Search results for: scalable automation testing

Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

Procedia PDF Downloads 177

Authors: B. K. Yadav, A. Gandhi, A. K. Verma, T. S. Rao, A. Saraswat, E. R. Kumar, M. Sarkar, K. N. Vyas

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This paper deals with the conceptual design of Experimental Helium Cooling Loop (EHCL) for Indian Test Blanket Module (TBM) and its related thermal hydraulic experiments. Indian TBM team is developing Lead Lithium cooled Ceramic Breeder (IN-LLCB) TBM to be tested in ITER. The TBM box structure is cooled by high pressure (8 MPa) and high temperature (300-500C) helium gas. The first wall of TBM made of complex channel geometry having several parallel channels carrying helium gas for efficient heat extraction. Several mock-ups of these channels need to be tested before finalizing the TBM first wall design and fabrication. Besides the individual testing of such mock-ups of breeding blanket, the testing of Pb-Li to helium heat exchanger, the operational experience of helium loop and understanding of the behaviour of high pressure and high temperature system components are very essential for final development of Helium Cooling System for LLCB TBM in ITER. The main requirements and characteristics of the EHCL and its conceptual design are presented in this paper.

Keywords: DEMO, EHCL, ITER, LLCB TBM

Procedia PDF Downloads 383

Authors: Faci Youcef, Ahmed Mebtouche, Djillali Allou, Maalem Badredine

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The inclination of the bolt in a fastened joint of composite material during a tensile test can be influenced by several parameters, including material properties, bolt diameter and length, the type of composite material being used, the size and dimensions of the bolt, bolt preload, surface preparation, the design and configuration of the joint, and finally testing conditions. These parameters should be carefully considered and controlled to ensure accurate and reliable results during tensile testing of composite materials with fastened joints. Our work focuses on the effect of the stacking sequence and the geometry of specimens. An experimental test is carried out to obtain the inclination of a bolt during a tensile test of a composite material using acoustic emission and digital image correlation. Several types of damage were obtained during the load. Digital image correlation techniques permit the obtaining of the inclination of bolt angle value during tensile test. We concluded that the inclination of the bolt during a tensile test of a composite material can be related to the damage that occurs in the material. It can cause stress concentrations and localized deformation in the material, leading to damage such as delamination, fiber breakage, matrix cracking, and other forms of failure.

Keywords: damage, inclination, analyzed, carbon

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Lewis J. Woollin, Robert I. Davidson, Paul Watson, Philip J. Hyde

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Introduction: In-vitro testing of arthroplasty materials is of paramount importance when ensuring that they can withstand the performance requirements encountered in-vivo. One common machine used for in-vitro testing is a pin-on-plate tribometer, an early stage screening device that generates data on the wear characteristics of arthroplasty bearing materials. These devices test vertically loaded rotating cylindrical pins acting against reciprocating plates, representing the bearing surfaces. In this study, a pin-on-plate machine has been developed that provides several improvements over current technology, thereby progressing arthroplasty bearing research. Historically, pin-on-plate tribometers have been used to investigate the performance of arthroplasty bearing materials under conditions commonly encountered during a standard gait cycle; nominal operating pressures of 2-6 MPa and an operating frequency of 1 Hz are typical. There has been increased interest in using pin-on-plate machines to test more representative in-vivo conditions, due to the drive to test 'beyond compliance', as well as their testing speed and economic advantages over hip simulators. Current pin-on-plate machines do not accommodate the increased performance requirements associated with more extreme kinematic conditions, therefore a next-generation pin-on-plate tribometer has been developed to bridge the gap between current technology and future research requirements. Methodology: The design was driven by several physiologically relevant requirements. Firstly, an increased loading capacity was essential to replicate the peak pressures that occur in the natural hip joint during running and chair-rising, as well as increasing the understanding of wear rates in obese patients. Secondly, the introduction of mid-cycle load variation was of paramount importance, as this allows for an approximation of the loads present in a gait cycle to be applied and to test the fatigue properties of materials. Finally, the rig must be validated against previous-generation pin-on-plate and arthroplasty wear data. Results: The resulting machine is a twelve station device that is split into three sets of four stations, providing an increased testing capacity compared to most current pin-on-plate tribometers. The loading of the pins is generated using a pneumatic system, which can produce contact pressures of up to 201 MPa on a 3.2 mm² round pin face. This greatly exceeds currently achievable contact pressures in literature and opens new research avenues such as testing rim wear of mal-positioned hip implants. Additionally, the contact pressure of each set can be changed independently of the others, allowing multiple loading conditions to be tested simultaneously. Using pneumatics also allows the applied pressure to be switched ON/OFF mid-cycle, another feature not currently reported elsewhere, which allows for investigation into intermittent loading and material fatigue. The device is currently undergoing a series of validation tests using Ultra-High-Molecular-Weight-Polyethylene pins and 316L Stainless Steel Plates (polished to a Ra < 0.05 µm). The operating pressures will be between 2-6 MPa, operating at 1 Hz, allowing for validation of the machine against results reported previously in the literature. The successful production of this next-generation pin-on-plate tribometer will, following its validation, unlock multiple previously unavailable research avenues.

