Search results for: library automation

Authors: Tim Giesen, Raphael Adamietz, Pablo Mayer, Philipp Stiefel, Patrick Alle, Dirk Schlenker

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The competitiveness and success of new electrical energy storages such as battery cells are significantly dependent on a short time-to-market. Producers who decide to supply new battery cells to the market need to be easily adaptable in manufacturing with respect to the early customers’ needs in terms of cell size, materials, delivery time and quantity. In the initial state, the required output rates do not yet allow the producers to have a fully automated manufacturing line nor to supply handmade battery cells. Yet there was no solution for manufacturing battery cells in low to medium volumes in a reproducible way. Thus, in terms of cell format and output quantity, a concept for the flexible assembly of battery cells was developed by the Fraunhofer-Institute for Manufacturing Engineering and Automation. Based on clustered processes, the modular system platform can be modified, enlarged or retrofitted in a short time frame according to the ordered product. The paper shows the analysis of the production steps from a conventional battery cell assembly line. Process solutions were found by using I/O-analysis, functional structures, and morphological boxes. The identified elementary functions were subsequently clustered by functional coherences for automation solutions and thus the single process cluster was generated. The result presented in this paper enables to manufacture different cell products on the same production system using seven process clusters. The paper shows the solution for a batch-wise flexible battery cell production using advanced process control. Further, the performed tests and benefits by using the process clusters as cyber-physical systems for an integrated production and value chain are discussed. The solution lowers the hurdles for SMEs to launch innovative cell products on the global market.

Keywords: automation, battery production, carrier, advanced process control, cyber-physical system

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Authors: Olga Kononova, Sergey Lyapin

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Global information society requirements are transparency and reliability of data, as well as ability to manage information resources independently; particularly to search, to analyze, to evaluate information, thereby obtaining new expertise. Moreover, it is satisfying the society information needs that increases the efficiency of the enterprise management and public administration. The study of structurally organized thematic and semantic contexts of different types, automatically extracted from unstructured data, is one of the important tasks for the application of information technologies in education, science, culture, governance and business. The objectives of this study are the contextual knowledge typologization, selection or creation of effective tools for extracting and analyzing contextual knowledge. Explication of various kinds and forms of the contextual knowledge involves the development and use full-text search information systems. For the implementation purposes, the authors use an e-library 'Humanitariana' services such as the contextual search, different types of queries (paragraph-oriented query, frequency-ranked query), automatic extraction of knowledge from the scientific texts. The multifunctional e-library «Humanitariana» is realized in the Internet-architecture in WWS-configuration (Web-browser / Web-server / SQL-server). Advantage of use 'Humanitariana' is in the possibility of combining the resources of several organizations. Scholars and research groups may work in a local network mode and in distributed IT environments with ability to appeal to resources of any participating organizations servers. Paper discusses some specific cases of the contextual knowledge explication with the use of the e-library services and focuses on possibilities of new types of the contextual knowledge. Experimental research base are science texts about 'e-government' and 'computer games'. An analysis of the subject-themed texts trends allowed to propose the content analysis methodology, that combines a full-text search with automatic construction of 'terminogramma' and expert analysis of the selected contexts. 'Terminogramma' is made out as a table that contains a column with a frequency-ranked list of words (nouns), as well as columns with an indication of the absolute frequency (number) and the relative frequency of occurrence of the word (in %% ppm). The analysis of 'e-government' materials showed, that the state takes a dominant position in the processes of the electronic interaction between the authorities and society in modern Russia. The media credited the main role in these processes to the government, which provided public services through specialized portals. Factor analysis revealed two factors statistically describing the used terms: human interaction (the user) and the state (government, processes organizer); interaction management (public officer, processes performer) and technology (infrastructure). Isolation of these factors will lead to changes in the model of electronic interaction between government and society. In this study, the dominant social problems and the prevalence of different categories of subjects of computer gaming in science papers from 2005 to 2015 were identified. Therefore, there is an evident identification of several types of contextual knowledge: micro context; macro context; dynamic context; thematic collection of queries (interactive contextual knowledge expanding a composition of e-library information resources); multimodal context (functional integration of iconographic and full-text resources through hybrid quasi-semantic algorithm of search). Further studies can be pursued both in terms of expanding the resource base on which they are held, and in terms of the development of appropriate tools.

