Search results for: project classification

Authors: Faraz Ali Memon

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Stakeholders are a vital part of any organisation. It includes working on the demands of different stakeholders within the projects. However, the reality of construction projects is slightly different when it comes to practice. The UK construction projects have a history of failing to complete projects on time and within the budget. The purpose of this qualitative study is to enhance knowledge of stakeholder engagement. Semi-structured interviews will be carried out using a purposive sampling technique. It includes interviewing and getting knowledge from industry practitioners from top UK construction firms on how to manage stakeholders effectively. The findings from this study will help in understanding stakeholders' impact and how the engagement of stakeholders can affect construction projects. The conclusions of this study add value to the existing body of knowledge on stakeholder management, especially in the UK, where academic studies on construction projects are few. As a contribution, this study will provide a practical guide for the practitioners to engage stakeholders within the scope of the project. In addition, this study is limited to UK construction projects. Therefore, the outcome may not be generalised to other developing and underdeveloped countries.

Keywords: stakeholders, UK construction, project management, cost and time

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Authors: Aniket Aaba Kadam, Manish Mangesh Panchal, Roushan Ashit Sharma

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This project focuses on the design and development of a lab-scale hybrid rocket motor to accurately determine the regression rate of a fuel/oxidizer combination consisting of solid paraffin and gaseous oxygen (GOX). Hybrid motors offer the advantage of on-demand thrust control over both solid and liquid systems in certain applications. The thermodynamic properties of the propellant combination were calculated using NASA CEA at different chamber pressures and corresponding O/F values to determine initial operating conditions with suitable peak temperatures and optimal O/F values. The project also includes the design of the injector orifice and the determination of the final design configurations of the motor casing, pressure control setup, and valve configuration. This research will be valuable in advancing the understanding of paraffin-based propulsion and improving the performance of hybrid rocket motors.

Keywords: hybrid rocket, NASA CEA, injector, thrust control

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Authors: Olivier Chaigneau, Damianos Oikonomidis, Marie-Cecile Delmas

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GAMBAS (Galileo Advanced features for the Maritime domain: Breakthrough Applications for Safety and security) is a project funded by the European Space Program Agency (EUSPA) aiming at identifying the search-and-rescue and ship security alert system needs for maritime users (including operators and fishing stakeholders) and developing operational concepts to answer these needs. The general objective of the GAMBAS project is to support the deployment of Galileo exclusive features in the maritime domain in order to improve safety and security at sea, detection of illegal activities and associated surveillance means, resilience to natural and human-induced emergency situations, and develop, integrate, demonstrate, standardize and disseminate these new associated capabilities. The project aims to demonstrate: improvement of the SAR (Search And Rescue) and SSAS (Ship Security Alert System) detection and response to maritime distress through the integration of new features into the beacon for SSAS in terms of cost optimization, user-friendly aspects, integration of Galileo and OS NMA (Open Service Navigation Message Authentication) reception for improved authenticated localization performance and reliability, and at sea triggering capabilities, optimization of the responsiveness of RCCs (Rescue Co-ordination Centre) towards the distress situations affecting vessels, the adaptation of the MCCs (Mission Control Center) and MEOLUT (Medium Earth Orbit Local User Terminal) to the data distribution of SSAS alerts.

Keywords: Galileo new advanced features, maritime, safety, security

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Authors: Erika Duggan

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A Major Hospital had identified that there was no standard process for handling a patient’s medication that they brought with them to the hospital. It was also identified that each floor was handling the patient’s medication differently and storing it in multiple locations. Based on this disconnect many patients were leaving the hospital without their medication. The project team was tasked with creating a cohesive process to send a patient’s unneeded medication home on admission, storing any of the patient’s medication that could not be sent home, storing any of the patient’s medication for inpatient administration, and sending all of the patient’s medication home on discharge. The project team consisted of pharmacists, RNs, LPNs, members from nursing informatics and a project engineer and followed a DMAIC framework. Working together observations were performed to identify what was working and not working on the different floors which resulted in process maps. Using the multidisciplinary team, brainstorming, including affinity diagramming and other lean six sigma techniques, the best process for receiving, storing, and returning the medication was created. It was highlighted that being able to track the medication throughout the patient’s stay would be beneficial and would help make sure the medication left with the patient on discharge. Using an automated medications dispensing system would help store, and track patient’s medications. Also, the use of a specific order that would show up on the discharge instructions would assist the front line staff in retrieving the medication from a set location and sending it home with the patient. This new process will effectively streamline the admission and discharge process for patients who brought their medication with them as well as effectively tracking the medication during the patient’s stay. As well as increasing patient safety as it relates to medication administration.

