Journal articles on the topic 'Factorized Databases'
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1
Olteanu, Dan, and Maximilian Schleich. "Factorized Databases." ACM SIGMOD Record 45, no. 2 (September 28, 2016): 5–16. http://dx.doi.org/10.1145/3003665.3003667.
2
Olteanu, Dan. "Report on the Workshop on Factorized Databases." ACM SIGMOD Record 52, no. 2 (August 10, 2023): 53–56. http://dx.doi.org/10.1145/3615952.3615967.
Abstract:
The workshop took place in Zurich and online from August 2 to 4, 2022. It was attended by researchers from 17 academic institutions and industry labs, including Microsoft Gray Systems Lab, Omics Data Automation, Oracle Labs Zurich, RelationalAI, and TigerGraph. It featured 18 talks and plenty of opportunities for discussions. The vast majority of participants attended in person.
3
Ruiz, A., P. E. Lopez-de-Teruel, and M. C. Garrido. "Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians." Journal of Artificial Intelligence Research 9 (October 1, 1998): 167–217. http://dx.doi.org/10.1613/jair.533.
Abstract:
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard probabilistic principles and illustrative examples are provided in the fields of nonparametric pattern classification, nonlinear regression and pattern completion. Finally, experiments on a real application and comparative results over standard databases provide empirical evidence of the utility of the method in a wide range of applications.
4
Huang, Zezhou, Rathijit Sen, Jiaxiang Liu, and Eugene Wu. "JoinBoost: Grow Trees over Normalized Data Using Only SQL." Proceedings of the VLDB Endowment 16, no. 11 (July 2023): 3071–84. http://dx.doi.org/10.14778/3611479.3611509.
Abstract:
Although dominant for tabular data, ML libraries that train tree models over normalized databases (e.g., LightGBM, XGBoost) require the data to be denormalized as a single table, materialized, and exported. This process is not scalable, slow, and poses security risks. In-DB ML aims to train models within DBMSes to avoid data movement and provide data governance. Rather than modify a DBMS to support In-DB ML, is it possible to offer competitive tree training performance to specialized ML libraries...with only SQL? We present JoinBoost, a Python library that rewrites tree training algorithms over normalized databases into pure SQL. It is portable to any DBMS, offers performance competitive with specialized ML libraries, and scales with the underlying DBMS capabilities. JoinBoost extends prior work from both algorithmic and systems perspectives. Algorithmically, we support factorized gradient boosting, by updating the Y variable to the residual in the non-materialized join result. Although this view update problem is generally ambiguous, we identify addition-to-multiplication preserving , the key property of variance semi-ring to support rmse the most widely used criterion. System-wise, we identify residual updates as a performance bottleneck. Such overhead can be natively minimized on columnar DBMSes by creating a new column of residual values and adding it as a projection. We validate this with two implementations on DuckDB, with no or minimal modifications to its internals for portability. Our experiment shows that JoinBoost is 3× (1.1×) faster for random forests (gradient boosting) compared to LightGBM, and over an order of magnitude faster than state-of-the-art In-DB ML systems. Further, JoinBoost scales well beyond LightGBM in terms of the # features, DB size (TPC-DS SF=1000), and join graph complexity (galaxy schemas).
5
Bakibayev, Nurzhan, Tomáš Kočiský, Dan Olteanu, and Jakub Závodný. "Aggregation and ordering in factorised databases." Proceedings of the VLDB Endowment 6, no. 14 (September 2013): 1990–2001. http://dx.doi.org/10.14778/2556549.2556579.
6
Bakibayev, Nurzhan, Dan Olteanu, and Jakub Závodný. "Demonstration of the FDB query engine for factorised databases." Proceedings of the VLDB Endowment 5, no. 12 (August 2012): 1950–53. http://dx.doi.org/10.14778/2367502.2367545.
7
Hutchinson, Harry. "Smarter Factories." Mechanical Engineering 123, no. 03 (March 1, 2001): 60–62. http://dx.doi.org/10.1115/1.2001-mar-2.
Abstract:
This article highlights about getting more out of information technology, from online services to digital databases, in order to make plants more flexible, to improve product development, or to let people at far-flung sites cooperate more closely. There are industry-led groups namely the Consortium for Advanced Manufacturing-International, which has an office in Bedford, TX, and Intelligent Manufacturing Systems, headquartered in Tokyo. These organizations address concerns ranging from budgeting to the best practices for designing a plant floor. The Consortium for Advanced Manufacturing and Intelligent Manufacturing Systems support a research initiative called Next Generation Manufacturing Systems (NIST). NIST also operates the Manufacturing Engineering Laboratory, where a variety of projects are being run. In another part of NIST—the physics lab, to be specific—Marc Desrosiers, a research chemist, has led an effort to cut the time and cost of certifying the calibration of irradiation equipment, which can be used to cure materials and coatings, or to kill bacteria on products ranging from medical devices to hamburger.
8
Beck, Thomas J. "China and the Modern World, Imperial China and the West, Part I, 1815‐1881." Charleston Advisor 24, no. 4 (April 1, 2023): 16–19. http://dx.doi.org/10.5260/chara.24.4.16.
Abstract:
China and the Modern World, Imperial China and the West, one of several Gale Primary Sources databases, consists of two parts and this database is the first, covering 1815‐1881. The documents are drawn from the FO 17 and FO 605 series of British Foreign Office files held at the UK National Archives. The database contains correspondence relating to China from missionaries, interpreters, the factories of Canton (modern Guangzhou), interpreters, envoys, legations, consulates, and missions sent to China from Britain. Included are materials on war, diplomacy, international law, rebellions, trade, piracy, treaty ports, cross-cultural communication, and emigration. Also included are materials regarding the internal politics and relationship between China and Britain, as well as the relationships between other Western powers involved in East Asia. While this database is relatively easy to navigate, its search functions, though understandable, frequently do not provide results that are apparently relevant to the query submitted. Nevertheless, it provides an impressive collection of primary sources on the history of China in this time period, especially with regard to its relationship with Britain and the West. The database can be subscribed to or purchased. The starting purchase price ranges from $5,405 (with an annual hosting fee starting at $49) to $7,721 (with an annual hosting fee of $69). Libraries and other institutions may or may not find this pricing reasonable, depending on their budgets and need for materials on Chinese and British history in this time period. The licensing agreement for this database is too long and detailed, but has average provisions and presents little reason for concern.
9
Hatou, Kenji, Toshinobu Takeuchi, and Yasushi Hashimoto. "Image Database for the Remote Control of Plant Factories in the Internet Age." IFAC Proceedings Volumes 33, no. 19 (July 2000): 309–14. http://dx.doi.org/10.1016/s1474-6670(17)40929-3.
10
Reining, Nine, and Simone Kauffeld. "Empirical Findings on Learning Success and Competence Development at Learning Factories: A Scoping Review." Education Sciences 12, no. 11 (October 29, 2022): 769. http://dx.doi.org/10.3390/educsci12110769.
