Search results for: labeling automation

Authors: Julian Wise

Abstract:

Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

Procedia PDF Downloads 86

Authors: Akaki Qatamidze

Abstract:

Implementation of the project will be a step forward in terms of reliability in Georgia and the improvement of the construction and the development of construction. Completion of the project is expected to result in a complete knowledge, which is expressed in concrete and stone structures of assessing the technical condition of the processing. This method is based on a detailed examination of the structure, in order to establish the injuries and the elimination of the possibility of changing the structural scheme of the new requirements and architectural preservationists. Reinforced concrete and stone structures research project carried out in a systematic analysis of the important approach is to optimize the process of research and development of new knowledge in the neighboring areas. In addition, the problem of physical and mathematical models of rational consent, the main pillar of the physical (in-situ) data and mathematical calculation models and physical experiments are used only for the calculation model specification and verification. Reinforced concrete and stone construction defects and failures the causes of the proposed research to enhance the effectiveness of their maximum automation capabilities and expenditure of resources to reduce the recommended system analysis of the methodological concept-based approach, as modern science and technology major particularity of one, it will allow all family structures to be identified for the same work stages and procedures, which makes it possible to exclude subjectivity and addresses the problem of the optimal direction. It discussed the methodology of the project and to establish a major step forward in the construction trades and practical assistance to engineers, supervisors, and technical experts in the construction of the settlement of the problem.

Keywords: building, reinforced concrete, expertise, stone structures

Procedia PDF Downloads 312

Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

Abstract:

The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

Procedia PDF Downloads 76

Authors: Enido Fabiano de Ramos, Ieda Kanashiro Makiya, Francisco I. Giocondo Cesar

Abstract:

This study investigates the application of Digital Twins (DT) in Smart Hospital Environments (SHE), through a bibliometric study and literature review, including comparison with the principles of Industry 4.0. It aims to analyze the current state of the implementation of digital twins in clinical and non-clinical operations in healthcare settings, identifying trends and challenges, comparing these practices with Industry 4.0 concepts and technologies, in order to present a basic framework including stages and maturity levels. The bibliometric methodology will allow mapping the existing scientific production on the theme, while the literature review will synthesize and critically analyze the relevant studies, highlighting pertinent methodologies and results, additionally the comparison with Industry 4.0 will provide insights on how the principles of automation, interconnectivity and digitalization can be applied in healthcare environments/operations, aiming at improvements in operational efficiency and quality of care. The results of this study will contribute to a deeper understanding of the potential of Digital Twins in Smart Hospitals, in addition to the future potential from the effective integration of Industry 4.0 concepts in this specific environment, presented through the practical framework, after all, the urgent need for changes addressed in this article is undeniable, as well as all their value contribution to human sustainability, designed in SDG3 – Health and well-being: ensuring that all citizens have a healthy life and well-being, at all ages and in all situations. We know that the validity of these relationships will be constantly discussed, and technology can always change the rules of the game.

Keywords: digital twin, smart hospital, healthcare operations, industry 4.0, SDG3, technology

Procedia PDF Downloads 26

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 112

Authors: Ruvaitha Banu, Amaladhithyan Krishnamoorthy

Abstract:

IoT networks today solve various consumer problems, from home automation systems to aiding in driving autonomous vehicles with the exploration of multiple devices. For example, in an autonomous vehicle environment, multiple sensors are available on roads to monitor weather and road conditions and interact with each other to aid the vehicle in reaching its destination safely and timely. IoT systems are predominantly dependent on the cloud environment for data storage, and computing needs that result in latency problems. With the advent of Fog networks, some of this storage and computing is pushed to the edge/fog nodes, saving the network bandwidth and reducing the latency proportionally. Managing the data stored in these fog nodes becomes crucial as it might also store sensitive information required for a certain application. Data management in fog nodes is strenuous because Fog networks are dynamic in terms of their availability and hardware capability. It becomes more challenging when the nodes in the network also live a short span, detaching and joining frequently. When an end-user or Fog Node wants to access, read, or write data stored in another Fog Node, then a new protocol becomes necessary to access/manage the data stored in the fog devices as a conventional static way of managing the data doesn’t work in Fog Networks. The proposed solution discusses a protocol that acts by defining sensitivity levels for the data being written and read. Additionally, a distinct data distribution and replication model among the Fog nodes is established to decentralize the access mechanism. In this paper, the proposed model implements stewardship towards the data stored in the Fog node using the application of Reinforcement Learning so that access to the data is determined dynamically based on the requests.