Keywords: contextual knowledge, contextual search, e-library services, frequency-ranked query, paragraph-oriented query, technologies of the contextual knowledge extraction

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Authors: S. Cowley, M. Lawrance, D. Bick, R. McCord

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Technology that automates manual handling (musculoskeletal disorder or MSD) risk assessments is increasingly available to ergonomists, engineers, generalist health and safety practitioners alike. The risk assessment process is generally based on the use of wearable motion sensors that capture information about worker movements for real-time or for posthoc analysis. Traditionally, MSD risk assessment is undertaken with the assistance of a checklist such as that from the SafeWork Australia code of practice, the expert assessor observing the task and ideally engaging with the worker in a discussion about the detail. Automation enables the non-expert to complete assessments and does not always require the assessor to be there. This clearly has cost and time benefits for the practitioner but is it an improvement on the assessment by the human. Human risk assessments draw on the knowledge and expertise of the assessor but, like all risk assessments, are highly subjective. The complexity of the checklists and models used in the process can be off-putting and sometimes will lead to the assessment becoming the focus and the end rather than a means to an end; the focus on risk control is lost. Automated risk assessment handles the complexity of the assessment for the assessor and delivers a simple risk score that enables decision-making regarding risk control. Being machine-based, they are objective and will deliver the same each time they assess an identical task. However, the WHS professional needs to know that this emergent technology asks the right questions and delivers the right answers. Whether it improves the risk assessment process and results or simply distances the professional from the task and the worker. They need clarity as to whether automation of manual task risk analysis and reporting leads to risk control or to a focus on the worker. Critically, they need evidence as to whether automation in this area of hazard management leads to better risk control or just a bigger collection of assessments. Practitioner experienced determinants of this automated manual task risk analysis and reporting being a benefit or distraction will address an understanding of emergent risk assessment technology, its use and things to consider when making decisions about adopting and applying these technologies.

Keywords: automated, manual-handling, risk-assessment, machine-based

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Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

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Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

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Authors: Konstantinos Pikos, Dimitrios Kaimaris

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Although designing building blocks is a procedure used by many planners around the world, there isn’t an automated tool that will help planners and designers achieve their goals with lesser effort. The difficulty of the subject lies in the repeating process of manually drawing lines, while not only it is mandatory to maintain the desirable offset but to also achieve a lesser impact to the existing building stock. In this paper, using Geographical Information Systems (GIS) and the Python programming language, an automated tool integrated into ArcGIS PRO, is being presented. Despite its simplistic enviroment and the lack of specialized building legislation due to the complex state of the field, a planner who is aware of such technical information can use the tool to draw an initial approach of the final building blocks in an area with pre-existing buildings in an attempt to organize the usually sprawling suburbs of a city or any continuously developing area. The tool uses ESRI’s ArcPy library to handle the spatial data, while interactions with the user is made throught Tkinter. The main process consists of a modification of building edgescoordinates, using NumPy library, in an effort to draw the line of best fit, so the user can get the optimal results per block’s side. Finally, after the tool runs successfully, a table of primary planning information is shown, such as the area of the building block and its coverage rate. Regardless of the primary stage of the tool’s development, it is a solid base where potential planners with programming skills could invest, so they can make the tool adapt to their individual needs. An example of the entire procedure in a test area is provided, highlighting both the strengths and weaknesses of the final results.

Keywords: arcPy, GIS, python, building blocks

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Authors: Yohannes Haile, Dipo Onipede, Jr., Omar Ashour