Abstract:
To meet the changing competence requirements for employees in engineering professions, education and training need to adapt accordingly. Learning factories offer various possibilities to design or integrate practice-oriented learning into training measures. Whether this approach in fact facilitates learning and competence development is rarely investigated. For this reason, the objective of this scoping review is to analyze and summarize the existing empirical findings on learning success and competence development in learning factories regarding their evaluation methods and results. Following standardized guidelines (PRISMA, JBI) for scoping reviews, 12 databases were researched. The literature screening led to the identification of 24 publications included in the final analysis. The results indicate that a variety of evaluation methods are used to assess learning and competences at learning factories and that criteria of all four competence facets (professional, methodological, social, and self-competence) can be enhanced at learning factories in general. As many of the identified studies show potential for improvement regarding the quality of the used methods and analysis of results, further studies on these topics are needed. Evaluations should be integrated into all training measures at learning factories to ensure learning success and competence development and to be able to readjust design, structure, and didactics where necessary.
11
Savytska, L. A., I. S. Bosak, N. V. Dobrovolska, and S. V. Bohomolov. "FILLING DATABASE THROUGH COLLECTIONS." Information technology and computer engineering 57, no. 2 (2023): 58–62. http://dx.doi.org/10.31649/1999-9941-2023-57-2-58-62.
Abstract:
ERP (Enterprise Resource Planning) information systems are necessary components of modern business, which play a critical role in managing enterprise resources and integrating business processes. By providing centralized management, integration, and automation, ERP systems help businesses effectively manage their operations, reduce costs, increase productivity, and make informed decisions. ERP information systems consist of various modules that interact with each other and provide comprehensive functionality for managing various aspects of the organization's activities. There are many popular ERP systems on the market that meet the needs of various industries and organizations. These systems are only a few examples on the market for ERP systems, there are many other solutions that can meet the specific needs of organizations of different sizes and industries. The choice of the system should take into account the needs of the enterprise, the budget, scalability and integration capabilities. Thus, an example of ERP - a system that takes into account the specifics of resource planning of industrial companies of PJSC "PlasmaTech" is called the "PlasmIS" information system. This system is constantly being developed and improved, taking into account the changing needs of factories producing welding electrodes, starting from the supply of materials and raw materials to the manufacture of finished products. Expansion and creation of new modules in the "PlasmIS" system take place in accordance with the tasks set, in particular in the field of filling the database through collections, providing new functionality of the system." [1]. This article presents a research study on the use of collections for populating databases. Various types of collections and their advantages are discussed, and methods for inserting data from collections into databases are analyzed. The impact of using collections on system performance is also investigated. The research confirms the effectiveness of using collections for populating databases and improving system performance.
12
Wang, Yan, Cai Ying Li, Heng Liang Mo, Yan Zhi Sun, Yong Mei Chen, and Ping Yu Wan. "Extraction of Chemical Fingerprint in Food Industry Wastewater." Advanced Materials Research 726-731 (August 2013): 1484–90. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.1484.
Abstract:
Wastewater source tracing technology is a method to find the pollution wrecker based on wastewater chemical fingerprint database. How to extract and verify the chemical fingerprints of each factory is the key technology. Here report the extraction of chemical fingerprint by taking two factories (food brewing and food processing factories) surrounding Tong Zhou North Canal (Beijing) as representatives. Firstly, the organic chemicals, anions, heavy metal ions in wastewater are detected respectively by gas chromatography-mass spectrometry (GC-MS), ion chromatography (IC), inductively coupled plasma mass spectrometry (ICP-MS) and three-dimensional excitation emission matrix fluorescence spectroscopy (3D-EEM). According to the screening principles of chemical fingerprints, the pollution and characteristic fingerprints of two factories are identified. Finally, the simulated water samples were used to test the stability and feasibility of the extracted chemical fingerprints.
13
Yao, Albert Wen Long, and H. C. Chen. "An Intelligent Color Image Recognition and Mobile Control System for Robotic Arm." International Journal of Robotics and Control Systems 2, no. 1 (February 11, 2022): 97–104. http://dx.doi.org/10.31763/ijrcs.v2i1.557.
Abstract:
The aim of this study is to develop intelligent color recognition, mobile control, and monitoring system for a pick-and-place robotic arm for manufacturing systems. The demand for smart manufacturing factories with real-time control of fabricating processes and traceability of production information is increasing urgently. Generally speaking, a smart manufacturing facility is usually composed of sensing, computing, control, and communication technologies together. In this study, the three-tier architecture of the Internet of things (IoT) was adopted as a guideline to design mobile devices to control and monitor a color image recognition and alarm monitoring system by using Raspberry Pi and a web page database. The practical results and contributions of this study are as follows: With integrating the techniques of advanced BR PLC, mobile devices and APP, color image recognition, Raspberry Pi microcomputer, and MySQL database technologies together, (1) the mobile control and monitoring system is able to supervise a real-time manufacturing plant anywhere and anytime with mobile devices easily; (2) the color identification system can identify and classify different color work-piece precisely, and the identification results are recorded for remote database platform; (3) the collected data are analyzed and displayed on mobile devices through the web database for field operators and engineers promptly. It provides a very successful practical paradigm to promote conventional factories to meet industry 4.0.
14
Shi, Zhenkun, Pi Liu, Xiaoping Liao, Zhitao Mao, Jianqi Zhang, Qinhong Wang, Jibin Sun, Hongwu Ma, and Yanhe Ma. "Data-Driven Synthetic Cell Factories Development for Industrial Biomanufacturing." BioDesign Research 2022 (July 1, 2022): 1–12. http://dx.doi.org/10.34133/2022/9898461.
Abstract:
Revolutionary breakthroughs in artificial intelligence (AI) and machine learning (ML) have had a profound impact on a wide range of scientific disciplines, including the development of artificial cell factories for biomanufacturing. In this paper, we review the latest studies on the application of data-driven methods for the design of new proteins, pathways, and strains. We first briefly introduce the various types of data and databases relevant to industrial biomanufacturing, which are the basis for data-driven research. Different types of algorithms, including traditional ML and more recent deep learning methods, are also presented. We then demonstrate how these data-based approaches can be applied to address various issues in cell factory development using examples from recent studies, including the prediction of protein function, improvement of metabolic models, and estimation of missing kinetic parameters, design of non-natural biosynthesis pathways, and pathway optimization. In the last section, we discuss the current limitations of these data-driven approaches and propose that data-driven methods should be integrated with mechanistic models to complement each other and facilitate the development of synthetic strains for industrial biomanufacturing.
15
Jerman, Andrej, Mirjana Pejić Bach, and Andrej Bertoncelj. "A Bibliometric and Topic Analysis on Future Competences at Smart Factories." Machines 6, no. 3 (September 16, 2018): 41. http://dx.doi.org/10.3390/machines6030041.