Keywords: IoT, fog networks, data stewardship, dynamic access policy

Procedia PDF Downloads 31

Authors: Sanchita Abrol, Kunal Rana, Ankit Dhir, S. K. Gupta

Abstract:

According to N.R.E.L.’s findings, 700 crore gallons of petrol is used annually to run the air conditioners of passenger vehicles (nearly 6% of total fuel consumption in the USA). Beyond fuel use, the Environmental Protection Agency reported that refrigerant leaks from auto air conditioning units add an additional 5 crore metric tons of carbon emissions to the atmosphere each year. The objective of our project is to deal with this vital issue by carefully modifying the interiors of a car thereby increasing its mileage and the efficiency of its engine. This would consequently result in a decrease in tail emission and generated pollution along with improved car performance. An automatic mechanism, deployed between the front and the rear seats, consisting of transparent thermal insulating sheet/curtain, would roll down as per the requirement of the driver in order to optimize the volume for effective air conditioning, when travelling alone or with a person. The reduction in effective volume will yield favourable results. Even on a mild sunny day, the temperature inside a parked car can quickly spike to life-threatening levels. For a stationary parked car, insulation would be provided beneath its metal body so as to reduce the rate of heat transfer and increase the transmissivity. As a result, the car would not require a large amount of air conditioning for maintaining lower temperature, which would provide us similar benefits. Authors established the feasibility studies, system engineering and primarily theoretical and experimental results confirming the idea and motivation to fabricate and test the actual product.

Keywords: automation, car, cooling insulating curtains, heat optimization, insulation, reduction in tail emission, mileage

Procedia PDF Downloads 250

Authors: A. Bhatt, C. Bassi, H. Farragher, J. Musk

Abstract:

Background: All medicines placed on the EU market are legally required to be accompanied by labeling and package leaflet, which provide comprehensive information, enabling its safe and appropriate use. Mock-ups with results of assessments using a target patient group must be submitted for a marketing authorisation application. Consumers need confidence in non-prescription, OTC medicines in order to manage their minor ailments and umbrella brands assist purchasing decisions by assisting easy identification within a particular therapeutic area. A number of regulatory agencies have risk management tools and guidelines to assist in developing umbrella brands for OTC medicines, however assessment and decision making is subjective and inconsistent. This study presents an evaluation in the UK following the US FDA warning concerning methaemoglobinaemia following 21 reported cases (11 children under 2 years) caused by OTC oral analgesics containing benzocaine. METHODS: A standard face to face, 25 structured task based user interview testing methodology using a standard questionnaire and rating scale in consumers aged 15-91 years, was conducted independently between June and October 2015 in their homes. Whether individuals could discriminate between the labelling, safety information and warnings on cartons and PILs between 3 different OTC medicines packs with the same umbrella name was evaluated. Each pack was presented with differing information hierarchy using, different coloured cartons, containing the 3 different active ingredients, benzocaine (oromucosal spray) and two lozenges containing 2, 4, dichlorobenzyl alcohol, amylmetacresol and hexylresorcinol respectively (for the symptomatic relief of sore throat pain). The test was designed to determine whether warnings on the carton and leaflet were prominent, accessible to alert users that one product contained benzocaine, risk of methaemoglobinaemia, and refer to the leaflet for the signs of the condition and what to do should this occur. Results: Two consumers did not locate the warnings on the side of the pack, eventually found them on the back and two suggestions to further improve accessibility of the methaemoglobinaemia warning. Using a gold pack design for the oromucosal spray, all consumers could differentiate between the 3 drugs, minimum age particulars, pharmaceutical form and the risk factor methaemoglobinaemia. The warnings for benzocaine were deemed to be clear or very clear; appearance of the 3 packs were either very well differentiated or quite well differentiated. The PIL test passed on all criteria. All consumers could use the product correctly, identify risk factors ensuring the critical information necessary for the safe use was legible and easily accessible so that confusion and errors were minimised. Conclusion: Patients with known methaemoglobinaemia are likely to be vigilant in checking for benzocaine containing products, despite similar umbrella brand names across a range of active ingredients. Despite these findings, the package design and spray format were not deemed to be sufficient to mitigate potential safety risks associated with differences in target populations and contraindications when submitted to the Regulatory Agency. Although risk management tools are increasingly being used by agencies to assist in providing objective assurance of package safety, further transparency, reduction in subjectivity and proportionate risk should be demonstrated.