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The main thrust of our research is to determine Industry 4.0 readiness of small and mid-size manufacturing companies in our region and assist them to implement Cyber Physical Production System (CPPS) capabilities. Adopting CPPS capabilities will help organizations realize improved quality, order delivery, throughput, new value creation, and reduced idle time of machines and work centers of their manufacturing operations. The key metrics for the assessment include the level of intelligence, internal and external connections, responsiveness to internal and external environmental changes, capabilities for customization of products with reference to cost, level of additive manufacturing, automation, and robotics integration, and capabilities to manufacture hybrid products in the near term, where near term is defined as 0 to 18 months. In our initial evaluation of several manufacturing firms which are profitable and successful in what they do, we found low level of Physical-Digital-Physical (PDP) loop in their manufacturing operations, whereas 100% of the firms included in this research have specialized manufacturing core competencies that have differentiated them from their competitors. The level of automation and robotics integration is low to medium range, where low is defined as less than 30%, and medium is defined as 30 to 70% of manufacturing operation to include automation and robotics. However, there is a significant drive to include these capabilities at the present time. As it pertains to intelligence and connection of manufacturing systems, it is observed to be low with significant variance in tying manufacturing operations management to Enterprise Resource Planning (ERP). Furthermore, it is observed that the integration of additive manufacturing in general, 3D printing, in particular, to be low, but with significant upside of integrating it in their manufacturing operations in the near future. To hasten the readiness of the local and regional manufacturing companies to Industry 4.0 and transitions towards CPPS capabilities, our working group (ADMAR Working Group) in partnership with our university have been engaged with the local and regional manufacturing companies. The goal is to increase awareness, share know-how and capabilities, initiate joint projects, and investigate the possibility of establishing the Center for Cyber Physical Production Systems Innovation (C2P2SI). The center is intended to support the local and regional university-industry research of implementing intelligent factories, enhance new value creation through disruptive innovations, the development of hybrid and data enhanced products, and the creation of digital manufacturing enterprises. All these efforts will enhance local and regional economic development and educate students that have well developed knowledge and applications of cyber physical manufacturing systems and Industry 4.0.

Keywords: automation, cyber-physical production system, digital manufacturing enterprises, disruptive innovation, new value creation, physical-digital-physical loop

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Authors: M. Jaculine Mary

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Today electronic resources are considered as an integral part of information sources to impart efficient services to the people aspiring to acquire knowledge in different fields. E-resources are those resources which include documents in e-format that can be accessed via the Internet in a digital library environment. The present study focuses on accessibility and use of e-resources by faculty and research scholars of academic libraries of Coimbatore, TamilNadu, India. The main objectives are to identify their purpose of using e-resources, know the users’ Information and Communication Technology (ICT) skills, identify satisfaction level of availability of e-resources, use of different e-resources, overall user satisfaction of using e-resources, impact of e-resources on their research and problems faced by them in the access of e-resources. The research methodology adopted to collect data for this study includes analysis of survey reports carried out by distributing questionnaires to the users. The findings of the research are based on the study of responses received from questionnaires distributed to a sample population of 200 users. Among the 200 respondents, 55 percent of research students and 45 percent of faculty members were users of e-resources. It was found that a majority of the users agreed that relevant, updated information at a fast pace had influenced them to use e-resources. Most of the respondents were of the view that more numbers of computers in the library would facilitate quick learning. Academic libraries have to take steps to arrange various training and orientation programmes for research students and faculty members to use the availability of e-resources. This study helps the librarian in planning and development of e-resources to provide modern services to their users of libraries. The study recommends that measures should be taken to increase the accessibility level of e-resource services among the information seekers for increasing the best usage of available electronic resources in the academic libraries.

Keywords: academic libraries, accessibility, electronic resources, satisfaction level, survey

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Authors: Oubelkacem Yacine, El Bast Hassan, El Bakkali Abdelmajid, Lamhasni Taibi, Ettakni Mahmoud, Ait Lyazidi Saadia, Haddad Mustapha, Ben-Ncer Abdelouahed, El Ferrane Mohammed, Boufarra Abdelkrim