Abstract:
The aim of the study is to review the topic of competences that will be present at smart factories. The study used bibliometric and topic analysis to achieve insight into new trends in Industry 4.0. Bibliometric analysis and topic mining was done on 43 peer-reviewed journal articles and conference papers, published before July 2018 in the Thomson Reuters’ Web of Science and Scopus databases, using the software tool Statistica Data Miner. Results are segmented into four sections: (1) personnel development in learning organizations, (2) training techniques for personnel, (3) future engineering profiles and engineering education, and (4) relational capabilities. Each section is thoroughly discussed in this paper. The study contributes to the pool of knowledge on Industry 4.0 phenomena by compiling competences needed at smart factories in the future.
16
Praekunatham, Hirunwut, Sutatip Buranasatitnon, and Hansa Ruksakom. "Situation and Spatial Analysis of the COVID-19 Epidemic in Business Establishments: Comparison between the Delta and Omicron Variants in Thailand, July 2021–May 2022." Outbreak, Surveillance, Investigation & Response (OSIR) Journal 15, no. 4 (December 30, 2022): 114–22. http://dx.doi.org/10.59096/osir.v15i4.262274.
Abstract:
COVID-19 outbreaks in business establishments cause a stagnant economy. In Thailand, the COVID-19 situation in business establishments has never been investigated. This study aims to (1) describe the situation and (2) compare characteristics, including spatial patterns, of COVID-19 cases in business establishments between the Delta (July–December 2021) and Omicron (January–May 2022) predominant periods. A cross-sectional study was conducted using secondary data extracted from the Department of Disease Control’s database, which was linked to listed company and factory databases. The study population included all reported COVID-19 cases. The proportions of case characteristics between the delta and omicron dominant periods were compared using Pearson’s Chi-square test. Spatial autocorrelation was tested using Moran’s I statistics. During July 2021–May 2022, 443,448 COVID-19 cases were reported in business establishments. The proportions of cases in factories and construction camps decreased from 41.3% and 6.7% in the Delta dominant period to 14.4% and 1.7% in the Omicron dominant period, respectively. A high number of cases occurred in businesses operating food production, wholesale/retail, transportation, and accommodation. Clustering patterns were evident in the central and eastern regions of Thailand where many business establishments are located. Public health agencies should promote organizational COVID-19 prevention measures and increase worker’s awareness in high-risk industries.
17
Chen, Fu, Le Yuan, Shaozhen Ding, Yu Tian, and Qian-Nan Hu. "Data-driven rational biosynthesis design: from molecules to cell factories." Briefings in Bioinformatics 21, no. 4 (June 26, 2019): 1238–48. http://dx.doi.org/10.1093/bib/bbz065.
Abstract:
Abstract A proliferation of chemical, reaction and enzyme databases, new computational methods and software tools for data-driven rational biosynthesis design have emerged in recent years. With the coming of the era of big data, particularly in the bio-medical field, data-driven rational biosynthesis design could potentially be useful to construct target-oriented chassis organisms. Engineering the complicated metabolic systems of chassis organisms to biosynthesize target molecules from inexpensive biomass is the main goal of cell factory design. The process of data-driven cell factory design could be divided into several parts: (1) target molecule selection; (2) metabolic reaction and pathway design; (3) prediction of novel enzymes based on protein domain and structure transformation of biosynthetic reactions; (4) construction of large-scale DNA for metabolic pathways; and (5) DNA assembly methods and visualization tools. The construction of a one-stop cell factory system could achieve automated design from the molecule level to the chassis level. In this article, we outline data-driven rational biosynthesis design steps and provide an overview of related tools in individual steps.
18
Liu, Li Juan, Wen Ge Wu, and Ming Lv. "Design of Database for High Speed Cutting of Difficult-to-Cut Materials." Materials Science Forum 723 (June 2012): 337–42. http://dx.doi.org/10.4028/www.scientific.net/msf.723.337.
Abstract:
High speed machining (HSM) is one of the main trends of cutting machinery and is an important development direction of advanced manufacturing technology. In our country, the relevant research of HSM database starts later, especially of the cutting of hardworking material, the actual machining and experiment on the machining technology and the machining parameters of HSM are few, the reasonable machining parameters selection scheme and the appropriate cutter choice method are lack. The paper established HSM database system of the hardworking material based on web to improve cutting efficiency. According to the different feed and cutting tool by the Web form, it gets the rational cutting parameters. And the system determines the tool-path planning by the manufacture HSM of hardworking material processing animation to simulate the high-speed milling. The results of inquiry as a Web page and let you get parameters of optimization, increases efficiency of factories.
19
Wang, Dejiang, and Haojie Lu. "Development of a BIM Platform for the Design of Single-Story Steel Structure Factories." Buildings 14, no. 3 (March 10, 2024): 747. http://dx.doi.org/10.3390/buildings14030747.
Abstract:
Traditional design methods for single-story steel structure factories are characterized by low levels of digitalization and high error rates. To deal with these problems, a building information modeling (BIM) platform for the design of single-story steel structure factories was developed in this paper, which aimed to improve the design process for such structures. Firstly, the components of the factory were categorized, and the Revit API was employed to automate the generation of the BIM model. Load applications and combinations were then established using the Revit API, which relied on a set of predefined parameters. Secondly, this paper proposed the creation of a dedicated database for data exchange between BIM software and finite element analysis software. Additionally, the SAP2000 Open Application Programming Interface (OAPI) was employed for the automated construction and analysis of the SAP2000 structural model. Finally, the innovative use of Dynamo–Revit API hybrid programming allowed for the visualization of internal forces directly within the Revit environment, significantly diminishing the dependency on standalone FEA software. The application results obtained on a project demonstrated that the developed platform markedly improves the efficiency of design single-story steel structure factories and ensures the accuracy of the structural analysis. This confirms that the developed platform can transform the traditional design process by integrating advanced digital tools, thereby providing a novel approach to the design of single-story steel structure factories.
20
D P, Ms Sai Sandhya, and Mrs Renuka Malge. "Generating Unique Identification Number to Product Manufacturing." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 1504–7. http://dx.doi.org/10.22214/ijraset.2022.45511.
Abstract:
Abstract: It is possible to identify any product that is created, stored, or sold out using a unique identification number. It demonstrates how this programme of intermediary organisations which have been generating identification to Products of groups' exposes the purposes and Product IDs of those organisations. An increasing number of entities now have unique identifiers (UIN). UIN has the potential to make database integrations considerably more effective, which is one benefit. In order to locate duplicate records within a database or to compare identical publications across databases, unique identifiers (UIN) are thought to be an effective key. The goal of the current study is to determine how effectively UIN serve as matching criteria in the integration of product ID and manufactured product. We analyse this data to find any matching errors that may have occurred. Users of the UIN Portal application, both internal and external, will be able to request that UINs be allocated to goods made in their factories. Therefore, this project aims to create features that let users accomplish this. This project seeks to provide UIN generating features as well as Commissioning capability and will enable users to keep master data necessary for the application. These systems' main aim is to build or construct a UIN identifier for a manufactured or stored product. The information is also kept in a data base use. Additionally, it helps both the client and the administrator track products requests made to produce UINs or storing in warehouses. Once the product is no longer in use, the UIN retires. The UIN will be deleted before it is returned to the warehouse. It only becomes invalid if a defective component is fabricated and a UIN is assigned to the manufactured product. Additionally, it should be able to give the security aspect so that White box and penetration testing may be done.