Keywords: lean six sigma, medication dispensing, process improvement, process mapping

Procedia PDF Downloads 254

Authors: Kashmir Johal

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Within a wider context of improving whole-life effectiveness of gas and oil fields, we have been researching how to generate power local to the wellhead. (Provision of external power to a subsea wellhead can be prohibitively expensive and results in uneconomic fields. This has been an oil/gas industry challenge for many years.) We have been developing a possible approach to “local” power generation and have been conducting technical, environmental, (and economic) research to develop a viable approach. We sought to create a workable design for a new type of power generation system that makes use of differential pressure that can exist between the sea surface and a gas (or oil reservoir). The challenge has not just been to design a system capable of generating power from potential energy but also to design it in such a way that it anticipates and deals with the wide range of technological, environmental, and chemical constraints faced in such environments. We believe this project shows the enormous opportunity in deriving clean, economic, and zero emissions renewable energy from offshore sources. Since this technology is not currently available, a patent has been filed to protect the advancement of this technology.

Keywords: renewable, energy, power, offshore

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Authors: Francisco M. Silva

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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.

Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Lisa Wilderink, Ingrid Bakker, Albertine J. Schuit, Jacob C. Seidell, Carry M. Renders

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To ensure that health behavior interventions for children living in low socioeconomic position (SEP) neighborhoods are in line with children’s wishes and needs, participation of the children in the development, implementation, and evaluation is crucial. In this paper, we show how children living in three low-SEP neighborhoods in the Netherlands can be involved in Participatory Action Research (PAR) and what influences this participation process. The Photovoice method was used and provided comprehensive information from the children’s perspectives. With the help of the community workers, the children identified feasible actions. This paper shows that it is possible to involve children from low SEP neighborhoods in a meaningful way. We found that it is important to constantly discuss the process with participants, start with a concrete question or problem and adapt the project to the local context and skills of participants

Keywords: children, healthy behavior, participatory action research, socioeconomic health inequalities

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Authors: Steven Kelly

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A fundament role of the researcher is research engagement, that is, the interaction between researchers and research end-users outside of academia for the mutually beneficial transfer of knowledge, technologies, methods, or resources. While research impact is the contribution that research makes to the economy, society, environment, or culture beyond the contribution to academic research. Ironically, traditional impact metrics in the academy are designed to focus on the outputs; it dismisses the important role engagement plays in fostering a collaborative process that leads to meaningful, ethical, and useful impacts. Dr. Kelly, aNanda (First Nations) man himself, has worked closely with the Nanda community over the past decade, ensuring cultural protocols are upheld and implemented while doing research engagement. The focus was on the process, which was essential to foster a positive research impact culture. The contributions that flowed from this process were the naming of a new species of squat lobster in the Nanda language, a poster design in collaboration with The University of Melbourne, Museums Victoria and Bundiyarra - IrraWanga language centre, media coverage, and the formation of the “Nanda language, Nanda country project”. The Nanda language, Nanda country project is a language revitalization project that focused on reconnecting Nanda people with the language & culture on Nanda Country. Such outcomes are imperative on the eve of the United Nations International Decade of Indigenous Languages. In this paperDr, Kellywill discuss howNanda cultural practicesinformed research engagement to foster a collaborative processthat, in turn, ledto meaningful, ethical, and useful impacts within and outside of the academy.