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The present work relates to an on-site and completely non-invasive investigation of one of the most famous west Mediterranean Torah Scroll housed at the National Library of the Kingdom of Morocco. The scroll is 26 m long and consists of 143 parchment sheets of 59 cm x 19 cm, exhibiting only black writings; it is of unknown age. The artifact has been restored by the curator staff of the library. The investigation exploring separately the parchment support and the writing black ink aims at: i) the examination of the parchment conservation/degradation state, ii) the identification of the black ink and iii) the identification of the parchment handcrafting materials. For this purpose, the analyses have been based on combining all of elemental XRF and structural Raman, ATR-FT Infrared Red and Fiber Optical Reflectance spectroscopies, in addition to chroma-metric and pH measurements. pH measurements showing values around 6.5 are in concordance with the absence of any visual corrosion related to the parchment acidity. However, on the basis of the relative intensities and frequency shift of amid I (AI) and amid II (AII) vibrational bands of the collagen, ATR-FTIR spectra revealed diffuse hydrolysis and gelatinization of the parchment writing support; diffuse and non-homogeny degradation by gelatinization has been also confirmed by the IG gelatinization index deduced from the NIR bands on the FOR spectra. This IG index, defined as the ratio I (6860 cm-1) / I (6685 cm-1), ranges in the interval 0.98 – 1 and highlights collagen degradation at the molecular level. Sequentially Shifted Excitation Raman measurements (SSERS) crossed to X-ray fluorescence (XRF) ones on the black writings revealed that the black ink used is an iron-copper gall one, while FOR spectra are typical of pure metal gall inks. These later reflectance measurements exclude, thus, any intentional addition of carbon black to the ink recipe. Moreover, no lead white had been used while pre-drawing the writing lines. On another side, ATR-FTIR measurements highlighted the presence of oxalates as ink degradation products. Considering the parchment handcrafting, the combination of XRF and ATR-FTIR measurements led to the assumption that this writing support had been prepared according to ancient Middle East practices; the parchment infrared fingerprint seems identical to that of the Dead Sea scroll. The present multi-technical analyses are the first ones performed on an ancient Judaic written parchment of Morocco; it is under furthering. The investigation will be extended to other parchments belonging to the Jewish Cultural Heritage Museum of Morocco in Casablanca.

Keywords: torah scroll, parchment, black ink, non-invasive analyses, XRF/ATR-FTIR/RAMAN/FORS

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Authors: Lars Rödel, Jonas Krebs, Gregor Müller

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The growing price pressure due to the increasing number of global suppliers, the growing individualization of products and ever-shorter delivery times are upcoming challenges in the industry. In this context, Mass Personalization stands for the individualized production of customer products in batch size 1 at the price of standardized products. The possibilities of digitalization and automation of technical order processing open up the opportunity for companies to significantly reduce their cost of complexity and lead times and thus enhance their competitiveness. Many companies already use a range of CAx tools and configuration solutions today. Often, the expert knowledge of employees is hidden in "knowledge silos" and is rarely networked across processes. DesignChain describes the automated digital process from the recording of individual customer requirements, through design and technical preparation, to production. Configurators offer the possibility of mapping variant-rich products within the Design Chain. This transformation of customer requirements into product features makes it possible to generate even complex CAD models, such as those for large-scale plants, on a rule-based basis. With the aid of an automated CAx chain, production-relevant documents are thus transferred digitally to production. This process, which can be fully automated, allows variants to always be generated on the basis of current version statuses.

Keywords: automation, design, CAD, CAx

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Authors: Thinh Huu Nguyen, Shahab Sharfaei, Jindřich Soukup

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In the pursuit of reducing production costs, offshoring has been a major trend throughout global value chains for many decades. However, with the rise of advanced technologies, new opportunities to automate their production are changing the motivation of multinational firms to go offshore. Instead, many firms are working to relocate their offshored activities from developing economies back to their home countries. This phenomenon, known as reshoring, has recently garnered much attention as it becomes clear that automation in advanced countries might have major implications not only on their own economies but also through international trade on the economy of low-income countries, including their labor market outcomes and their comparative advantages. Thus, while using robots to substitute human labor may lower the relative costs of producing at home, it has the potential to decrease employment and demand for exports from developing economies through reshoring. In this paper, we investigate the recent literature to provide a further understanding of the relationships between robotization and the reshoring of production. Moreover, we analyze the impact of robot adoption on international trade in both developed and emerging markets. Finally, we identify the research gaps and provide avenues for future research in international economics. This study is a part of the project funded by the Internal Grant Agency (IGA) of the Faculty of Business Administration, Prague University of Economics and Business.