Keywords: labelling, OTC, risk, user testing

Procedia PDF Downloads 275

Authors: Mehrshad Khosraviani, Sepehr Najjarpour

Abstract:

Considering the usage of graph-based approaches in systems and synthetic biology, and the various types of ‎the graphs employed by them, a comprehensive graph library based ‎on the three-tier architecture (3TA) was previously introduced for full representation of the biological systems. Although proposing a 3TA-based graph library, three following reasons motivated us to redesign the graph ‎library based on the service-oriented architecture (SOA): (1) Maintaining the accuracy of the data related to an input graph (including its edges, its ‎vertices, its topology, etc.) without involving the end user:‎ Since, in the case of using 3TA, the library files are available to the end users, they may ‎be utilized incorrectly, and consequently, the invalid graph data will be provided to the ‎computer algorithms. However, considering the usage of the SOA, the operation of the ‎graph registration is specified as a service by encapsulation of the library files. In other words, overall control operations needed for registration of the valid data will be the ‎responsibility of the services. (2) Partitioning of the library product into some different parts: Considering 3TA, a whole library product was provided in general. While here, the product ‎can be divided into smaller ones, such as an AND/OR graph drawing service, and each ‎one can be provided individually. As a result, the end user will be able to select any ‎parts of the library product, instead of all features, to add it to a project. (3) Reduction of the complexities: While using 3TA, several other libraries must be needed to add for connecting to the ‎database, responsibility of the provision of the needed library resources in the SOA-‎based graph library is entrusted with the services by themselves. Therefore, the end user ‎who wants to use the graph library is not involved with its complexity. In the end, in order to ‎make ‎the library easier to control in the system, and to restrict the end user from accessing the files, ‎it was preferred to use the service-oriented ‎architecture ‎‎(SOA) over the three-tier architecture (3TA) and to redevelop the previously proposed graph library based on it‎.

Keywords: Bio-Design Automation, Biological System, Graph Library, Service-Oriented Architecture, Systems and Synthetic Biology

Procedia PDF Downloads 286

Authors: Edward Nartey

Abstract:

Although the boundaries of sustainable performance and growth in the field of service supply chains (SCs) have been broadened by scholars in recent years, research on the impact and promises of Industry 4.0 Destructive Technologies (IDTs) on sustainability performance under disruptive events is still scarce. To mitigate disruptions in the SC and improve efficiency by identifying areas for cost savings, organizations have resorted to investments in digitalization, automation, and control mechanisms in recent years. However, little is known about the sustainability implications for IDT adoption and controls in service SCs, especially during disruptive events. To investigate this paradox, survey data were sought from 223 public health managers across Ghana and analyzed via covariance-based structural equations modelling. The results showed that both formal and informal control have a positive and significant relationship with IDT adoption. In addition, formal control has a significant and positive relationship with environmental and economic sustainability but an insignificant relationship with social sustainability. Furthermore, informal control positively impacts economic performance but has an insignificant relationship with social and environmental sustainability. While the findings highlight the prevalence of the IDTs being initiated by Ghanaian public health institutions (PHIs), this study concludes that the installed control systems in these organizations are inadequate for promoting sustainable SC behaviors under destructive events. Thus, in crisis situations, PHIs need to redesign their control systems to facilitate IDT integration towards sustainability issues in SCs.

Keywords: industry 4.0 destructive technologies, formal control, informal control, sustainable supply chain performance, public health organizations

Procedia PDF Downloads 26

Authors: Joshua Loiselle

Abstract:

This paper discusses the challenges engineering teams face in conducting Failure Modes and Effects Analysis (FMEA) studies. This paper focuses on the specific topic of improving the efficiency and effectiveness of FMEA studies. Modern economic needs and increased business competition require engineers to constantly develop newer and better solutions within shorter timeframes and tighter margins. In addition, documentation requirements for meeting standards/regulatory compliance and customer needs are becoming increasingly complex and verbose. Managing open actions and continuous improvement activities across all projects, product variations, and processes in addition to daily engineering tasks is cumbersome, time consuming, and is susceptible to errors, omissions, and non-conformances. FMEA studies are proven methods for improving products and processes while subsequently reducing engineering workload and improving machine and resource availability through a pre-emptive, systematic approach of identifying, analyzing, and improving high-risk components. If implemented correctly, FMEA studies significantly reduce costs and improve productivity. However, the value of an effective FMEA is often shrouded by a lack of clarity and structure, misconceptions, and previous experiences and, as such, FMEA studies are frequently grouped with the other required information and documented retrospectively in preparation of customer requirements or audits. Performing studies in this way only adds cost to a project and perpetuates the misnomer that FMEA studies are not value-added activities. This paper discusses the benefits of effective FMEA studies, the challenges related to conducting FMEA studies, best practices for efficiently overcoming challenges via structure and automation, and the benefits of implementing those practices.