Keywords: community collaboration, indigenous, nanda, research engagement, research impacts

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Authors: H. G. C. P. Dinesh, G. Tharshini, M. P. B. Ekanayake, G. M. R. I. Godaliyadda

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This paper presents a new spatial feature extraction method based on principle component analysis (PCA) and Fisher Discernment Analysis (FDA) for facial expression recognition. It not only extracts reliable features for classification, but also reduces the feature space dimensions of pattern samples. In this method, first each gray scale image is considered in its entirety as the measurement matrix. Then, principle components (PCs) of row vectors of this matrix and variance of these row vectors along PCs are estimated. Therefore, this method would ensure the preservation of spatial information of the facial image. Afterwards, by incorporating the spectral information of the eigen-filters derived from the PCs, a feature vector was constructed, for a given image. Finally, FDA was used to define a set of basis in a reduced dimension subspace such that the optimal clustering is achieved. The method of FDA defines an inter-class scatter matrix and intra-class scatter matrix to enhance the compactness of each cluster while maximizing the distance between cluster marginal points. In order to matching the test image with the training set, a cosine similarity based Bayesian classification was used. The proposed method was tested on the Cohn-Kanade database and JAFFE database. It was observed that the proposed method which incorporates spatial information to construct an optimal feature space outperforms the standard PCA and FDA based methods.

Keywords: facial expression recognition, principle component analysis (PCA), fisher discernment analysis (FDA), eigen-filter, cosine similarity, bayesian classifier, f-measure

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Authors: Per Blomqvist

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The overall aim of this study is to highlight how the degree project-course in teacher education has developed over time at Swedish universities, above all regarding changes in the formative assessment practices in relation to student's opportunities to take part in writing processes that can develop both their independent critical thinking, subject knowledge, and academic writing skills. Theoretically, the study is based on deliberative and transformative perspectives of teaching academic writing in higher education. The deliberative perspective is motivated by the fact that it is the universities and their departments' responsibility to give the students opportunities to develop their academic writing skills, while there is little guidance on how this can be implemented. The transformative perspective is motivated by the fact that education needs to be adapted to the student's prior knowledge and developed in relation to the student group. Given the academisation of education and the new student groups, this is a necessity. The empirical data consists of video recordings of teacher groups' conversations at three Swedish universities. The conversations were conducted as so-called collective remembering interviews, a method to stimulate the participants' memory through social interaction, and focused on addressing issues on how the degree project-course in teacher education has changed over time. Topic analysis was used to analyze the conversations in order to identify common descriptions and expressions among the teachers. The result highlights great similarities in how the degree project-course has changed over time, both from a deliberative and a transformative perspective. The course is characterized by a “strong framing,” where the teachers have great control over the work through detailed instructions for the writing process and detailed templates for the text. This is justified by the fact that the education has been adapted based on the student teachers' lack of prior subject knowledge. The strong framing places high demands on continuous discussions between teachers about, for example, which tools the students have with them and which linguistic and textual tools are offered in the education. The teachers describe that such governance often leads to conflicts between teachers from different departments because reading and writing are always part of cultural contexts and are linked to different knowledge, traditions, and values. The problem that is made visible in this study raises questions about how students' opportunities to develop independence and make critical judgments in academic writing are affected if the writing becomes too controlled and if passing students becomes the main goal of education.

Keywords: formative assessment, academic writing, degree project, higher education, deliberative perspective, transformative perspective

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: David de Oliveira Costa, Miguel Ângelo Lellis Moreira, Carlos Francisco Simões Gomes, Daniel Augusto de Moura Pereira, Marcos dos Santos

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Strategic management is a fundamental process for global companies that intend to remain competitive in an increasingly dynamic and complex market. To do so, it is necessary to maintain alignment with their principles and values. The Balanced Scorecard (BSC) proposes to ensure that the overall business performance is based on different perspectives (financial, customer, internal processes, and learning and growth). However, relying solely on the BSC may not be enough to ensure the success of strategic management. It is essential that companies also evaluate and prioritize strategic projects that need to be implemented to ensure they are aligned with the business vision and contribute to achieving established goals and objectives. In this context, the proposition involves the incorporation of the SAPEVO-M multicriteria method to indicate the degree of relevance between different perspectives. Thus, the strategic objectives linked to these perspectives have greater weight in the classification of structural projects. Additionally, it is proposed to apply the concept of the Impact & Probability Matrix (I&PM) to structure and ensure that strategic projects are evaluated according to their relevance and impact on the business. By structuring the business's strategic management in this way, alignment and prioritization of projects and actions related to strategic planning are ensured. This ensures that resources are directed towards the most relevant and impactful initiatives. Therefore, the objective of this article is to present the proposal for integrating the BSC methodology, the SAPEVO-M multicriteria method, and the prioritization matrix to establish a concrete weighting of strategic planning and obtain coherence in defining strategic projects aligned with the business vision. This ensures a robust decision-making support process.