Keywords: automation, robotization, reshoring, international trade

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Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

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Authors: J. P. Reges, L. C. S. Mazza, E. J. Braga, J. A. Bessa, A. R. Alexandria

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This paper proposes the development of control and automation of irrigation system located sunflower harvest in the Teaching Unit, Research and Extension (UEPE), the Apodi Plateau in Limoeiro do Norte. The sunflower extraction, which in turn serves to get the produced oil from its seeds, animal feed, and is widely used in human food. Its nutritional potential is quite high what makes of foods produced from vegetal, very rich and healthy. The focus of research is to make the autonomous irrigation system sunflower crop from programmable logic control energized with alternative energy sources, solar photovoltaics. The application of automated irrigation system becomes interesting when it provides convenience and implements new forms of managements of the implementation of irrigated cropping systems. The intended use of automated addition to irrigation quality and consequently brings enormous improvement for production of small samples. Addition to applying the necessary and sufficient features of water management in irrigation systems, the system (PLC + actuators + Renewable Energy) will enable to manage the quantitative water required for each crop, and at the same time, insert the use of sources alternative energy. The entry of the automated collection will bring a new format, and in previous years, used the process of irrigation water wastage base and being the whole manual irrigation process.

Keywords: automation, control, sunflower, irrigation, programming, renewable energy

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Authors: Ibrahim Baba

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The work examines the nature and causes of differential politics in Africa with particular reference to the sub-Saharan region of the continent. It also among other objectives provides alternative panacea to gender discrimination in African politics and offers solutions on how to promote political inclusion of all citizens in respect of gender differences in Africa. The work is conducted using library base documentation analysis.

Keywords: gender, political, participation, differential politics, sub-Saharan Africa

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Authors: Meimei Shi

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Objectives: The identification of endangered species, especially simultaneous detection of multiple species in complex samples, plays a critical role in alleged wildlife crime incidents and prevents illegal trade. This study was to develop a multi-locus DNA metabarcoding method for endangered animal species identification. Methods: Several pairs of universal primers were designed according to the mitochondria conserved gene regions. Experimental mixtures were artificially prepared by mixing well-defined species, including endangered species, e.g., forest musk, bear, tiger, pangolin, and sika deer. The artificial samples were prepared with 1-16 well-characterized species at 1% to 100% DNA concentrations. After multiplex-PCR amplification and parameter modification, the amplified products were analyzed by capillary electrophoresis and used for NGS library preparation. The DNA metabarcoding was carried out based on Illumina MiSeq amplicon sequencing. The data was processed with quality trimming, reads filtering, and OTU clustering; representative sequences were blasted using BLASTn. Results: According to the parameter modification and multiplex-PCR amplification results, five primer sets targeting COI, Cytb, 12S, and 16S, respectively, were selected as the NGS library amplification primer panel. High-throughput sequencing data analysis showed that the established multi-locus DNA metabarcoding method was sensitive and could accurately identify all species in artificial mixtures, including endangered animal species Moschus berezovskii, Ursus thibetanus, Panthera tigris, Manis pentadactyla, Cervus nippon at 1% (DNA concentration). In conclusion, the established species identification method provides technical support for customs and forensic scientists to prevent the illegal trade of endangered animals and their products.

Keywords: DNA metabarcoding, endangered animal species, mitochondria nucleic acid, multi-locus

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Authors: Serzhan Ashirov, Dana Nour, Rafat Rob, Khaled Alotaibi

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There has been a fast growth in the introduction and use of communications, information, monitoring, and sensing technologies. The new technologies are making their way to the Industrial Control Systems as embedded in products, software applications, IT services, or commissioned to enable integration and automation of increasingly global supply chains. As a result, the lines that separated the physical, digital, and cyber world have diminished due to the vast implementation of the new, disruptive digital technologies. The variety and increased use of these technologies introduce many cybersecurity risks affecting cyber-resilience of the supply chain, both in terms of the product or service delivered to a customer and members of the supply chain operation. US department of energy considers supply chain in the IR4 space to be the weakest link in cybersecurity. The IR4 identified the digitization of the field devices, followed by digitalization that eventually moved through the digital transformation space with little care for the new introduced cybersecurity risks. This paper will examine the best methodologies for securing the electrical substations from cybersecurity attacks due to supply chain risks, and due to digitization effort. SCADA systems are the most vulnerable part of the power system infrastructure due to digitization and due to the weakness and vulnerabilities in the supply chain security. The paper will discuss in details how create a secure supply chain methodology, secure substations, and mitigate the risks due to digitization

Keywords: cybersecurity, supply chain methodology, secure substation, digitization