Keywords: FMEA, quality, APQP, PPAP

Procedia PDF Downloads 277

Authors: Andrew Couch, Nicholas Loyd, Nathan Tenhundfeld

Abstract:

The rapid emergence of technology observably induces disruptive effects that carry implications for internal organizational dynamics as well as external market opportunities, strategic pressures, and threats. An examination of the historical tendencies of technology innovation shows that the body of managerial knowledge for addressing such disruption is underdeveloped. Fundamentally speaking, the impacts of innovation are unique and situationally oriented. Hence, the appropriate managerial response becomes a complex function that depends on the nature of the emerging technology, the posturing of internal organizational dynamics, the rate of technological growth, and much more. This research considers a particular case of mismanagement, the BP Texas City Refinery explosion of 2005, that carries notable discrepancies on the basis of human factors principles. Moreover, this research considers the modern technological climate (shaped by Industry 4.0 technologies) and seeks to arrive at an appropriate conceptual lens by which human factors principles and Industry 4.0 may be favorably integrated. In this manner, the careful examination of these phenomena helps to better support the sustainment of human factors principles despite the disruptive impacts that are imparted by technological innovation. In essence, human factors considerations are assessed through the application of principles that stem from usability engineering, the Swiss Cheese Model of accident causation, human-automation interaction, signal detection theory, alarm design, and other factors. Notably, this stream of research supports a broader framework in seeking to guide organizations amid the uncertainties of Industry 4.0 to capture higher levels of adoption, implementation, and transparency.

Keywords: Industry 4.0, human factors engineering, management, case study

Procedia PDF Downloads 35

Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

Abstract:

The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

Procedia PDF Downloads 338

Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

Abstract:

Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

Procedia PDF Downloads 117

Authors: Nikolay P. Brayanov, Anna V. Stoynova

Abstract:

Model-based development approach is gaining more support and acceptance. Its higher abstraction level brings simplification of systems’ description that allows domain experts to do their best without particular knowledge in programming. The different levels of simulation support the rapid prototyping, verifying and validating the product even before it exists physically. Nowadays model-based approach is beneficial for modelling of complex embedded systems as well as a generation of code for many different hardware platforms. Moreover, it is possible to be applied in safety-relevant industries like automotive, which brings extra automation of the expensive device certification process and especially in the software qualification. Using it, some companies report about cost savings and quality improvements, but there are others claiming no major changes or even about cost increases. This publication demonstrates the level of maturity and autonomy of model-based approach for code generation. It is based on a real live automotive seat heater (ASH) module, developed using The Mathworks, Inc. tools. The model, created with Simulink, Stateflow and Matlab is used for automatic generation of C code with Embedded Coder. To prove the maturity of the process, Code generation advisor is used for automatic configuration. All additional configuration parameters are set to auto, when applicable, leaving the generation process to function autonomously. As a result of the investigation, the publication compares the quality of generated embedded code and a manually developed one. The measurements show that generally, the code generated by automatic approach is not worse than the manual one. A deeper analysis of the technical parameters enumerates the disadvantages, part of them identified as topics for our future work.

Keywords: embedded code generation, embedded C code quality, embedded systems, model-based development

Procedia PDF Downloads 219

Authors: Adrian Ionita, Ana-Maria Ghimes

Abstract:

The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

Procedia PDF Downloads 141

Authors: Pedro Ferreira, Alexandre Frugoli, Pedro Frugoli, Lucio Leonardo, Thais Cavalheri

Abstract:

The teaching of fluid mechanics in engineering courses is, in general, a source of great difficulties for learning. The possibility of the use of experiments with didactic wind tunnels can facilitate the education of future professionals. The objective of this proposal is the development of a low-cost aerodynamic balance to be used in a didactic wind tunnel. The set is comprised of an Arduino microcontroller, programmed by an open source software, linked to load cells built by students from another project. The didactic wind tunnel is 5,0m long and the test area is 90,0 cm x 90,0 cm x 150,0 cm. The Weq® electric motor, model W-22 of 9,2 HP, moves a fan with nine blades, each blade 32,0 cm long. The Weq® frequency inverter, model WEGCFW 08 (Vector Inverter) is responsible for wind speed control and also for the motor inversion of the rotational direction. A flat-convex profile prototype of airfoil was tested by measuring the drag and lift forces for certain attack angles; the air flux conditions remained constant, monitored by a Pitot tube connected to a EXTECH® Instruments digital pressure differential manometer Model HD755. The results indicate a good agreement with the theory. The choice of all of the components of this proposal resulted in a low-cost product providing a high level of specific knowledge of mechanics of fluids, which may be a good alternative to teaching in countries with scarce educational resources. The system also allows the expansion to measure other parameters like fluid velocity, temperature, pressure as well as the possibility of automation of other functions.