21
Brailovsky, Peter, Lorena Sanchez, Dilara Subasi, Jochen Rentsch, Ralf Preu, and Sebastian Nold. "Photovoltaic Manufacturing Factories and Industrial Site Environmental Impact Assessment." Energies 17, no. 11 (May 24, 2024): 2540. http://dx.doi.org/10.3390/en17112540.
Abstract:
Life cycle inventories (LCIs) and life cycle assessments (LCAs) of photovoltaic (PV) modules and their components focus on the operations of PV factories, but the factories and industrial site product and construction stages are either not or only partially tackled. This work contributes through the bottom-up, model-based generation of LCIs and LCAs for setting up a vertically integrated 5 GWp/a PV industrial site, including the manufacturing of silicon ingots, wafers, solar cells, and PV modules, on a 50 ha greenfield location. Two comparative LCAs are performed. The first compares the annualized environmental impacts of the developed LCI sets with four existing inventories in the Ecoinvent v3.8 database. The second comparative LCA explores the environmental impact differences concerning the industrial site when using different building systems for the factories. Here, the reference system with a steel structure is compared with two alternative building systems: precast concrete and structural timber. The results show that the wafer, cell, and module factories’ annualized environmental impacts with the Ecoinvent LCIs are strongly overestimated. For the ingot factory, the opposite result is identified. The impacts of all four factories show reductions of between 11.7% and 94.3% for 14 of the 15 impact categories. High mean environmental impact shares of 79.0%, 78.2% and 79.2% for the steel, precast concrete and timber structural building systems, respectively, are generated at the product stage. The process and facilities equipment generates 54.2%, 54.4% and 58.2% of the total product and construction stages’ mean environmental impact shares. The proposed alternative timber building system reduces the environmental impacts in 14 of the 15 evaluated categories, with reductions ranging from 1.1% to 12.4%.
22
Asgedom, Akeza Awealom. "Dust Exposure and Respiratory Health among Selected Factories in Ethiopia: Existing Evidence, Current Gaps and Future Directions." Journal of Respiration 3, no. 2 (May 4, 2023): 49–59. http://dx.doi.org/10.3390/jor3020006.
Abstract:
Workers who are working in dusty environments might be associated with respiratory health problems. In Ethiopia, factories processing wood, textile, coffee, flour, cement and other materials are associated with dust emission. Furthermore, despite the adoption of the International Labor Organization (ILO) convention, the available constitution and labor proclamation, there are a lot of gaps in terms of occupational health and safety measures in Ethiopia. The current review aims to examine the existing evidence, current challenges and future direction regarding dust exposure and respiratory health in selected Ethiopian factories. Searches of peer-reviewed articles with full-length papers were made in online databases such as PubMed, Web of Science, MEDLINE, EMBASE and Google Scholar with a key words “Dust exposure”, “Respiratory health”, “Respiratory symptom”, “Ethiopia” and “Factory workers” from January 2000 to March 2023. The review found that excessive dust exposure is associated with a high prevalence of respiratory health problems. Lack of personal protective equipment and absence of safety and health training were the main occupational health deficits identified in most factories. Actions that focus on these deficiencies are commendable. Interventions focused on safety and health trainings, and the provision of adequate personal protective equipment of the required quality is recommended. In addition, administrative solutions and longitudinal studies on dust exposure and respiratory health are suggested.
23
Cavas, Bulent. "INDUSTRY 4.0 AND SCIENCE EDUCATION." Journal of Baltic Science Education 18, no. 5 (October 12, 2019): 652–53. http://dx.doi.org/10.33225/jbse/19.18.652.
Abstract:
Industry 4.0 and its applications are one of the most important issues of countries that want to keep their competitiveness in the field of scientific, technological and innovation in today's world. The Countries that are not able to adapt to Industry 4.0 processes will not be able to develop scientifically and technologically or keep up with current innovation processes. One of the aims of this paper is to explain the concept of industry 4.0 to our readers in a comprehensible manner and to show how much science education is actually related to industry 4.0. In a general sense, Industry 4.0 or in other words, the 4th Industrial Revolution is an expression that includes many modern automation processes, large databases that communicate with each other, robotic devices and dark factories, in short, quality production technologies. In addition, Industry 4.0 includes modern technologies such as additive manufacturing, autonomous robots, big data, artificial intelligence, augmented reality, system integration, internet of things, cybersecurity, cloud computing, machine learning, deep learning etc. These technologies play an important role especially in the formation of new smart factories.
24
Tanaka, Kenji, Shen-Ming Gu, and Jing Zhang. "Designing Multi-Agent Simulation with Big Time Series Data for a Global Supply Chain System." International Journal of Automation Technology 10, no. 4 (July 5, 2016): 632–38. http://dx.doi.org/10.20965/ijat.2016.p0632.
Abstract:
Multinational corporations produce products at relatively few factories and then sell those products in all areas of the world. Longer lead times increase the risk of fluctuations in product demand. To reduce this risk, the entire business chain, from production to sale, must be optimized. In this study, we propose, implement, and verify a total optimization system. This system uses multi-agent simulation on big time series data. It consists of management, integrated database, and operation modules.
25
LEE, CHAN-SU, and AHMED ELGAMMAL. "DYNAMIC SHAPE STYLE ANALYSIS: BILINEAR AND MULTILINEAR HUMAN IDENTIFICATION WITH TEMPORAL NORMALIZATION." International Journal of Pattern Recognition and Artificial Intelligence 24, no. 07 (November 2010): 1133–57. http://dx.doi.org/10.1142/s0218001410008330.
Abstract:
Modeling and analyzing the dynamic shape of human motion is a challenging task owing to temporal variations in the shape and multiple sources of observed shape variations such as viewpoint, motion speed, clothing, etc. We present a new framework for dynamic shape analysis based on temporal normalization and factorized shape style analysis. Using a nonlinear generative model with motion manifold embedding in a low-dimensional space, we detect cycles of periodic motion like gait in different views and synthesize temporally-aligned shape sequences from the same type of motion at different speeds. The bilinear analysis of temporally-aligned shape sequences decomposes dynamic motion into time-invariant shape style factors and time-dependent motion factors. We extend the bilinear model into a tensor shape model, a multilinear decomposition of dynamic shape sequences for view-invariant shape style representations. The shape style is a view-invariant, time-invariant, and speed-invariant shape signature and is used as a feature vector for human identification. The shape style can be adapted to new environmental conditions by iterative estimation of style and content factors to reflect new observation conditions. We present the experimental results of gait recognition using the CMU Mobo gait database and the USF gait challenging database.
26
Xia, Yan Chun. "The Establishment of a Flexible PdM System for Industry Detection." Applied Mechanics and Materials 263-266 (December 2012): 457–61. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.457.