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Authors: W. S. Thulasitha, N. Umasuthan, G. I. Godahewa, Jehee Lee

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In fish, innate immune defense is the first immune response against microbial pathogens which consists of several antimicrobial components. Galectins are one of the carbohydrate binding lectins that have the ability to identify pathogen by recognition of pathogen associated molecular patterns. Galectins play a vital role in the regulation of innate and adaptive immune responses. Rock bream Oplegnathus fasciatus is one of the most important cultured species in Korea and Japan. Considering the losses due to microbial pathogens, present study was carried out to understand the molecular and functional characteristics of a galectin in normal and pathogenic conditions, which could help to establish an understanding about immunological components of rock bream. Complete cDNA of rock bream galectin like protein B (rbGal like B) was identified from the cDNA library, and the in silico analysis was carried out using bioinformatic tools. Genomic structure was derived from the BAC library by sequencing a specific clone and using Spidey. Full length of rbGal like B (contig14775) cDNA containing 517 nucleotides was identified from the cDNA library which comprised of 435 bp in the open reading frame encoding a deduced protein composed of 145 amino acids. The molecular mass of putative protein was predicted as 16.14 kDa with an isoelectric point of 8.55. A characteristic conserved galactose binding domain was located from 12 to 145 amino acids. Genomic structure of rbGal like B consisted of 4 exons and 3 introns. Moreover, pairwise alignment showed that rock bream rbGal like B shares highest similarity (95.9 %) and identity (91 %) with Takifugu rubripes galectin related protein B like and lowest similarity (55.5 %) and identity (32.4 %) with Homo sapiens. Multiple sequence alignment demonstrated that the galectin related protein B was conserved among vertebrates. A phylogenetic analysis revealed that rbGal like B protein clustered together with other fish homologs in fish clade. It showed closer evolutionary link with Takifugu rubripes. Tissue distribution and expression patterns of rbGal like B upon immune challenges were performed using qRT-PCR assays. Among all tested tissues, level of rbGal like B expression was significantly high in gill tissue followed by kidney, intestine, heart and spleen. Upon immune challenges, it showed an up-regulated pattern of expression with Edwardsiella tarda, rock bream irido virus and poly I:C up to 6 h post injection and up to 24 h with LPS. However, In the presence of Streptococcus iniae rbGal like B showed an up and down pattern of expression with the peak at 6 - 12 h. Results from the present study revealed the phylogenetic position and role of rbGal like B in response to microbial infection in rock bream.

Keywords: galectin like protein B, immune response, Oplegnathus fasciatus, molecular characterization

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode, a short mitochondrial DNA fragment, made up of three subunits; a phosphate group, sugar and nucleic bases (A, T, C, and G). They provide good sources of information needed to classify living species. Such intuition has been confirmed by many experimental results. Species classification with DNA Barcode sequences has been studied by several researchers. The classification problem assigns unknown species to known ones by analyzing their Barcode. This task has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. To make this type of analysis feasible, heuristics, like progressive alignment, have been developed. Another tool for similarity search against a database of sequences is BLAST, which outputs shorter regions of high similarity between a query sequence and matched sequences in the database. However, all these methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. This method permits to avoid the complex problem of form and structure in different classes of organisms. On empirical data and their classification performances are compared with other methods. Our system consists of three phases. The first is called transformation, which is composed of three steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. The second is called approximation, which is empowered by the use of Multi Llibrary Wavelet Neural Networks (MLWNN).The third is called the classification of DNA Barcodes, which is realized by applying the algorithm of hierarchical classification.

Keywords: DNA barcode, electron-ion interaction pseudopotential, Multi Library Wavelet Neural Networks (MLWNN)

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Authors: Nemanja Kajtez, Yue Zhan, Basel Halak