Keywords: aerodynamic balance, wind tunnel, strain gauge, load cell, Arduino, low-cost education

Procedia PDF Downloads 412

Authors: Sugandhi, Parteek Kumar, Sanmeet Kaur

Abstract:

Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.

Keywords: avatar, dictionary, HamNoSys, hearing impaired, Indian sign language (ISL), sign language

Procedia PDF Downloads 200

Authors: Tei Kim, Brooklynn McNeil, Kathryn Dunn, Douglas I. Walker

Abstract:

To better characterize the relationship between complex chemical exposures and disease, our laboratory uses an approach that combines low-cost, polydimethylsiloxane (silicone) wristband samplers that absorb many of the chemicals we are exposed to with untargeted high-resolution mass spectrometry (HRMS) to characterize 1000’s of chemicals at a time. In studies with human populations, these wristbands can provide an important measure of our environment: however, there is a need to use this approach in large cohorts to study exposures associated with the disease. To facilitate the use of silicone samplers in large scale population studies, the goal of this research project was to establish automated sample preparation methods that improve throughput, robustness, and scalability of analytical methods for silicone wristbands. Using the Opentron OT2 automated liquid platform, which provides a low-cost and opensource framework for automated pipetting, we created two separate workflows that translate the manual wristband preparation method to a fully automated protocol that requires minor intervention by the operator. These protocols include a sequence generation step, which defines the location of all plates and labware according to user-specified settings, and a transfer protocol that includes all necessary instrument parameters and instructions for automated solvent extraction of wristband samplers. These protocols were written in Python and uploaded to GitHub for use by others in the research community. Results from this project show it is possible to establish automated and open source methods for the preparation of silicone wristband samplers to support profiling of many environmental exposures. Ongoing studies include deployment in longitudinal cohort studies to investigate the relationship between personal chemical exposure and disease.

Keywords: bioinformatics, automation, opentrons, research

Procedia PDF Downloads 84

Authors: H. M. B. N Jayasinghe

Abstract:

The water is found almost everywhere on Earth. Water resources contain a lot of pollution. Some diseases can be spread through the water to the living beings. So to be clean water it should undergo a number of treatments necessary to make it drinkable. So it is must to have purification technology for the wastewater. So the waste water treatment plants act a major role in these issues. When considering the procedures taken after the water treatment process was always based on manual calculations and recordings. Water purification plants may interact with lots of manual processes. It means the process taking much time consuming. So the final evaluation and chemical, biological treatment process get delayed. So to prevent those types of drawbacks there are some computerized programmable calculation and analytical techniques going to be introduced to the laboratory staff. To solve this problem automated system will be a solution in which guarantees the rational selection. A decision support system is a way to model data and make quality decisions based upon it. It is widely used in the world for the various kind of process automation. Decision support systems that just collect data and organize it effectively are usually called passive models where they do not suggest a specific decision but only reveal information. This web base system is based on global positioning data adding facility with map location. Most worth feature is SMS and E-mail alert service to inform the appropriate person on a critical issue. The technological influence to the system is HTML, MySQL, PHP, and some other web developing technologies. Current issues in the computerized water chemistry analysis are not much deep in progress. For an example the swimming pool water quality calculator. The validity of the system has been verified by test running and comparison with an existing plant data. Automated system will make the life easier in productively and qualitatively.

Keywords: automated system, wastewater, purification technology, map location

Procedia PDF Downloads 225

Authors: Bruno R. A. Oliveira, Italo V. V. Braga, Jonas P. Reges, Luiz P. O. Santos, Sidney C. Duarte, Emilson R. R. Melo, Auzuir R. Alexandria

Abstract:

