High Degree Of Automation Research Articles

Optimization of Chaboche Material Parameters with a Genetic Algorithm

The main objective of this study is to research and develop a genetic algorithm (GA) for optimizing Chaboche material model parameters within an industrial environment. The optimization is based on 12 experiments (tensile, low-cycle fatigue, and creep) that are performed on the material, and corresponding finite element models were created using Abaqus. Comparing experimental and simulation data is the objective function that the GA is minimizing. The GA's fitness function makes use of a similarity measure algorithm to compare the results. Chromosome genes are represented with real-valued numbers within defined limits. The performance of the developed GA was evaluated using different population sizes, mutation probabilities, and crossover operators. The results show that the population size had the most significant impact on the performance of the GA. With a population size of 150, a mutation probability of 0.1, and two-point crossover, the GA was able to find a suitable global minimum. Comparing it to the classic trial and error approach, the GA improves the fitness score by 40%. It can deliver better results in a shorter time and offer a high degree of automation not present in the trial and error approach. Additionally, the algorithm is implemented in Python to minimize the overall cost and ensure its upgradability in the future.

Sustainable development of simulation setups and addons for OpenFOAM for nuclear reactor safety research

Abstract Open-source environments such as the Computational Fluid Dynamics software OpenFOAM are very appealing for research groups since they allow for an efficient prototyping of new models or concepts. However, for downstream developments to be sustainable, i.e. reproducible and reusable in the long term, a significant amount of maintenance work must be accounted for. To allow for growth and extensibility, the maintenance work should be underpinned by a high degree of automation for repetitive tasks such as build tests, code deployment and validation runs, in order to keep the focus on scientific work. Here, an information technology environment is presented that aids the centralized maintenance of addon code and setup files with relation to reactor coolant system safety research. It fosters collaborative developments and review processes. State-of-the-art tools for managing software developments are adapted to meet the requirements of OpenFOAM. A flexible approach for upgrading the underlying installation is proposed, based on snapshots of the OpenFOAM development line rather than yearly version releases, to make new functionality available when needed by associated research projects. The process of upgrading within so-called sprint cycles is accompanied by several checks to ensure compatibility of downstream code and simulation setups. Furthermore, the foundation for building a validation data base from contributed simulation setups is laid, creating a basis for continuous quality assurance.

Exposure to occupational risk factors is associated with the severity and progression of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) results from a complex interaction between genes and the environment, and occupational exposures are an underappreciated risk factor. Until now, little research attention has been paid to the potential impact of occupational risk factor exposure on the COPD in China. The aim of this retrospective study was to analyze the role of occupational risk factor exposure on the severity and progression of COPD for exploring new prevention strategies for this disease. This study adopted a random cluster-sampling method. Five grade-A tertiary hospitals that met the inclusion criteria were selected as the survey sites, and patients with COPD hospitalized in these hospitals from January 1, 2019, to December 31, 2019, were selected as the research subjects. Data of the patients diagnosed with COPD met the Global Initiative for Chronic Obstructive Lung Disease (2019) criteria and were collected from the computerized medical record databases. Among 4082 investigated COPD patients, 1063 (26%) were found to have occupational risk factor exposure history. The top 3 industries with a large COPD case number and a history of occupational risk factor exposure ranked in the order of agriculture (including farming, forestry, animal husbandry, and fishery), manufacturing, and mining. Further multivariate logistic regression analysis indicated that when setting a low exposure level as a reference, medium and high exposure levels were correlated with the severity of COPD (odds ratio values were 2.837 and 6.201, respectively, P < .05). Linear regression analysis showed that cumulative exposure to occupational risk factors was negatively correlated with the forced expiratory volume in 1-second percentage of COPD patients, with a correlation coefficient of 0.68. Our results indicated that occupational risk factor exposure levels were related to the severity of COPD significantly. The incubation period of COPD in the exposure group was significantly shorter than that in the non-exposure group. To prevent worked-related COPD, special attention and control efforts should be taken to reduce the level of occupational risk factors such as organic dust, irritating chemicals, etc in the work environments, especially in the industries of agriculture, forestry, animal husbandry and fishery, manufacturing, and mining.