Abstract:
The universal predictive maintenance(PdM) system framework integrated several common and important technologies is established in the paper. It is very important to choose and design the relative technologies for the PdM system in the real application at different factories. Here the reasons and method of the system establishment are explained. The functions and structures of the system are analyzed. The establishment of the database of the system is proposed. The PdM system can be realized flexibly based on the real conditions in the real industry application.
27
Jayasekara, Sivakolundu, Hithanadura Dassanayake, and Anil Fernando. "A Novel Image Retrieval System Based on Histogram Factorization and Contextual Similarity Learning." Applied Mechanics and Materials 380-384 (August 2013): 4148–51. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.4148.
Abstract:
Image retrieval has been a top topic in the field of both computer vision and machine learning for a long time. Content based image retrieval, which tries to retrieve images from a database visually similar to a query image, has attracted much attention. Two most important issues of image retrieval are the representation and ranking of the images. Recently, bag-of-words based method has shown its power as a representation method. Moreover, nonnegative matrix factorization is also a popular way to represent the data samples. In addition, contextual similarity learning has also been studied and proven to be an effective method for the ranking problem. However, these technologies have never been used together. In this paper, we developed an effective image retrieval system by representing each image using the bag-of-words method as histograms, and then apply the nonnegative matrix factorization to factorize the histograms, and finally learn the ranking score using the contextual similarity learning method. The proposed novel system is evaluated on a large scale image database and the effectiveness is shown.
28
Tziavelis, Nikolaos, Wolfgang Gatterbauer, and Mirek Riedewald. "Beyond equi-joins." Proceedings of the VLDB Endowment 14, no. 11 (July 2021): 2599–612. http://dx.doi.org/10.14778/3476249.3476306.
Abstract:
We study theta-joins in general and join predicates with conjunctions and disjunctions of inequalities in particular, focusing on ranked enumeration where the answers are returned incrementally in an order dictated by a given ranking function. Our approach achieves strong time and space complexity properties: with n denoting the number of tuples in the database, we guarantee for acyclic full join queries with inequality conditions that for every value of k , the k top-ranked answers are returned in O ( n polylog n + k log k ) time. This is within a polylogarithmic factor of O ( n + k log k ), i.e., the best known complexity for equi-joins, and even of O ( n + k ), i.e., the time it takes to look at the input and return k answers in any order. Our guarantees extend to join queries with selections and many types of projections (namely those called "free-connex" queries and those that use bag semantics). Remarkably, they hold even when the number of join results is n ℓ for a join of ℓ relations. The key ingredient is a novel O ( n polylog n )-size factorized representation of the query output , which is constructed on-the-fly for a given query and database. In addition to providing the first nontrivial theoretical guarantees beyond equi-joins, we show in an experimental study that our ranked-enumeration approach is also memory-efficient and fast in practice, beating the running time of state-of-the-art database systems by orders of magnitude.
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Yang, Yu Xue, Xiang Su, Jian Lu, and Ye Wei Xu. "Review on Smart Factory Operations: A Bibliometric Analysis." Applied Mechanics and Materials 906 (April 29, 2022): 87–104. http://dx.doi.org/10.4028/p-40l741.
Abstract:
Over the last few years, existing and emerging Information and Communication Technologies (ICT) and artificial intelligence have been changing the way that factories conduct their manufacturing activities. Operation system of smart factories has been of great interest to researchers in recent years. However, the research concerning operations for the smart factory is still at the nascent stage. To address this need, we conduct a citation and co-citation analysis on smart factory operation system research published in the 11-year period from 2010-2020. A total of 351 papers were selected from Web of Science database. In the citation analysis, we depend on the degree centrality and betweenness centrality to identify 36 important papers. In addition, our main path analysis reveals the role of ICT in facilitating fast development of operation in smart factory. In the co-citation analysis, we identify four major research themes: resource reconfiguration, predictive production planning model, collaborative scheduling mechanism and technology basis of logistics. This is among the first studies to examine the knowledge structure of smart factory operations research by using evidence-based analysis methods. Recommendations for the future research directions have suggested based on our analysis.
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Liu, Bai Lin, Wen Chen, Lei Li, and Qin Ren Xiong. "Material Performance Data Acquisition and Management System for Welded Pipe Used in the 2nd West-East Gas Pipeline." Advanced Materials Research 581-582 (October 2012): 1176–79. http://dx.doi.org/10.4028/www.scientific.net/amr.581-582.1176.
Abstract:
To improve the performance data management efficiency of welded pipe used in the 2nd west to east gas pipeline, a distributed performance data acquiring and management system for welded pipe was developed. The system was established by using two-level three-tier Client/Server model. Performance data for welded pipe from different factories was acquired at clients and input to local database. The data then can be analyzed at local, or be transferred to the server through networks for unified storage and analysis. The System has functions as data management, file transferring, standard technology condition management, statistical analysis, figure displaying and statistical analysis report generation, etc. The system was implemented using VC++. Oracle and Access is adopted as database for server and client respectively, XML is as the data encapsulation for transferring file. The developed system plays a significant role in analyzing and evaluating the whole quality of welded pipe, and is useful for pipeline quality control.
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Nikolyukin, Danila, Vladimir Peters, Mikhail Popov, and Andrey Kryshchenko. "CHOOSING A NEURAL NETWORK MODEL AND ARCHITECTURE FOR A TECHNICAL VISION SYSTEM FOR DETECTING SUGAR BEET ROOT CROPS." SCIENCE IN THE CENTRAL RUSSIA, no. 2 (April 27, 2024): 98–105. http://dx.doi.org/10.35887/2305-2538-2024-2-98-105.
Abstract:
The use of a technical vision system, aimed at ensuring greater safety of sugar beet roots during harvesting and storage by analyzing raw materials arriving at factories, is considered among the methods of long-term storage. The process of distribution of trucks at the receiving point of sugar factories is considered by humans in the work. The purpose of the work is to develop a method for detecting sugar beet roots on an image of the surface of a truck embankment at the receiving point of sugar factories. A neural network was chosen as the raw material recognition method due to the extremely diverse nature of the resulting images, which recognition using a threshold transformation cannot cope with. Algorithms (options such as SSD, YOLO, R-CNN) and architectures (options such as AlexNet, VGGNet, GoogleNet, ResNet) of various neural networks are considered. The most suitable neural network for the required tasks has been identified. The optimal size of the database for training has been determined. As a result of training and testing the neural network, the need to create additional filters was identified. Filters have been created and described that clarify the work of the neural network: filtering out “stuck together” objects, objects with low class membership, objects with an impossible area (too small or large), as well as with an aspect ratio of less than 0.2 or more than 5. A neural network capable to find a sufficient number of sugar beet roots in incoming images and to meet the requirements for high-quality functioning of the technical vision system, was trained based on the results of the work performed.
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CHAVES JUNIOR, Wankes Solony de Carvalho. "Engenharia de Materiais no âmbito da Indústria 4.0." RCMOS - Revista Científica Multidisciplinar O Saber 1, no. 6 (January 22, 2024): 1–9. http://dx.doi.org/10.51473/rcmos.v1i1.2020.112.