This project aims to building a controlled greenhouse, or for better understanding, a structure where one can maintain a given range of temperature values (°C) coming from radiation emitted by an incandescent light, as previously defined, characterizing as a kind of on-off control and a differential, which is the plotting of temperature versus time graphs assisted by MATLAB software via serial communication. That way it is possible to connect the stove with a computer and monitor parameters. In the control, it was performed using a PIC 16F877A microprocessor which enabled convert analog signals to digital, perform serial communication with the IC MAX232 and enable signal transistors. The language used in the PIC's management is Basic. There are also a cooling system realized by two coolers 12V distributed in lateral structure, being used for venting and the other for exhaust air. To find out existing temperature inside is used LM35DZ sensor. Other mechanism used in the greenhouse construction was comprised of a reed switch and a magnet; their function is in recognition of the door position where a signal is sent to a buzzer when the door is open. Beyond it exist LEDs that help to identify the operation which the stove is located. To facilitate human-machine communication is employed an LCD display that tells real-time temperature and other information. The average range of design operating without any major problems, taking into account the limitations of the construction material and structure of electrical current conduction, is approximately 65 to 70 ° C. The project is efficient in these conditions, that is, when you wish to get information from a given material to be tested at temperatures not as high. With the implementation of the greenhouse automation, facilitating the temperature control and the development of a structure that encourages correct environment for the most diverse applications.

Keywords: greenhouse, microcontroller, temperature, control, MATLAB

Procedia PDF Downloads 379

Authors: Latif Duran, Erdem Aydin, Ahmet Baydin, Ali Kemal Erenler, Iskender Aksoy

Abstract:

Aim: In this retrospective study, we aim to contribute to the literature by presenting the proposals for taking measures to reduce the mortality by examining the demographic characteristics of the pediatric age group patients presenting with trauma and the factors that may cause mortality Material and Method: This study has been performed by retrospectively investigating the data obtained from the patient files and the hospital automation registration system of the pediatric trauma patients who applied to the Adult Emergency Department of the Ondokuz Mayıs University Medical Faculty between January 1, 2016, and December 31, 2016. Results: 289 of 415 patients involved in our study, were males. The median age was 11.3 years. The most common trauma mechanism was falling from the high. A significant statistical difference was found on the association between trauma mechanisms and gender. An increase in the number of trauma cases was found especially in the summer months. The study showed that thoracic and abdominal trauma was relevant to the increased mortality. Computerized tomography was the most common diagnostic imaging modality. The presence of subarachnoid hemorrhage has increased the risk of mortality by 62.3 fold. Eight of the patients (1.9%) died. Scoring systems were statistically significant to predict mortality. Conclusion: Children are vulnerable to trauma because of their unique anatomical and physiological differences compared to adult patient groups. It will be more successful in the mortality rate and in the post-traumatic healing process by administering the patient triage fast and most appropriate trauma centers in the prehospital period, management of the critical patients with the scoring systems and management with standard treatment protocols

Keywords: emergency service, pediatric patients, scoring systems, trauma, age groups

Procedia PDF Downloads 170

Authors: Sanelisiwe Ndlovu

Abstract:

Cities have become testbeds for automation and experimenting with artificial intelligence (AI) in managing urban services and public spaces. Smart Cities and AI systems are changing most human experiences from health and education to personal relations. For instance, in healthcare, social robots are being implemented as tools to assist patients. Similarly, in education, social robots are being used as tutors or co-learners to promote cognitive and affective outcomes. With that general picture in mind, one can now ask a further question about Smart Cities and artificial agents and their moral standing in the African context of personhood. There has been a wealth of literature on the topic of personhood; however, there is an absence of literature on African personhood in highly automated environments. Personhood in African philosophy is defined by the role one can and should play in the community. However, in today’s technologically advanced world, a risk is that machines become more capable of accomplishing tasks that humans would otherwise do. Further, on many African communitarian accounts, personhood and moral standing are associated with active relationality with the community. However, in the Smart City, human closeness is gradually diminishing. For instance, humans already do engage and identify with robotic entities, sometimes even romantically. The primary aim of this study is to investigate how African conceptions of personhood and community interact in a highly automated environment such as Smart Cities. Accordingly, this study lies in presenting a rarely discussed African perspective that emphasizes the necessity and the importance of relationality in handling Smart Cities and AI ethically. Thus, the proposed approach can be seen as the sub-Saharan African contribution to personhood and the growing AI debates, which takes the reality of the interconnectedness of society seriously. And it will also open up new opportunities to tackle old problems and use existing resources to confront new problems in the Fourth Industrial Revolution.