METHODS OF PROTECTING THE ENVIRONMENT BY USING AUTOMATED AND COMPUTERIZED WORK TECHNIQUES IN THE CEREALS GRINDING PROCESS

The technological flow from a compound feed factory is a very complex one, starting from the storage of raw materials in special bunkers, then their movement to the processing installations with the help of conveyor belts, grinding the cereals, adding all the ingredients indicated by the assortment recipe, mixing and homogenization, and finally granulation and sterilization of the finished product obtained. As can be seen, one of the basic activities carried out during the production process of various types of compound feed is the grinding of cereal grains, which involves the release of small dust particles into the atmosphere. Therefore, it is aimed to use high-performance work installations in compound feed factories, with a high degree of mechanization, automation and computerization, with high productivity and low specific consumption, to ensure a rigorous monitoring of dust and other noxes according to accepted European norms. This article analyses the technical working parameters in the cereals grinding area and presents the results of the experimental measurements carried out in the dust discharge areas, which prove the advantage of using automated and computerized work installations, equipped with special filters which respect the optimal projected parameters and which ensure the rules imposed by the European Union for the protection of the environment.&#x0D;

A Model-Driven Approach for Software Process Line Engineering

It has become increasingly preferable to construct bespoke software development processes according to the specifications of the project at hand; however, defining a separate process for each project is time consuming and costly. One solution is to use a Software Process Line (SPrL), a specialized Software Product Line (SPL) in the context of process definition. However, instantiating an SPrL is a slow and error-prone task if performed manually; an adequate degree of automation is therefore essential, which can be achieved by using a Model-Driven Development (MDD) approach. Furthermore, we have identified specific shortcomings in existing approaches for SPrL Engineering (SPrLE). To address the identified shortcomings, we propose a novel MDD approach specifically intended for SPrLE; this approach can be used by method engineers and project managers to first define an SPrL, and then construct custom processes by instantiating it. The proposed approach uses a modeling framework for modeling an SPrL, and applies transformations to provide a high degree of automation when instantiating the SPrL. The proposed approach addresses the shortcomings by providing an adequate coverage of four activities, including Feasibility analysis, Enhancing the core process, Managing configuration complexity, and Post-derivation enhancement. The proposed approach has been validated through an industrial case study and an experiment; the results have shown that the proposed approach can improve the processes being used in organizations, and is rated highly as to usefulness and ease of use.

Validation of a flow-cytometry-based red blood cell antigen phenotyping method.

Current manual and automated phenotyping methods are based on visual detection of the antigen-antibody interaction. This approach has several limitations including the use of large volumes of patient and reagent red blood cells (RBCs) and antisera to produce a visually detectable reaction. We sought to determine whether the flow cytometry could be developed and validated to perform RBC phenotyping to enable a high-throughput method of phenotyping using comparatively miniscule reagent volumes via fluorescence-based detection of antibody binding. RBC phenotyping by flow cytometry was performed using monoclonal direct typing antisera (human IgM): anti-C, -E, -c, -e, -K, -Jka , -Jkb and indirect typing antisera (human IgG): anti-k, -Fya , -Fyb , -S, -s that are commercially available and currently utilized in our blood transfusion services (BTS) for agglutination-based phenotyping assays. Seventy samples were tested using both flow-cytometry-based-phenotyping and a manual tube standard agglutination assay. For all the antigens tested, 100% concordance was achieved. The flow-cytometry-based method used minimal reagent volume (0.5-1μl per antigen) compared with the volumes required for manual tube standard agglutination (50μl per antigen) CONCLUSION: This study demonstrates the successful validation of flow-cytometry-based RBC phenotyping. Flow cytometry offers many benefits compared to common conventional RBC phenotyping methods including high degrees of automation, quantitative assessment with automated interpretation of results and extremely low volumes of reagents. This method could be used for high-throughput, low-cost phenotyping for both blood suppliers and hospital BTS.

