is helpful to forecast the times and places with less precipitation and more air pollution for a better urban management. In this study, we tried to extract any probable relationship between these two parameters by investigating their monthly measured amounts in 22 municipal districts of Tehran in three epochs of time (2009, 2013 and 2017). Carbon Monoxide (CO) was considered as the indicator of air pollution. Results of the study show that the parameters have a significant relationship with each other. By using Pearson Correlation Coefficient and One-Way Variance (ANOVA) test, relationship between the data for each month and for each district of Tehran were studied separately. As the time has passed and the air pollution has increased, the correlation between the parameters in districts has decreased. In addition, during the cold months of the year, the correlations decrease since the fact that precipitation is not the only influencing factor on the air pollution due to the rise of air “Inversion”. Finally, the polynomial regression model of carbon monoxide based on precipitation was extracted for each of the three years. The model suggests a degree three polynomial equation. The obtained coefficients from the regression model show that the relationship between parameters was stronger in the years with more rainfalls. This can be due to the more significant impact of other influencing factors on air pollution, such as population density, wind direction, vehicles and factories in the areas or conditions with a less rainfall.</p>

scholarly journals Analysis of Revenue Incentive Dynamic Mechanism of Financial Supply Chain from the Perspective of the Internet of Things

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yue Yin
Keyword(s):  
Supply Chain ◽  
Life Cycle ◽  
Influencing Factors ◽  
Incentive Mechanism ◽  
Influencing Factor ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
The Incentive Mechanism ◽  
Relationship Factors ◽  
The Internet Of Things

With the rapid development of society, all walks of life need the support of the Internet of Things, and the financial industry is no exception. This article integrates blockchain technology with supply chain finance and builds a supply chain financial alliance architecture based on blockchain technology and an underlying model of the Ethereum blockchain system suitable for supply chain finance. We innovated new supply chain finance models and operating mechanisms and proposed business scenarios for supply chain finance from the perspective of blockchain. Taking into account the actual operation of the blockchain supply chain financial platform, the principal-agent model and the incentive theory are applied, and the supply chain financial accounts receivable model is taken as an example in the case of complete information and incomplete information. The incentive mechanism between the service provider of the chain supply chain financial platform and the core enterprise promotes the better implementation of blockchain technology and supply chain finance. Based on the existing theoretical research, this paper identifies the key influencing factors of the supply chain’s cross-enterprise incentive mechanism. These influencing factors system includes two dimensions: transaction factors and relationship factors. Transaction factors include resource dependence, uncertainty, and cooperation experience; relationship factors include corporate reputation, trust level, and relationship commitment. Based on the nature of the incentive mechanism, information sharing and revenue sharing are extracted as the measurement dimensions of the supply chain’s cross-enterprise incentive mechanism. On this basis, this article draws on the existing enterprise life cycle division method and constructs a hypothetical model of the influencing factors of the incentive mechanism in the incubation period, the growth period, and the maturity period. Relevant data was collected through questionnaires, and SPSS and AMOS software were used to perform statistical analysis, reliability analysis, exploratory factor analysis, confirmatory factor analysis, and structural equation hypothesis testing on the data. The performance of each influencing factor in different stages of the enterprise’s life cycle and the importance of each influencing factor in the same life cycle stage are obtained.

Mineral Water Quality Influencing Factors in their Selection for Use

2021 ◽  
Vol 42 ◽  
pp. 203-208
Author(s):  
Mihai Demian ◽  
Gabriela Demian
Keyword(s):  
Water Quality ◽  
Decision Making ◽  
Influencing Factors ◽  
Therapeutic Effect ◽  
Mineral Water ◽  
Mineral Waters ◽  
Selection For ◽  
Physical And Chemical ◽  
Selection Of

The paper presents a way of selecting flat or carbonated mineral waters depending on the purpose for which it wishes to be used. A good mineral water must meet certain physical and chemical qualities at certain temperatures and have the appropriate pH to have the desired therapeutic effect. The analysis of the purpose for which the selection of mineral waters is desired results in the characteristics of the water to be analyzed, compared, and for which a weight of their influence in the decision-making is established. For selected waters, the characteristics receive scores that will in turn influence the selection of the recommended type of mineral water. The conclusions of the paper allow the establishment of a certain type of mineral water for the characteristics imposed by the desired purpose.

System Reliable Probability for Multi-AUV Cooperative Systems under the Influence of Current

2019 ◽  
Vol 72 (06) ◽  
pp. 1649-1659
Author(s):  
Qingwei Liang ◽  
Tianyuan Sun ◽  
Junlin Ou
Keyword(s):  
Marine Environment ◽  
Reliability Index ◽  
Autonomous Underwater Vehicle ◽  
Influencing Factor ◽  
Practical Method ◽  
Underwater Vehicle ◽  
Cooperative Systems ◽  
Cooperative System ◽  
Structure Selection ◽  
Selection Of

Real multi-Autonomous Underwater Vehicle (AUV) cooperative systems operate in complicated marine environments. The interaction between a multi-AUV cooperative system and its marine environment will affect the reliability of the system. Current is an important influencing factor of multi-AUV cooperative systems. A reliability index of multi-AUV cooperative systems known as System Reliable Probability (SRP) is proposed in this study. A method to calculate SRP is introduced, and the influence of current on SRP is discussed in detail. Current is considered an attack source, and the degree of its influence on SRP is calculated. As an example, the performance of this method is shown on two multi-AUV cooperative systems. Results show that the influence of the same current environment on different structures of the multi-AUV cooperative systems differs. This result provides a reference for the structure selection of multi-AUV systems. This study provides a practical method to estimate the reliability of multi-AUV cooperative systems.

A Study on the Effectiveness of College English Blended Learning Under MOOCs Philosophy in China

2020 ◽  
pp. 247-270
Author(s):  
Zhaohui Dai
Keyword(s):  
Collaborative Learning ◽  
Blended Learning ◽  
Influencing Factors ◽  
Influencing Factor ◽  
Negative Attitude ◽  
Great Emphasis ◽  
Autonomous Learning ◽  
College English ◽  
Blended Education ◽  
Attitude And Motivation

This study investigated the effectiveness of college English blended education under MOOCs philosophy in China. The findings suggest that many features of MOOCs philosophy are evident in college English blended education and eight factors influence effectiveness. Relationships of the influencing factors demonstrate that interactions and evaluations are highly influencing factors in autonomous learning and motivations exert high influences on autonomous learning. However, students have low motivation in interaction and evaluation, for they are more extrinsically than intrinsically motivated. And also, collaborative learning is the least influencing factor in the study. To motivate the students, great emphasis should be laid on interactions and evaluation in student's autonomous learning. Moreover, students' negative attitude towards autonomous learning hampers their adaptability to college English blended learning, and, as attitude and motivation are highly related, this deserves equal attention.

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