Keywords: MCDA process, prioritization problematic, corporate strategy, multicriteria method

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Authors: Bisemiire Anthony,

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PESH Poultry is a business project proposed specifically to solve unemployment and income-related problems affecting the youths in the Busia district. The project is intended to transform the life of the youth in terms of economic, social and behavioral, as well as the domestic well-being of the community at large. PESH Poultry is a start-up poultry farm that will be engaged in the keeping of poultry birds, broilers and layers for the production of quality and affordable poultry meat and eggs respectively and other poultry derivatives targeting consumers in eastern Uganda, for example, hotels, restaurants, households and bakeries. We intend to use a semi-intensive system of farming, where water and some food are provided in a separate nighttime shelter for the birds; our location will be in Lumino, Busia district. The poultry project will be established and owned by Bisemiire Anthony, Nandera Patience, Naula Justine, Bwire Benjamin and other investors. The farm will be managed and directed by Nandera Patience, who has five years of work experience and business administration knowledge. We will sell poultry products, including poultry eggs, chicken meat, feathers and poultry manure. We also offer consultancy services for poultry farming. Our eggs and chicken meat are hygienic, rich in protein and high quality. We produce processes and packages to meet the standard organization of Uganda and international standards. The business project shall comprise five (5) workers on the key management team who will share various roles and responsibilities in the identified business functions such as marketing, finance and other related poultry farming activities. PESH Poultry seeks 30 million Ugandan shillings in long-term financing to cover start-up costs, equipment, building expenses and working capital. Funding for the launch of the business will be provided primarily by equity from the investors. The business will reach positive cash flow in its first year of operation, allowing for the expected repayment of its loan obligations. Revenue will top UGX 11,750,000, and net income will reach about UGX115 950,000 in the 1st year of operation. The payback period for our project is 2 years and 3 months. The farm plans on starting with 1000 layer birds and 1000 broiler birds, 20 workers in the first year of operation.

Keywords: chicken, pullets, turkey, ducks

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Authors: Rahul Thakur, Onkar Chandel

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Red Hat is the world leader in providing open source software and solutions. A global enterprise, like Red Hat, has unique issues of connecting employees with content because of distributed offices, multiple teams spread across geographies, multiple languages, and different cultures. Employees, of a global company, create content that is distributed across departments, teams, regions, and countries. This makes finding the best content difficult since owners keep iterating on the existing content. When employees are unable to find the content, they end up creating it once again and in the process duplicating existing material and effort. Also, employees may not find the relevant content and spend time reviewing obsolete duplicate, or irrelevant content. On an average, a person spends 15 minutes/day in failed searches that might result in missed business opportunities, employee frustration, and substandard deliverables. Red Hat Knowledge Management Office (KMO) applied 'open source strategy' to solve the above problems. Under the Open Source Strategy, decisions are taken collectively. The strategy aims at accomplishing common goals with the help of communities. The objectives of this initiative were to save employees' time, get them authentic content, improve their content search experience, avoid duplicate content creation, provide context based search, improve analytics, improve content management workflows, automate content classification, and automate content upload. This session will describe open source strategy, its applicability in content management, challenges, recommended solutions, and outcome.

Keywords: content classification, content management, knowledge management, open source

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Vitalijs Lusis, Videvuds-Arijs Lapsa, Olga Kononova, Andrejs Krasnikovs

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Steel fibres use in a concrete, such way obtaining Steel Fibre Reinforced Concrete (SFRC), is an important technological direction in building industry. Steel fibers are substituting the steel bars in conventional concrete in another situation is possible to combine them in the concrete structures. Traditionally fibers are homogeneously dispersed in a concrete. At the same time in many situations fiber concrete with homogeneously dispersed fibers is not optimal (majority of added fibers are not participating in a load bearing process). It is obvious, that is possible to create constructions with oriented fibers distribution in them, in different ways. Present research is devoted to one of them. Acknowledgment: This work has been supported by the European Social Fund within the project «Support for the implementation of doctoral studies at Riga Technical University» and project No. 2013/0025/1DP/1.1.1.2.0/13/APIA/VIAA/019 “New “Smart” Nanocomposite Materials for Roads, Bridges, Buildings and Transport Vehicle”.