Abstract:
Industry 4.0 has shown itself to be substantially present in manufacturing industries, and its processes can be associated with so-called smart factories, with technology used to optimize activities, seeking, therefore, to guarantee accurate results in comparison with companies that are not included. no model of industry 4.0. The objective of this article is to carry out an integrative review of the literature with a view to delineating the changes possibly required for Industry 4.0 in the area of material engineering to adapt it to this new industrial revolution (fourth) cenário. The operationalization of the research corresponding to or that is proposed contemplates the realization of consultation of the Capes, Google Academic and Science databases by means of information on the following keywords: Industry 4.0, Quarta Revolução Industrial, Engenharia de Materiais.
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Yaghi, Y., and H. Salim. "INTEGRATION OF RS/GIS FOR SURFACE WATER POLLUTION RISK MODELING. CASE STUDY: AL-ABRASH SYRIAN COASTAL BASIN." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 13, 2017): 949–54. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-949-2017.
Abstract:
Recently the topic of the quality of surface water (rivers – lakes) and the sea is an important topics at different levels. It is known that there are two major groups of pollutants: Point Source Pollution (PSP) and non-point Source pollution (NPSP). Historically most of the surface water pollution protection programs dealing with the first set of pollutants which comes from sewage pipes and factories drainage. <br><br> With the growing need for current and future water security must stand on the current reality of the coastal rivers basin in terms of freshness and cleanliness and condition of water pollution. <br><br> This research aims to assign the NPS pollutants that reach Al Abrash River and preparation of databases and producing of risk Pollution map for NPS pollutants in order to put the basin management plan to ensure the reduction of pollutants that reach the river. This research resulted of establishing of Databases of NPSP (Like pesticides and fertilizers) and producing of thematic maps for pollution severity and pollution risk based on the pollution models designed in GIS environment and utilizing from remote sensing data. Preliminary recommendations for managing these pollutants were put.
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Li, Hai Ming, Li Mei Zhang, and Feng Sa. "Design the Integrated Multipurpose Instrument Calibrating Equipment Based on the PXI and LabVIEW." Advanced Materials Research 1037 (October 2014): 134–38. http://dx.doi.org/10.4028/www.scientific.net/amr.1037.134.
Abstract:
According to the function, the technical indexes and the cost control etc, we select the embedded control computer and virtual instrument module based on the PXI, and developed the integrated multipurpose instrument calibrating equipment, it realized the field measurement and calibration of the electrical instrument away from the laboratory. The system is designed based on PXI and LabVIEW, it uses virtual instrument technology, automatic control technology and database technology, by combining these functional modules of NI, we realized the calibration of electrical instruments such as digital multimeter, signal generator, oscilloscope and cymometer etc. The system is used integrated design, and it is very flexible, it can be popularized and applied as working standard to troops, factories or schools etc.
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Cao, Yan, Sen Cao, Yu Bai, and Xiao Fei Yang. "CBR-Based Cutting Parameter Selection System and Searching Algorithm for Metal Machining Operations." Advanced Materials Research 710 (June 2013): 554–57. http://dx.doi.org/10.4028/www.scientific.net/amr.710.554.
Abstract:
At present, most factories choose cutting parameters only depending on experience or handbooks in production. To improve the intelligent level of cutting parameter selection, Case-Based Reasoning (CBR) is used to search rational cutting parameters. The structure of a CBR-based cutting parameter selection system is presented and its functional modules are discussed. CBR-based cutting parameter selection system is mainly composed of case base management system, cutting parameter database management system, application, interface, etc. A complete case is composed of four parts, i.e., objectives, initial conditions, constraints and results. The system adopts hierarchical searching method in combination with nearest neighbor method. It provides a scientific approach for selecting cutting parameters in actual production.
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Segarwati, Yulia, Nurhayati Nurhayati, Trisa Nurkania, Yuyun Yuniarti, and Maun Jamaludin. "Implementation of supply chain management using the ERP system at XYZ Company Indonesia." Research Horizon 2, no. 6 (December 22, 2022): 561–67. http://dx.doi.org/10.54518/rh.2.6.2022.561-567.
Abstract:
Supply Chain Management (SCM) is a network of companies working to create and deliver a product to the end user. These companies include suppliers, factories, distributors, shops or retail, as well as supporting companies such as logistics services. The company is integrated with an ERP or enterprise resource planning system that combines each department into one database to save time in its use. In this study, researchers implemented supply chain management and this ERP system at XYZ Company Indonesia. A company engaged in the marketing and distributing various goods for consumption, including toiletries, body care, cosmetics, and cooking spices, which of course, gives an advantage if it can implement this supply chain management and ERP system.
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Zhang, Guangchao, and Junrong Liu. "Intelligent vehicle modeling design based on image processing." International Journal of Advanced Robotic Systems 18, no. 1 (January 1, 2021): 172988142199334. http://dx.doi.org/10.1177/1729881421993347.
Abstract:
With the urgent demand of consumers for diversified automobile modeling, simple, efficient, and intelligent automobile modeling analysis and modeling method is an urgent problem to be solved in current automobile modeling design. The purpose of this article is to analyze the modeling preference and trend of the current automobile market in time, which can assist the modeling design of new models of automobile main engine factories and strengthen their branding family. Intelligent rapid modeling shortens the current modeling design cycle, so that the product rapid iteration is to occupy an active position in the automotive market. In this article, aiming at the family analysis of automobile front face, the image database of automobile front face modeling analysis was created. The database included two data sets of vehicle signs and no vehicle signs, and the image data of vehicle front face modeling of most models of 22 domestic mainstream brands were collected. Then, this article adopts the image classification processing method in computer vision to conduct car brand classification training on the database. Based on ResNet-8 and other model architectures, it trains and classifies the intelligent vehicle brand classification database with and without vehicle label. Finally, based on the shape coefficient, a 3D wireframe model and a curved surface model are obtained. The experimental results show that the 3D curve model can be obtained based on a single image from any angle, which greatly shortens the modeling period by 92%.
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Park, Jonghyuk, Eunyoung Choi, and Yerim Choi. "Real-World Failure Prevention Framework for Manufacturing Facilities Using Text Data." Processes 9, no. 4 (April 13, 2021): 676. http://dx.doi.org/10.3390/pr9040676.
Abstract:
In recent years, manufacturing companies have been continuously engaging in research for the full implementation of smart factories, with many studies on methods to prevent facility failures that directly affect the productivity of the manufacturing sites. However, most studies have only analyzed sensor signals rather than text manually typed by operators. In addition, existing studies have not proposed an actual application system considering the manufacturing site environment but only presented a model that predicts the status or failure of the facility. Therefore, in this paper, we propose a real-world failure prevention framework that alerts the operator by providing a list of possible failure categories based on a failure pattern database before the operator starts work. The failure pattern database is constructed by analyzing and categorizing manually entered text to provide more detailed information. The performance of the proposed framework was evaluated utilizing actual manufacturing data based on scenarios that can occur in a real-world manufacturing site. The performance evaluation experiments demonstrated that the proposed framework could prevent facility failures and enhance the productivity and efficiency of the shop floor.