Algorithms in the court: does it matter which part of the judicial decision-making is automated?

Artificial intelligence plays an increasingly important role in legal disputes, influencing not only the reality outside the court but also the judicial decision-making process itself. While it is clear why judges may generally benefit from technology as a tool for reducing effort costs or increasing accuracy, the presence of technology in the judicial process may also affect the public perception of the courts. In particular, if individuals are averse to adjudication that involves a high degree of automation, particularly given fairness concerns, then judicial technology may yield lower benefits than expected. However, the degree of aversion may well depend on how technology is used, i.e., on the timing and strength of judicial reliance on algorithms. Using an exploratory survey, we investigate whether the stage in which judges turn to algorithms for assistance matters for individual beliefs about the fairness of case outcomes. Specifically, we elicit beliefs about the use of algorithms in four different stages of adjudication: (i) information acquisition, (ii) information analysis, (iii) decision selection, and (iv) decision implementation. Our analysis indicates that individuals generally perceive the use of algorithms as fairer in the information acquisition stage than in other stages. However, individuals with a legal profession also perceive automation in the decision implementation stage as less fair compared to other individuals. Our findings, hence, suggest that individuals do care about how and when algorithms are used in the courts.

A novel 3D-imaging and characterisation technique for special nuclear materials in radioactive waste

A novel technique for non-destructive assay (NDA) of radioactive waste called ARCTERIX (Advanced Radwaste Characterisation based on Tomographically Enhanced Radiation Imaging without X-rays) is presented. The concept is based on a 3D-tomographic imaging technique for special nuclear materials – neutron-gamma emission tomography (NGET). ARCTERIX takes the NGET principle from its original application area of nuclear security systems into the realm of radioactive waste assay with its special characteristics and challenges. By adding localisation and imaging of SNM inside shielded waste containers to the array of existing techniques used for radioactive waste characterisation, ARCTERIX complements the state of the art in passive and active NDA interrogation methods. It is aimed primarily at the class of mixed, long-lived radioactive waste that is commonly called “legacy” or “historic” waste which has special safety, security and safeguards concerns due to its mixed composition, commonly poor documentation, and the frequent presence of SNM. The ARCTERIX concept provides rapid imaging and characterisation of nuclear materials in radioactive waste with a high degree of automation and high throughput capabilities, making it possible to quickly scan large radioactive waste inventories for the presence of special nuclear materials with minimal manual intervention. The first ARCTERIX prototype system has demonstrated a high technological readiness for the implementation of the technique in a commercial stand-alone system for rapid assessment of radioactive waste drums or in a system operating in conjunction with established techniques.

Study on the detection method of HDPE electro-fusion welding defect based on X-ray technology

Electro-fusion welding is a common method for high-density polyethylene (HDPE) pipes. It has a high degree of automation and mature technology. However, during the welding process, various buried defects are easily generated. In this paper, HDPE pipes with welding defects were processed, and X-ray technology was used to detect the defects. The results show that: The X-ray detection technology is sensitive to the defects of sockets and ultralight clay-filled holes. But it is difficult to distinguish the size of the holes. Unfilled holes are partially fused during the welding process, which makes them difficult to detect. In addition, the defects of cold-welding and unscratched oxide skin cannot be detected.

Artificial intelligence-accelerated high-throughput screening of antibiotic combinations on a microfluidic combinatorial droplet system.