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The significant rise in the cost of manufacturing of nanoscale integrated circuits (IC) has led the majority of IC design companies to outsource the fabrication of their products to other companies, often located in different countries. This multinational nature of the hardware supply chain has led to a host of security threats, including IP piracy, IC overproduction, and Trojan insertion. To combat that, researchers have proposed logic locking techniques to protect the intellectual properties of the design and increase the difficulty of malicious modification of its functionality. However, the adoption of logic locking approaches is rather slow due to the lack of the integration with IC production process and the lack of efficacy of existing algorithms. This work automates the logic locking process by developing software using Python that performs the locking on a gate-level netlist and can be integrated with the existing digital synthesis tools. Analysis of the latest logic locking algorithms has demonstrated that the SFLL-HD algorithm is one of the most secure and versatile in trading-off levels of protection against different types of attacks and was thus selected for implementation. The presented tool can also be expanded to incorporate the latest locking mechanisms to keep up with the fast-paced development in this field. The paper also presents a case study to demonstrate the functionality of the tool and how it could be used to explore the design space and compare different locking solutions. The source code of this tool is available freely from (https://www.researchgate.net/publication/353195333_Source_Code_for_The_Lockit_Tool).

Keywords: design automation, hardware security, IP piracy, logic locking

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Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

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Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

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Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

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Authors: June-Jei Kuo, Yi-Chuan Hsieh

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Because of the rapid growth of information technology, more and more libraries introduce the new information retrieval systems to enhance the users’ experience, improve the retrieval efficiency, and increase the applicability of the library resources. Nevertheless, few of them are discussed the usability from the users’ aspect. The aims of this study are to understand that the scenario of the information retrieval system utilization, and to know why users are willing to continuously use the web-scale discovery system to improve the web-scale discovery system and promote their use of university libraries. Besides of questionnaires, observations and interviews, this study employs both Information System Success Model introduced by DeLone and McLean in 2003 and the flow theory to evaluate the system quality, information quality, service quality, use, user satisfaction, flow, and continuing to use web-scale discovery system of students from National Chung Hsing University. Then, the results are analyzed through descriptive statistics and structural equation modeling using AMOS. The results reveal that in web-scale discovery system, the user’s evaluation of system quality, information quality, and service quality is positively related to the use and satisfaction; however, the service quality only affects user satisfaction. User satisfaction and the flow show a significant impact on continuing to use. Moreover, user satisfaction has a significant impact on user flow. According to the results of this study, to maintain the stability of the information retrieval system, to improve the information content quality, and to enhance the relationship between subject librarians and students are recommended for the academic libraries. Meanwhile, to improve the system user interface, to minimize layer from system-level, to strengthen the data accuracy and relevance, to modify the sorting criteria of the data, and to support the auto-correct function are required for system provider. Finally, to establish better communication with librariana commended for all users.

Keywords: web-scale discovery system, discovery system, information system success model, flow theory, academic library

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Authors: Yogesh C. Sharma, A. Seetharaman

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The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision-making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation, and workplace motivation. Hybrid human-AI systems require the development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.

Keywords: employee decision making, artificial intelligence (AI) environment, human trust, technology innovation, psychological safety

Procedia PDF Downloads 79

Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Emmanuel D. Buedi, K. O. Boateng, Griffith S. Klogo

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Electrical distribution networks are prone to power quality disturbances originating from the complexity of the distribution network, mode of distribution (overhead or underground) and types of loads used by customers. Data on the types of disturbances present and frequency of occurrence is needed for economic evaluation and hence finding solution to the problem. Utility companies have resorted to using secondary power quality devices such as smart meters to help gather the required data. Even though this approach is easier to adopt, data gathered from these devices may not serve the required purpose, since the installation of these devices in the electrical network usually does not conform to available PQM placement methods. This paper presents a design of a PQM that is capable of integrating into an existing DAS infrastructure to take advantage of available placement methodologies. The monitoring component of the design is implemented and installed to monitor an existing LV network. Data from the monitor is analyzed and presented. A portion of the LV network of the Electricity Company of Ghana is modeled in MATLAB-Simulink and analyzed under various earth fault conditions. The results presented show the ability of the PQM to detect and analyze PQ disturbance such as voltage sag and overvoltage. By adopting a placement methodology and installing these nodes, utilities are assured of accurate and reliable information with respect to the quality of power delivered to consumers.

Keywords: power quality, remote monitoring, distributed automation system, economic evaluation, LV network

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Authors: Emna Hlel, Salma Jamousi, Abdelmajid Ben Hamadou

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Every model for knowledge representation to model real-world applications must be able to cope with the effects of uncertain phenomena. One of main defects of classical ontology is its inability to represent and reason with uncertainty. To remedy this defect, we try to propose a method to construct probabilistic ontology for integrating uncertain information in an ontology modeling a set of basic publications DBLP (Digital Bibliography & Library Project) using a probabilistic model.