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Torras, Carme. "Service Robots for Citizens of the Future." European Review 24, no. 1 (February 2016): 17–30. http://dx.doi.org/10.1017/s1062798715000393.
Abstract:
Robots are no longer confined to factories; they are progressively spreading to urban, social and assistive domains. In order to become handy co-workers and helpful assistants, they must be endowed with quite different abilities from their industrial ancestors. Research on service robots aims to make them intrinsically safe to people, easy to teach by non-experts, able to manipulate not only rigid but also deformable objects, and highly adaptable to non-predefined and dynamic environments. Robots worldwide will share object and environmental models, their acquired knowledge and experiences through global databases and, together with the internet of things, will strongly change the citizens’ way of life in so-called smart cities. This raises a number of social and ethical issues that are now being debated not only within the Robotics community but by society at large.
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Galindo, Inmaculada, Eladio Viñuela, and Angel L. Carrascosa. "Characterization of the African swine fever virus protein p49: a new late structural polypeptide." Microbiology 81, no. 1 (January 1, 2000): 59–65. http://dx.doi.org/10.1099/0022-1317-81-1-59.
Abstract:
The open reading frame B438L, located within the EcoRI B fragment of the African swine fever virus genome, is predicted to encode a protein of 438 amino acids with a molecular mass of 49·3 kDa. It presents a cell attachment RGD (Arg–Gly–Asp) motif but no other significant similarity to protein sequences in databases. Northern blot and primer extension analysis showed that B438L is transcribed only at late times during virus infection. The B438L gene product has been expressed in Escherichia coli, purified and used as an antigen for antibody production. The rabbit antiserum specific for pB438L recognized a protein of about 49 kDa in virus-infected cell extracts. This protein was synthesized late in infection by all the virus strains tested, was located in cytoplasmic virus factories and appeared as a structural component of purified virus particles.
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Zemrane, Hamza, Youssef Baddi, and Abderrahim Hasbi. "Routing Communication Inside Ad Hoc Drones Network." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 17 (September 6, 2021): 192. http://dx.doi.org/10.3991/ijim.v15i17.19179.
Abstract:
The world knows a constant development of technology applied in different sectors of activities: health, factories, homes, transportation, and others, one of the big axes that take a lot of attention today is the drone’s field. To communicate information a fleet of drones can use different communication architectures: centralized communication architecture, satellite communication architecture, cellular network communication architecture and a specific AdHoc communication architecture called the UAANET drones architecture. In our work we focused specifically on the routing of information inside the UAANET where we analyze and compare the performances of the reactive protocol AODV and the proactive protocol OLSR, when the UAANET use an applications based on the HTTP protocol, the FTP protocol, the database queries, voice application, and video conferencing application.
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He, Yuan, Xin-Yue Huang, and Francis Eng Hock Tay. "Fabric Defect Detection based on Improved Object as Point." International Journal of Computer Science and Information Technology 13, no. 3 (June 30, 2021): 1–13. http://dx.doi.org/10.5121/ijcsit.2021.13301.
Abstract:
In the field of fabric manufacturing, many factories still utilise the traditional manual detection method. It requires a lot of labour, resulting in high error rates and low efficiency. In this paper, we represent a realtime automated detection method based on object as point. This work makes three attributions. First, we build a fabric defects database and augment the data to training the intelligence model. Second, we provide a real-time fabric defects detection algorithm, which have potential to be applied in manufacturing. Third, we figure out CenterNet with soft NMS will improved the performance in fabric defect detection area, which is considered an NMS-free algorithm. Experiment results indicated that our lightweight network based method can effectively and efficiently detect five different fabric defects.
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Del Gallo, Mateo, Giovanni Mazzuto, Filippo Emanuele Ciarapica, and Maurizio Bevilacqua. "Artificial Intelligence to Solve Production Scheduling Problems in Real Industrial Settings: Systematic Literature Review." Electronics 12, no. 23 (November 22, 2023): 4732. http://dx.doi.org/10.3390/electronics12234732.
Abstract:
This literature review examines the increasing use of artificial intelligence (AI) in manufacturing systems, in line with the principles of Industry 4.0 and the growth of smart factories. AI is essential for managing the complexities in modern manufacturing, including machine failures, variable orders, and unpredictable work arrivals. This study, conducted using Scopus and Web of Science databases and bibliometric tools, has two main objectives. First, it identifies trends in AI-based scheduling solutions and the most common AI techniques. Second, it assesses the real impact of AI on production scheduling in real industrial settings. This study shows that particle swarm optimization, neural networks, and reinforcement learning are the most widely used techniques to solve scheduling problems. AI solutions have reduced production costs, increased energy efficiency, and improved scheduling in practical applications. AI is increasingly critical in addressing the evolving challenges in contemporary manufacturing environments.
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Volkov, Andrey N. Volkov, and Valeriy A. Zuev Zuev. "Technical indicators of modern trawlers." Russian Journal of Water Transport, no. 69 (December 23, 2021): 49–62. http://dx.doi.org/10.37890/jwt.vi69.215.
Abstract:
The article identifies the problem of the lack of up-to-date publicly available statistical information on the technical and economic performance of modern fishing vessels, including foreign mining vessels, which entails serious restrictions on the choice of a prototype, from which domestic authors are forced to use outdated indicators of ship designs built in the second half of the XX century. The methods of obtaining the necessary information using the open databases of the Global Fishing Watch organization are presented. The methods of the organization's work with information and the characteristics of some databases are described. The data has been processed for further use. According to one of the fishing criteria, the most effective trawlers of 2020 were selected. Thanks to the obtained statistics on the operation of trawlers, it was possible to obtain many technical indicators of the vessels ' operation: the operating mode, the structure and duration of the fishing voyage, the form of fishing organization, the balance of calendar time. As the statistics are processed, the results are analyzed. The observations made are described: about the round-the-clock operation mode; about the duration of storming; about the associated fishing. The obtained indicators were compared with the indicators of trawler factories in 1969. The necessity of continuing the study of the main technical and economic indicators of modern fishing vessels: income, expenses, profit is justified.
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Hassan, Jumana A., and Basil H. Jasim. "Design and implementation of internet of things-based electrical monitoring system." Bulletin of Electrical Engineering and Informatics 10, no. 6 (December 1, 2021): 3052–63. http://dx.doi.org/10.11591/eei.v10i6.3155.
Abstract:
Many modern monitoring and controlling projects such as systems in factories, home, and other used the internet of things (IoT). These devices perform self-functions without requiring manual intervention in order to improve convenience and safety. Electrical networks are one of the most important areas in which IoT systems can control, monitor, detect, and alarm for faultier, because detecting faults, monitoring network data, and finding the best solutions in a smaller duration of time to improve the efficiency and reliability of electrical networks. This paper proposes a system on the basis of a wireless sensor network (WSN). This system monitors and controls a variety of electrical and environmental variables, including power consumption, weather temperature, humidity, flame, lighting, and detection cut in the cable in electrical poles. Each sensor is a node and is connected to a microcontroller board separately. The data collected by these sensors is display and monitored on a web page and saved in a local server's database, this site was created with a variety of web programming languages. The system was developed using a free global domain. The website having a database for storing real-time sensor information.