Keywords: fiber reinforced concrete, 4-point bending, steel fiber, SFRC

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Authors: Hassan Noun, Christian Urban-Seelmann, Mohamed Abdelfattah, Guillaume Zeller, Rajesh G., Iryna Mozgova, Roland Lachmayer

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Several modules in automotive are usually modified and adapted for various project-specific applications. Due to a standardized safety concept, high reusability is accessible. A safety element out of context (SEooC) according to ISO 26262 can be a suitable approach. Based on the same safety concept and analysis, common modules can reach high usability. For developing according to a module out of context, an appropriate and detailed development approach is required. This paper shows how to derive these development processes for platform modules. Therefore, the detailed approach to the safety element out of context is derived. The aim is to create a detailed workflow for all phases of the development and integration of any kind of system modules. As an application example, an automotive project for an actuator control module is considered.

Keywords: functional safety, engineering processes, system engineering, electronic engineering

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Authors: Jichi Wu

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Though fast fashion and consumption do boost the economy and push the progress of the industry, they have also caused a mass of waste, which has led to great pressure on the environment. This project mainly focuses on how to develop new sustainable textile and fashion design through recycling, upcycling, and reusing. Substantial field researches were implemented from the very beginning, including collecting reusable material from recycling centers. Hot-pressed composite materials, hand-cutting, and weaving were finally selected as the core material/method of this project after attempts and experiments. Four pieces of menswear, as well as hats and other decorative products made from wasted foams and fabrics, were successfully manufactured. Results show that foam is not only possible for furniture but also for clothing. It helps people to realize that foam is warm, heatproof, anti-slippery, and crease-resistant. So, all advantages could inspire people that even common materials could have new usage and are worthy of upcycling.

Keywords: sustainable design, foam, upcycling, life cycle, textile design

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Authors: Mohammed Aljoma, Eblal Zakzok

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Safety is a science that seeks to protect and avoid humans from risks in any field and prevent losses in properties and lives as much as possible. On the other hand, occupational safety goals aim to protect workers from risks which can occur during work execution. The main purpose of occupational safety is to ultimately protect people, properties and the environment by reducing accidents and injuries that may cause losses and damages. To achieve this goal, we must remove the direct and indirect reasons which cause accidents and injuries; some of the reasons of accidents are the unsafe cases and inept behavior or both of them. This research focuses on the manner of providing instant protection from the very first beginning to people, properties and the environment by: -Inserting safety demands in the planning and designing works by identifying risk levels in every task of the project, -Using a new risk managing system or modifying or changing a previously-used one.

Keywords: planning, scheduling, risk management, project duration, site safety

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Authors: Radha Krishan, Deepak Khare, Bhaskar R. Nikam, Ayush Chandrakar

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Every irrigation project is planned considering long-term historical climatic conditions; however, the prompt climatic shift and change has come out with such circumstances which were inconceivable in the past. Considering this fact, scrutiny of rainfall and temperature trend has been carried out over the command area of Eastern Ganga Canal project for pre-climate shift period and post-climate shift periods in the present study. Non-parametric Mann-Kendall and Sen’s methods have been applied to study the trends in annual rainfall, seasonal rainfall, annual rainy day, monsoonal rainy days, average annual temperature and seasonal temperature. The results showed decreasing trend of 48.11 to 42.17 mm/decade in annual rainfall and 79.78 tSo 49.67 mm/decade in monsoon rainfall in pre-climate to post-climate shift periods, respectively. The decreasing trend of 1 to 4 days/decade has been observed in annual rainy days from pre-climate to post-climate shift period. Trends in temperature revealed that there were significant decreasing trends in annual (-0.03 ºC/yr), Kharif (-0.02 ºC/yr), Rabi (-0.04 ºC/yr) and summer (-0.02 ºC/yr) season temperature during pre-climate shift period, whereas the significant increasing trend (0.02 ºC/yr) has been observed in all the four parameters during post climate shift period. These results will help project managers in understanding the climate shift and lead them to develop alternative water management strategies.