Microfluidic platforms have been employed as an effective tool for drug screening and exhibit the advantages of lower reagent consumption, higher throughput and a higher degree of automation. Despite the great advancement, it remains challenging to screen complex antibiotic combinations in a simple, high-throughput and systematic manner. Meanwhile, the large amounts of datasets generated during the screening process generally outpace the abilities of the conventional manual or semi-automatic data analysis. To address these issues, we propose an artificial intelligence-accelerated high-throughput combinatorial drug evaluation system (AI-HTCDES), which not only allows high-throughput production of antibiotic combinations with varying concentrations, but can also automatically analyze the dynamic growth of bacteria under the action of different antibiotic combinations. Based on this system, several antibiotic combinations displaying an additive effect are discovered, and the dosage regimens of each component in the combinations are determined. This strategy not only provides useful guidance in the clinical use of antibiotic combination therapy and personalized medicine, but also offers a promising tool for the combinatorial screenings of other medicines.

Effect of serum lipid subfractions on nuclear magnetic resonance spectroscopy's ability to detect coronary atherosclerosis early

Nuclear magnetic resonance spectroscopy, also known as NMRS, is a cutting-edge method based on nuclear magnetic induction theory and quantum optics that has found extensive usage in the domains of chemical analysis, life science, and other disciplines. The method is quantitative and repeatable, making it particularly effective for detecting and analyzing tiny compounds in complicated solutions like blood and urine. With a high degree of standardization and automation, it can assess 114 hemo lipoprotein subfractions and particles in human serum/plasma in a targeted way (exact quantification) and produce precise and dependable detection findings. All processes may be tracked back to fulfill our requirements for non-targeted analysis, which is suited for biological fluid specimens and water-soluble specimens from tissue or cell extracts. The 114 lipoprotein subfractions and particles can be targeted using nuclear magnetic resonance spectroscopy (NMRS), which can detect the serum lipid profile in its entirety. The analysis of the serum lipid profile, the correlation between the levels of lipid subfractions and lipid particles and the degree of coronary stenosis, and the development of a coronary stenosis early warning system can therefore improve the current risk model on the inadequacy of the risk stratification of the patients. These studies are based on a cohort of individuals with varying degrees of coronary atherosclerosis. The development of a coronary artery stenosis early warning system might enhance the patient risk classification models already in use. To analyze the correlation of lipid subfractions and particle levels with cardiovascular events and therapeutic efficacy, to explore more effective biomarkers for lipid-lowering monitoring, and to evaluate the efficacy of classical Chinese medicinal preparations.

Theoretical study of the influence of the changing environment on the process of rainfall irrigation

The technology of sprinkler irrigation has a higher coefficient of land use compared to that of regular irrigation, due to the absence of irrigation erosion, the prevention of unnecessary absorption of water into the soil, the high degree of mechanization and automation of the irrigation process, the saving of equipment and fuel costs, the availability of irrigation in areas with uneven relief, the uniform moistening of the root layer. It has the advantage of achieving the same growth and development of the plant in all parts of the field. At the same time, there are opportunities to achieve savings as a result of giving mineral fertilizers in the form of suspension during irrigation. This article examines the distribution of water droplets on the field surface during sprinkler irrigation and the influence of wind speed on the intensity of irrigation. Water drop motion and wind motion were analyzed in one coordinate system. As a result, a mathematical model of the resistance coefficient of the environment and the movement of a water droplet in a variable environment was developed.

World trends in the creation of robots for spraying crops

The article is devoted to the problem of identifying global trends in the development of robotic sprayers for crop processing. The author distinguishes three groups of spraying robots depending on the area of application. The first group is characterized by the use of technical vision and computer learning technologies for recognition and selective spraying of weeds, the use of spot treatment systems with a micro dose of chemicals, the development of robots with a certain level of versatility, which makes it possible to perform other field works in addition to spraying. The second group is characterized by the installation of high-performance spraying equipment, the use of universal spraying devices to ensure the processing of plants of various heights, the use of laser sensors, gyroscopes, wheel and steering sensors to adjust the movement of the robot in real time. The installation of deployed video surveillance systems on the robot to control movement machine and the quality of the work process is also feature of this group. The third group is characterized by a high degree of automation of all work processes, the installation of a wide range of additional equipment for monitoring the current state of plants and soil, air parameters and illumination.