Keywords: smart city, artificial intelligence, personhood, community

Procedia PDF Downloads 173

Authors: Amjad Alsulami, Farah Albishri, Kholod Alzubidi, Lama Almehemadi, Salma Elhag

Abstract:

Food allergy is a common and rising problem among children. Many students have their first allergic reaction at school, one of these is anaphylaxis, which can be fatal. This study discovered that several schools' processes lacked safety regulations and information on how to handle allergy issues and chronic diseases like diabetes where students were not supervised or monitored during the cafeteria purchasing process. There is no obvious prevention or effort in academic institutions when purchasing food containing allergens or negatively impacting the health status of students who suffer from chronic diseases. Students must always be stable to reflect positively on their educational development process. To address this issue, this paper uses a business reengineering process to propose the automation of the whole food-purchasing process, which will aid in detecting and avoiding allergic occurrences and preventing any side effects from eating foods that are conflicting with students' health. This may be achieved by designing a smart card with an embedded QR code that reveals which foods cause an allergic reaction in a student. A survey was distributed to determine and examine how the cafeteria will handle allergic children and whether any management or policy is applied in the school. Also, the survey findings indicate that the integration of QR technology into the food purchasing process would improve health condition detection. The suggested system would be beneficial to all parties, the family agreed, as they would ensure that their children didn't eat foods that were bad for their health. Moreover, by analyzing and simulating the as-is process and the suggested process the results demonstrate that there is an improvement in quality and time.

Keywords: QR code, smart card, food allergies, business process reengineering, health condition detection

Procedia PDF Downloads 45

Authors: Lisete Barlach, Guilherme Ary Plonski

Abstract:

Innovative ideas are not always synonymous with business opportunities. Any idea can be creative and not recognized as a potential project in which money and time will be invested, among other resources. Even in firms that promote and enhance innovation, there are two 'check-points', the first corresponding to the acknowledgment of the idea as creative and the second, its consideration as a business opportunity. Both the recognition of new business opportunities or new ideas involve cognitive and psychological frameworks which provide individuals with a basis for noticing connections between seemingly independent events or trends as if they were 'connecting the dots'. It also involves prototypes-representing the most typical member of a certain category–functioning as 'templates' for this recognition. There is a general assumption that these kinds of evaluation processes develop through experience, explaining why expertise plays a central role in this process: the more experienced a professional, the easier for him (her) to identify new opportunities in business. But, paradoxically, an increase in expertise can lead to the inflexibility of thought due to automation of procedures. And, besides this, other cognitive biases can also be present, because new ideas or business opportunities generally depend on heuristics, rather than on established algorithms. The paper presents a literature review about the Einstellung effect by tracking famous cases of rejected ideas, extracted from historical records. It also presents the results of empirical research, with data upon rejected ideas gathered from two different environments: projects rejected during first semester of 2017 at a large incubator center in Sao Paulo and ideas proposed by employees that were rejected by a well-known business company, at its Brazilian headquarter. There is an implicit assumption that Einstellung effect tends to be more and more present in contemporaneity, due to time pressure upon decision-making and idea generation process. The analysis discusses desirability, viability, and feasibility as elements that affect decision-making.

Keywords: cognitive biases, Einstellung effect, recognition of business opportunities, rejected ideas

Procedia PDF Downloads 167

Authors: Omojokun G. Aju, Adedayo O. Sule

Abstract:

ZigBee wireless sensor and control network is one of the most popularly deployed wireless technologies in recent years. This is because ZigBee is an open standard lightweight, low-cost, low-speed, low-power protocol that allows true operability between systems. It is built on existing IEEE 802.15.4 protocol and therefore combines the IEEE 802.15.4 features and newly added features to meet required functionalities thereby finding applications in wide variety of wireless networked systems. ZigBee‘s current focus is on embedded applications of general-purpose, inexpensive, self-organising networks which requires low to medium data rates, high number of nodes and very low power consumption such as home/industrial automation, embedded sensing, medical data collection, smart lighting, safety and security sensor networks, and monitoring systems. Although the ZigBee design specification includes security features to protect data communication confidentiality and integrity, however, when simplicity and low-cost are the goals, security is normally traded-off. A lot of researches have been carried out on ZigBee technology in which emphasis has mainly been placed on ZigBee network performance characteristics such as energy efficiency, throughput, robustness, packet delay and delivery ratio in different scenarios and applications. This paper investigate and analyse the data accuracy, network implementation difficulties and security challenges of ZigBee network applications in star-based and mesh-based topologies with emphases on its home monitoring application using the ZigBee ProBee ZE-10 development boards for the network setup. The paper also expose some factors that need to be considered when designing ZigBee network applications and suggest ways in which ZigBee network can be designed to provide more resilient to network attacks.