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Pfeifer, Marcel Rolf. "Computer-Aided Standardisation for Manufacturing and Maintenance Activities." Technological Engineering 16, no. 1 (October 1, 2019): 22–24. http://dx.doi.org/10.1515/teen-2019-0004.
Abstract:
Abstract The paper deals with the development and application of computer-aided standardisation (CAS) for the distribution of standardisation data of production and maintenance processes within the company network. Rising integration pressure of company software tools also include CAx technologies. These CAx technologies provide software solutions for different applications, being able to work closely together with ERP-systems, Business Intelligence (BI) tools and further systems. The possibility of integration makes it also feasible to look on the CAS tool and its potential. While CAS is a topic not yet fully discussed, future development may lead to the requirement of integrating the CAS with the ERP and planning system. Approaches, such as CIM, digital factories (DF) and Industry 4.0 benefit from a broader database available with the CAS system employed
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El Jaouhari, Asmae, Soumaya Fellaki, Mohamed Amejwal, and Jabir Arif. "Industry 4.0 Implementation in Lean Supply Chain Management: a Systematic Literature Review." Statistics, Optimization & Information Computing 11, no. 1 (January 23, 2023): 178–85. http://dx.doi.org/10.19139/soic-2310-5070-1539.
Abstract:
The major aspects and impacts of the interrelationships between Industry 4.0 (I4.0) technology and Lean Supply Chain Management are discussed in this article (LSCM). Many practical LSCM systems based on I4.0 have lately appeared. Despite this, there has been little research into the use of I4.0 technologies within LSCM. Machine learning, smart factories, blockchain, and the internet of services (IoS) are all possible LSCM revolution enablers. The goal of this research is to find out more about present and potential I4.0 technologies that can improve LSCM research and application in order to fill a gap in the current literature. A Systematic Literature Review (SLR) technique was used for the collection, selection, and evaluation of published literature. We looked at 79 studies published between 2010 and 2021 that were found in the Scopus database.
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Kherraki, Amine, Muaz Maqbool, and Rajae El Ouazzani. "Efficient lightweight residual network for real-time road semantic segmentation." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 1 (March 1, 2023): 394. http://dx.doi.org/10.11591/ijai.v12.i1.pp394-401.
Abstract:
<span lang="EN-US">Intelligent transportation system (ITS) is currently one of the most discussed topics in scientific research. Actually, ITS offers advanced monitoring systems that include vehicle counting, pedestrian detection. Lately, convolutional neural networks (CNNs) are extensively used in computer vision tasks, including segmentation, classification, and detection. In fact, image semantic segmentation is a critical issue in computer vision applications. For example, self-driving vehicles require high accuracy with lower parameter requirements to segment the road scene objects in real-time. However, most related work focus on one side, accuracy or parameter requirements, which make CNN models difficult to use in real-time applications. In order to resolve this issue, we propose the efficient lightweight residual network (ELRNet), a novel and ELRNet, which is an asymmetrical encoder-decoder architecture. Indeed, in this network, we compare four varieties of the proposed factorized block, and three loss functions to get the best combination. In addition, the proposed model is trained from scratch using only 0.61M parameters. All experiments are evaluated on the popular public the cambridge-driving labeled video database (CamVid) road scene dataset and reached results show that ELRNet can achieve better performance in terms of parameters requirements and precision compared to related work.</span>
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Deharja, Atma, Muhammad Yunus, and Maya Weka Santi. "Electronic Health Records Design in the Nutrition Care Center of Teaching Factory at Politeknik Negeri Jember, Indonesia." International Journal of Health and Information System 1, no. 1 (May 18, 2023): 47–54. http://dx.doi.org/10.47134/ijhis.v1i1.6.
Abstract:
The Nutrition Care Center (NCC) is one of the teaching factories (TEFA) at Politeknik Negeri Jember that provides community nutrition services. Preliminary data collection found that the factory did not have complete health database of their staff so that nutritionists find it difficult to screen for non-communicable disease risk factors. In this study, the use of Electronic Health Record (EHR) equipped with Clinical Decision Support System (CDSS) was incorporated to record, retrieve, archive, and update patients and other medical records in the NCC. This system provides easier health record management for the nutritionist team at the NCC TEFA Politeknik Negeri Jember. Medical records help them conduct screening on non-communicable disease (NCD) risk factors and make clinical decision support for doctors/counselors which have missions to reduce NCD cases in the productive age. This study used a waterfall method model and collected data through a literature review, observation, and interviews. The results produced an application of a clinic database management in which all data and information could be integrated well to improve the quality of services and facilitate data storage and access. This study concludes that the EHRs generates quick and accurate information to support operations and decision-making in the NCC.
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Feletto, Eleonora, Evgeny V. Kovalevskiy, Sara J. Schonfeld, Monika Moissonnier, Ann Olsson, Sergey V. Kashanskiy, Evgenia Ostroumova, Igor V. Bukhtiyarov, Joachim Schüz, and Hans Kromhout. "Developing a company-specific job exposure matrix for the Asbest Chrysotile Cohort Study." Occupational and Environmental Medicine 79, no. 5 (October 8, 2021): 339–46. http://dx.doi.org/10.1136/oemed-2021-107438.
Abstract:
ObjectivesExposure assessment for retrospective industrial cohorts are often hampered by limited availability of historical measurements. This study describes the development of company-specific job-exposure matrices (JEMs) based on measurements collected over five decades for a cohort study of 35 837 workers (Asbest Chrysotile Cohort Study) in the Russian Federation to estimate their cumulative exposure to chrysotile containing dust and fibres.MethodsAlmost 100 000 recorded stationary dust measurements were available from 1951-2001 (factories) and 1964–2001 (mine). Linear mixed models were used to extrapolate for years where measurements were not available or missing. Fibre concentrations were estimated using conversion factors based on side-by-side comparisons. Dust and fibre JEMs were developed and exposures were allocated by linking them to individual workers’ detailed occupational histories.ResultsThe cohort covered a total of 515 355 employment-years from 1930 to 2010. Of these individuals, 15% worked in jobs not considered professionally exposed to chrysotile. The median cumulative dust exposure was 26 mg/m3 years for the entire cohort and 37.2 mg/m3 years for those professionally exposed. Median cumulative fibre exposure was 16.4 fibre/cm3 years for the entire cohort and 23.4 fibre/cm3 years for those professionally exposed. Cumulative exposure was highly dependent on birth cohort and gender. Of those professionally exposed, women had higher cumulative exposures than men as they were more often employed in factories with higher exposure concentrations rather than in the mine.ConclusionsUnique company-specific JEMs were derived using a rich measurement database that overlapped with most employment-years of cohort members and will enable estimation of quantitative exposure–response.