Emotional Vietnamese Speech Synthesis Using Style-Transfer Learning

In recent years, speech synthesis systems have allowed for the production of very high-quality voices. Therefore, research in this domain is now turning to the problem of integrating emotions into speech. However, the method of constructing a speech synthesizer for each emotion has some limitations. First, this method often requires an emotional-speech data set with many sentences. Such data sets are very time-intensive and labor-intensive to complete. Second, training each of these models requires computers with large computational capabilities and a lot of effort and time for model tuning. In addition, each model for each emotion failed to take advantage of data sets of other emotions. In this paper, we propose a new method to synthesize emotional speech in which the latent expressions of emotions are learned from a small data set of professional actors through a Flowtron model. In addition, we provide a new method to build a speech corpus that is scalable and whose quality is easy to control. Next, to produce a high-quality speech synthesis model, we used this data set to train the Tacotron 2 model. We used it as a pre-trained model to train the Flowtron model. We applied this method to synthesize Vietnamese speech with sadness and happiness. Mean opinion score (MOS) assessment results show that MOS is 3.61 for sadness and 3.95 for happiness. In conclusion, the proposed method proves to be more effective for a high degree of automation and fast emotional sentence generation, using a small emotional-speech data set.

Automatic XML Extraction from Word and Formatting of E-Book Formats: Insight into the Open Source Academic Publishing Suite (OS-APS)

Due to resource constraints, most Diamond Open Access journals publish fewer than 25 articles per year, and 75% of journals are not able to provide their content in XML and HTML, primarily providing only PDFs. In order to keep up with larger commercial publishers, a high degree of automation and streamlining of processes is necessary. The Open Source Academic Publishing Suite (OS-APS) project, funded by the German Federal Ministry of Education and Research, aims to achieve this. OS-APS automatically extracts the underlying XML from Word manuscripts and offers optimization and export options in various formats (PDF, HTML, EPUB). The professional corporate design, e.g., of the PDFs, is managed automatically using templates or creating one’s own using a Template Development Kit. OS-APS will also connect to scholarly-led and community-driven publishing platforms such as Open Journal Systems (OJS), Open Monograph Press (OMP), and DSpace: the software will be able to be integrated into a wide range of publication processes, whether at small, low-resource commercial Open Access Publishers, or institutional and Diamond Open Access Publishers.

Training PPA Models for Embedded Memories on a Low-data Diet

Supervised machine learning requires large amounts of labeled data for training. In power, performance, and area (PPA) estimation of embedded memories, every new memory compiler version is considered independently of previous compiler versions. Since the data of different memory compilers originate from similar domains, transfer learning may reduce the amount of supervised data required by pre-training PPA estimation neural networks on related domains. We show that provisioning times of PPA models for new compiler versions can be reduced significantly by exploiting similarities among different compilers, versions, and technology nodes. Through transfer learning, we shorten the time to provision PPA models for new compiler versions, which speeds up time-critical periods of the design cycle. Using only 901 training samples (10%) is sufficient to achieve an almost worst-case (98th percentile) estimation error of 2.67% and allows us to shorten model provisioning times from 40 days to less than one week without sacrificing accuracy. To enable a diverse set of source domains for transfer learning, we devise a new, application-independent method for overcoming structural domain differences through domain equalization that attains competitive results when compared to domain-free transfer. A high degree of automation necessitates the efficient assessment of the best source domains. We propose using various metrics to accurately identify four of the five best among 45 datasets with low computational effort.

Self-Driving Vehicles. A Perspective on Ethics

At the time of writing this paper there are already some implementations of autonomous vehicles. This paper approaches this subject from a different perspective by defining what automation means in other areas of transportation as well as ethical problems regarding the operation of this kind of vehicle. In the later part although of equal importance discuss the operation of the autonomous vehicle from a security and data privacy point of view. This paper tries to define autonomous vehicles by comparison with other ways of transportation which have a higher degree of automation and defines what autonomous vehicles might impact our lives and our privacy.

Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes

Abstract. This study explores the potential of using Doppler (power) spectra from vertically pointing C-band radar birdbath scans to investigate precipitating clouds above the radar. First, the new birdbath scan strategy for the network of dual-polarization C-band radars operated by the German Meteorological Service (Deutscher Wetterdienst, DWD) is outlined, and a novel spectral postprocessing and analysis method is presented. The postprocessing algorithm isolates the weather signal from non-meteorological contributions in the radar output based on polarimetric attributes, identifies the statistically significant precipitation modes contained in each Doppler spectrum, and calculates characteristics of every precipitation mode as well as multimodal properties that describe the relation among different modes when more than a single mode is identified. To achieve a high degree of automation and flexibility, the postprocessing chain combines classical signal processing with clustering algorithms. Uncertainties in the calculated modal and multimodal properties are estimated from the small variations associated with smoothing the measured radar signal. The analysis of five birdbath scans recorded at different radar sites and for various precipitation conditions delivers reliable profiles of the derived modal and multimodal properties for two snowfall cases and for stratiform precipitation above and below the melting layer. To help identify the dominant precipitation growth mechanism, Doppler spectra from DWD's birdbath scans can be used to retrieve the typical degree of riming for individual snow modes. Here, the automatically identified snow modes span a wide range of riming conditions with estimated rime mass fractions (RMFs) of up to RMF&gt;0.5. The evaluation of Doppler spectra inside the melting layer and for an intense frontal shower, with observed radar reflectivities of up to about 40 dBZ, occasionally shows erroneously identified precipitation modes and spurious results for the calculated higher-order Doppler moments of skewness and kurtosis. Nonetheless, the Doppler spectra from DWD's operational C-band radar birdbath scan provide a detailed view into the precipitating clouds and allow for calculating a high-resolution profile of radar reflectivity, mean Doppler velocity, and spectral width even in intense frontal precipitation.

A VIEW ON HUMAN CAPITAL IN INDUSTRY 4.0

The article's subject is the definition of areas where space is created for targeted workforce management and its successful implementation within the Industry 4.0 concept. In most cases, if we talk about the performance of Industry 4.0 elements, the investments of enterprises are primarily directed to the area of production, information and communication technologies, research and development, not to the formation of specific competencies of Work 4.0 and support for the implementation of human capital in practice. It is generally assumed that introducing Industry 4.0 will mean a lower need for labour for the enterprise, which will be replaced by a higher degree of automation and robotization. It is essential to recognize that human participation will still be required in work systems that are more automated and digitized, but that humans need to be sufficiently prepared for the changed way of doing work. The digitalization of the economy is not only creating new jobs and occupations but is also creating the need for new skills for employment. Employees will need to be willing and able to continue to learn and acquire new skills. It is essential to work with the workforce in the enterprise and gradually equip them with the missing skills and abilities. Several analytical methods were used to obtain the analytical background to identify areas of investment for companies in Industry 4.0 and to identify threats and risks associated with implementing Industry 4.0. An important component was the perspective of the affected employees and their perception of disadvantages within Industry 4.0. The analysis findings are used to understand better the workforce status in the enterprise and the gaps where space is created for workforce development in the changing needs of industrial enterprises in the Industry 4.0 environment.

Design of a Drum Brake Turnover Machine

In order to meet the demand of turning over brakes in an automatic assembly line of drum brakes, a drum brake turnover machine is designed. SolidWorks software is used to complete the three-dimensional modeling of the mechanical structure of the whole device; The control system of the drum brake turnover machine based on Schneider M241 PLC is designed, and the AC servo system control based on CANopen BUS is realized. The precise control of the position of reclaiming, overturning, discharging and turning angle of the drum brake is achieved. The engineering application results show that the equipment has a high degree of automation, stable operation, and good economy.