Keywords: home monitoring, IEEE 802.14.5, topology, wireless security, wireless sensor network (WSN), ZigBee

Procedia PDF Downloads 355

Authors: Arkadiusz Zurek

Abstract:

The potential of using drones is visible in many areas of logistics, especially in terms of their use for monitoring and control of many processes. The technologies implemented in the last decade concern new possibilities for companies that until now have not even considered them, such as warehouse inventories. Unmanned aerial vehicles are no longer seen as a revolutionary tool for Industry 4.0, but rather as tools in the daily work of factories and logistics operators. The research problem is to develop a method for measuring the weight of goods in a selected link of the clothing supply chain by drones. However, the purpose of this article is to analyze the causes of errors in traditional measurements, and then to identify adverse events related to the use of drones for the inventory of a heap of textiles intended for production purposes. On this basis, it will be possible to develop guidelines to eliminate the causes of these events in the measurement process using drones. In a real environment, work was carried out to determine the volume and weight of textiles, including, among others, weighing a textile sample to determine the average density of the assortment, establishing a local geodetic network, terrestrial laser scanning and photogrammetric raid using an unmanned aerial vehicle. As a result of the analysis of measurement data obtained in the facility, the volume and weight of the assortment and the accuracy of their determination were determined. In this article, this work presents how such heaps are currently being tested, what adverse events occur, indicate and describes the current use of photogrammetric techniques of this type of measurements so far performed by external drones for the inventory of wind farms or construction of the station and compare them with the measurement system of the aforementioned textile heap inside a large-format facility.

Keywords: drones, unmanned aerial system, UAS, indoor system, security, process automation, cost optimization, photogrammetry, risk elimination, industry 4.0

Procedia PDF Downloads 44

Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

Abstract:

The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

Procedia PDF Downloads 57

Authors: Faris Elghaish, Sepehr Abrishami, Mark Gaterell, Richard Wise

Abstract:

The collaboration and integration between all building information management (BIM) processes and tasks are necessary to ensure that all project objectives can be delivered. The literature review has been used to explore the state of the art BIM technologies to manage construction materials as well as the challenges which have faced the construction process using traditional methods. Thus, this paper aims to articulate a framework to integrate traditional material planning methods such as ABC analysis theory (Pareto principle) to analyse and categorise the project materials, as well as using independent material planning methods such as Economic Order Quantity (EOQ) and Fixed Order Point (FOP) into the BIM 4D, and 5D capabilities in order to articulate a dependent material planning cycle into BIM, which relies on the constructability method. Moreover, we build a model to connect between the material planning outputs and the BIM 4D and 5D data to ensure that all project information will be accurately presented throughout integrated and complementary BIM reporting formats. Furthermore, this paper will present a method to integrate between the risk management output and the material management process to ensure that all critical materials are monitored and managed under the all project stages. The paper includes browsers which are proposed to be embedded in any 4D BIM platform in order to predict the EOQ as well as FOP and alarm the user during the construction stage. This enables the planner to check the status of the materials on the site as well as to get alarm when the new order will be requested. Therefore, this will lead to manage all the project information in a single context and avoid missing any information at early design stage. Subsequently, the planner will be capable of building a more reliable 4D schedule by allocating the categorised material with the required EOQ to check the optimum locations for inventory and the temporary construction facilitates.

Keywords: building information management, BIM, economic order quantity, EOQ, fixed order point, FOP, BIM 4D, BIM 5D

Procedia PDF Downloads 144

Authors: Vivek Anand, Rainer Naegele

Abstract:

Industry 4.0 envisages 'smart' manufacturing and services, taking the automation of the 3rd Industrial Revolution to the autonomy of the 4th Industrial Revolution. Powered by innovations in technology and business models, this disruptive transformation is revitalising industry by integrating silos across and beyond value chains. Motivated by the challenges faced by SMEs and Startups in understanding and adopting Industry 4.0, this paper aims to analyse the concept of Growth Poles and evaluate the possibility of its application to Innovation Clusters that strive to propel Industry 4.0 adoption and capacity building. The proposed paper applies qualitative research methodologies including focus groups and survey questionnaires to identify the various factors that affect formation and development of Innovation Clusters. Employing content analysis, the interaction between SMEs and other ecosystem players in such clusters is studied. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position these cluster-based growth poles at the forefront of industrial renaissance. Motivated by this argument, and based on the results of the qualitative research, a roadmap will be proposed to position Innovation Clusters as Growth Poles and effective ecosystems to support Industry 4.0 adoption in a region in the medium to long term. This paper will contribute to the current understanding of the role of Innovation Clusters in capacity building. Relevant management and policy implications stem from the analysis. Furthermore, the findings will be helpful for academicians and policymakers alike, who can leverage an ‘innovation cluster policy’ to enable Industry 4.0 Growth Poles in their regions.

Keywords: digital transformation, fourth industrial revolution, growth poles, industry 4.0, innovation clusters, innovation policy, SMEs and startups

Procedia PDF Downloads 201