Keywords: classical ontology, probabilistic ontology, uncertainty, Bayesian network

Procedia PDF Downloads 319

Authors: Ozlem Oral, Seval Kilic, Ozlem Yedier, Serap Dokmeci, Devrim Gozuacik

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Autophagy is a degradation pathway, activating under stress conditions. It digests macromolecules, such as abnormal proteins and long-lived organelles by engulfing them and by subsequent delivery of the cargo to lysosomes. The members of the phospholipid-dependent serine/threonine kinases, involved in many signaling pathways, which are necessary for the regulation of cellular metabolic activation. Previous studies implicate that, serine/threonine kinases have crucial roles in the mechanism of many diseases depend on the activated and/or inactivated signaling pathway. Data indicates, the signaling pathways activated by serine/threonine kinases are also involved in activation of autophagy mechanism. However, the information about the effect of serine/threonine kinases on autophagy mechanism and the roles of these effects in disease formation is limited. In this study, we investigated the effect of activated serine/threonine kinases on autophagic pathway. We performed a commonly used autophagy technique, GFP-LC3 dot formation and by using microscopy analyses, we evaluated promotion and/or inhibition of autophagy in serine/threonine kinase-overexpressed fibroblasts as well as cancer cells. In addition, we carried out confocal microscopy analyses and examined autophagic flux by utilizing the differential pH sensitivities of RFP and GFP in mRFP-GFP-LC3 probe. Based on the shRNA-library based screening, we identified autophagy-related proteins affected by serine/threonine kinases. We further studied the involvement of serine/threonine kinases on the molecular mechanism of newly identified autophagy proteins and found that, autophagic pathway is indirectly controlled by serine/threonine kinases via specific autophagic proteins. Our data indicate the molecular connection between two critical cellular mechanisms, which have important roles in the formation of many disease pathologies, particularly cancer. This project is supported by TUBITAK-1001-Scientific and Technological Research Projects Funding Program, Project No: 114Z836.

Keywords: autophagy, GFP-LC3 dot formation assay, serine/threonine kinases, shRNA-library screening

Procedia PDF Downloads 267

Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Lokesh Soni, Sushanta Kumar Sethi, Gaurav Manik

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This work attempts to use molecular simulations to create equilibrated structures of a range of commercially used polymers. Generated equilibrated structures for polyvinyl acetate (isotactic), polyvinyl alcohol (atactic), polystyrene, polyethylene, polyamide 66, poly dimethyl siloxane, poly carbonate, poly ethylene oxide, poly amide 12, natural rubber, poly urethane, and polycarbonate (bisphenol-A) and poly ethylene terephthalate are employed to estimate the correct chain length that will correctly predict the chain parameters and properties. Further, the equilibrated structures are used to predict some properties like density, solubility parameter, cohesive energy density, surface energy, and Flory-Huggins interaction parameter. The simulated densities for polyvinyl acetate, polyvinyl alcohol, polystyrene, polypropylene, and polycarbonate are 1.15 g/cm3, 1.125 g/cm3, 1.02 g/cm3, 0.84 g/cm3 and 1.223 g/cm3 respectively are found to be in good agreement with the available literature estimates. However, the critical repeating units or the degree of polymerization after which the solubility parameter showed saturation were 15, 20, 25, 10 and 20 respectively. This also indicates that such properties that dictate the miscibility of two or more polymers in their blends are strongly dependent on the chosen polymer or its characteristic properties. An attempt has been made to correlate such properties with polymer properties like Kuhn length, free volume and the energy term which plays a vital role in predicting the mentioned properties. These results help us to screen and propose a useful library which may be used by the research groups in estimating the polymer properties using the molecular simulations of chains with the predicted critical lengths. The library shall help to obviate the need for researchers to spend efforts in finding the critical chain length needed for simulating the mentioned polymer properties.

Keywords: Kuhn length, Flory Huggins interaction parameter, cohesive energy density, free volume

Procedia PDF Downloads 171

Authors: Kelvin Lo

Abstract:

Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

Procedia PDF Downloads 23