Keywords: climate shift, rainfall trend, temperature trend, Mann-Kendall test, sen slope estimator, eastern Ganga canal command

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Authors: M. Armenteros, A. Domínguez, M. Fernández, A. J. Benítez

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The following paper describes the video database tool used by the Fédération Internationale de Football Association (FIFA) as part of the research project developed in collaboration with the Carlos III University of Madrid. The database project began in 2012, with the aim of creating an educational tool for the training of instructors, referees and assistant referees, and it has been used in all FUTURO III courses since 2013. The platform now contains 3,135 video clips of different match situations from FIFA competitions. It has 1,835 users (FIFA instructors, referees and assistant referees). In this work, the main features of the database are described, such as the use of a search tool and the creation of multimedia presentations and video quizzes. The database has been developed in MySQL, ActionScript, Ruby on Rails and HTML. This tool has been rated by users as "very good" in all courses, which prompt us to introduce it as an ideal tool for any other sport that requires the use of video analysis.

Keywords: assistants referees, cloud computing, e-learning, instructors, FIFA, referees, soccer, video database

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Authors: Jelena Kovačević Vorgučin, Sibila Petenji Arbutina

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The postmodern age brings a rapid development of technology which inevitably leads to man's need to adapt to modern lifestyle. On the one hand, technological achievements have made human life easier, but there are numerous risks involved. Moreover, man's awareness and perception is changing and adapting unconsciously to the world we live in, while communication in the 21st century is predominantly based on the consumption of images. This paper presents sociological aspects of a community which is confined due to turbulent political-economic circumstances and its impact on the development of media literacy in Serbia. Previous researches led to the conclusion that the media culture is on an extremely low level, and that it can have a strong influence on the general development of the society, starting from the youngest segment of the population. Our aim is to use the conceptual authorial photographs inspired by the obtained research results to emphasize the importance that the impact of visual art has in delivering the message, its role in education and in raising awareness of universal social problems. The paper presents a number of stages involved in the conceptual project which is designed to last over a longer period of time in order to facilitate dissemination of information. First, a survey was carried out in several preschool institutions. This resulted in obtaining the necessary information on the habitual use of the medium of television in children and their carers-parents. The second stage focused on the relationship between the parent and the child in TV consumption. Further, an overview of the visual part of the project was made, which consisted of photographs in various dimensions, ranging from miniature to large dimensions, and following various exhibition principles in both gallery and alternative spaces. This stage of the project placed particular emphasis on the non-standard exhibiting formats and alternative exhibition principles which are increasingly present in all kinds of visual art aimed at achieving a higher level of information noticing and memorizing. The motif on the authorial photographs is children's portraits taken while they are watching different television contents, with emphasis on their emotional response. The importance of the medium of TV is particularly emphasized due to the fact that its consumption is the highest, even though there are newer and more advanced information-technological achievements. The already realized part of the project was used for an analysis of the results in the last stage of the project, which led to the conclusion that the response to the entire visual expression campaign was extremely positive, and action as such very useful indeed. The results obtained speak in favour of widening and continuation of the project, both on a greater number of sites locally as well as in other communities in Serbia with the aim of guiding people towards meaningful consumption of the television medium.

Keywords: alternative space exhibiting, children and TV, conceptual portrait photography, media literacy

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Authors: Yoshinori Wakatake

Abstract:

Many defects after the release of software packages are caused due to omissions of sufficient test items in test specifications. Poor test specifications are detected by manual review, which imposes a high human load. The prevention of omissions depends on the end-user awareness of test specification writers. If test specifications were written while envisioning the behavior of end-users, the number of omissions in test items would be greatly reduced. The paper pays attention to the point that writers who can achieve it differ from those who cannot in not only the description richness but also their gaze information. It proposes a method to estimate the degree of user-awareness of writers through the analysis of their gaze information when writing test specifications. We conduct an experiment to obtain the gaze information of a writer of the test specifications. Test specifications are automatically classified using gaze information. In this method, a Random Forest model is constructed for the classification. The classification is highly accurate. By looking at the explanatory variables which turn out to be important variables, we know behavioral features to distinguish test specifications of high quality from others. It is confirmed they are pupil diameter size and the number and the duration of blinks. The paper also investigates test specifications automatically classified with gaze information to discuss features in their writing ways in each quality level. The proposed method enables us to automatically classify test specifications. It also prevents test item omissions, because it reveals writing features that test specifications of high quality should satisfy.

Keywords: blink, eye tracking, gaze information, pupil diameter, quality improvement, specification document, user-awareness

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

Abstract:

Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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Authors: Marie Oslène Honorat

Abstract:

Porto Belo is a neighborhood in the city of Foz do Iguaçu / PR, located in the Vila C region of Brazil. It is a project that addresses the question of the dirt generated by the neighborhood community about how they dispose and recycle domestic waste. This project aimed at raising awareness among residents, on how important it is to preserve the environment and take care, especially of the space in which we are located. Living this way manages to minimize the exploitation of natural resources, soil and water pollution. After collecting information about what one saw, we questioned some people in the neighborhood to find out about selective collection, recycling, and the separation and final destination of garbage. From the study, it was possible to verify the importance of placing more trash cans on neighborhood streets, where garbage is discarded, and the importance of promoting environmental education to improve the environment and quality of life. The methodology used in this research was a qualitative methodology that seeks the principle of transforming reality through investigation.

Keywords: awareness, recycling, selective collection, waste disposal

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Authors: Kishen Prathivadi

Abstract:

The Sewer Authority Mid-Coastside (SAM) is a Joint Powers Authority formed in 1976 and provides secondary wastewater treatment to an average flow of 2.0 million gallons per day. SAM owns and operates a Wastewater Treatment Plant (WWTP) and a sanitary sewage collection system that collects sewage from its three member agencies: the City of Half Moon Bay, the Granada Community Services District and Montara Water and Sanitary District. The Sewer Authority Mid-Coastside (SAM) partnered with Pacific Gas & Electric, and its contractor GEL America, to review and replace all inefficient lighting fixtures and bulbs at the SAM treatment plant and administrative office. The project focused on replacing old and inefficient lighting fixtures and bulbs, reducing annual operating and maintenance costs, and reducing SAM’s carbon footprint. The project resulted in a 55% overall energy reduction, higher light quality and acuity, and a total operational savings of $495,000 over ten years.

Keywords: energy savings, LED, lighting, electrical

Procedia PDF Downloads 139

Authors: Cheng-Yu Tsai, Wen-Te Liu, Shin-Mei Hsu, Yin-Tzu Lin, Chi Wu

Abstract:

Background: Obstructive Sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. In addition, Body parameters were identified high predictive importance for OSAS severity. However, the effects of body parameters on OSAS severity remain unclear. Objective: In this study, the objective is to establish a prediction model for OSAS by using body parameters and investigate the effects of body parameters in OSAS. Methodologies: Severity was quantified as the polysomnography and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). Four levels of OSAS severity were classified by the apnea and hypopnea index (AHI) with American Academy of Sleep Medicine (AASM) guideline. Body parameters, including neck circumference, waist size, and body mass index (BMI) were obtained from questionnaire. Next, dividing the collecting subjects into two groups: training and testing groups. The training group was used to establish the random forest (RF) to predicting, and test group was used to evaluated the accuracy of classification. Results: There were 3330 subjects recruited in this study, whom had been done polysomnography for evaluating severity for OSAS. A RF of 1000 trees achieved correctly classified 79.94 % of test cases. When further evaluated on the test cohort, RF showed the waist and BMI as the high import factors in OSAS. Conclusion It is possible to provide patient with prescreening by body parameters which can pre-evaluate the health risks.

Keywords: apnea and hypopnea index, Body parameters, obstructive sleep apnea syndrome, Random Forest

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Authors: Mohsen Maraoui

Abstract:

In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

Procedia PDF Downloads 141

Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

Abstract:

Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

Procedia PDF Downloads 54