Keywords: arthroplasty, mechanical design, pin-on-plate, total joint replacement, wear testing

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Authors: Sastry Y. Kandukuri, Isak Andersen

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Despite recent advances in the manufacturing sector, quality issues remain a frequent occurrence, and can result in fatal accidents, equipment downtime, and loss of life. Adequate quality is of high importance in high-risk industries such as sea-going vessels and offshore installations in which third party quality assurance and product control play an important essential role in ensuring manufacturing quality of critical components. Classification societies play a vital role in mitigating risk in these industries by making sure that all the stakeholders i.e. manufacturers, builders, and end users are provided with adequate rules and standards that effectively ensures components produced at a high level of quality based on the area of application and risk of its failure. Quality issues have also been linked to the lack of competence or negligence of stakeholders in supply value chain. However, continued actions and regulatory reforms through modernization of rules and requirements has provided additional tools for purchasers and manufacturers to confront these issues. Included among these tools are updated ‘approval of manufacturer class programs’ aimed at developing and implementing a set of standardized manufacturing quality metrics for use by the manufacturer and verified by the classification society. The establishment and collection of manufacturing and testing requirements described in these programs could provide various stakeholders – from industry to vessel owners – with greater insight into the state of quality at a given manufacturing facility, and allow stakeholders to anticipate better and address quality issues while simultaneously reducing unnecessary failures that are costly to the industry. The publication introduces, explains and discusses critical manufacturing and testing requirements set in a leading class society’s approval of manufacturer regime and its rationale and some case studies.

Keywords: classification society, manufacturing, materials processing, materials testing, quality control

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: H. M. Ferreira, H. Cockings, D. F. Gordon

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Climate change is driving a transition in the energy sector, with low-carbon energy sources such as hydrogen (H2) emerging as an alternative to fossil fuels. However, the successful implementation of a hydrogen economy requires an expansion of hydrogen production, transportation and storage capacity. The costs associated with this transition are high but can be partly mitigated by adapting the current oil and natural gas networks, such as pipeline, an important component of the hydrogen infrastructure, to transport pure or blended hydrogen. Steel pipelines are designed to withstand fatigue, one of the most common causes of pipeline failure. However, it is well established that some materials, such as steel, can fail prematurely in service when exposed to hydrogen-rich environments. Therefore, it is imperative to evaluate how defects (e.g. inclusions, dents, and pre-existing cracks) will interact with hydrogen under cyclic loading and, ultimately, to what extent hydrogen induced failure will limit the service conditions of steel pipelines. This presentation will explore how the exposure of API 5L X65 to a hydrogen-rich environment and cyclic loads will influence its susceptibility to hydrogen induced failure. That evaluation will be performed by a combination of several techniques such as hydrogen permeation testing (ISO 17081:2014), fatigue crack growth (FCG) testing (ISO 12108:2018 and AFGROW modelling), combined with microstructural and fractographic analysis. The development of a FCG test setup coupled with an electrochemical cell will be discussed, along with the advantages and challenges of measuring crack growth rates in electrolytic hydrogen environments. A detailed assessment of several electrolytic charging conditions will also be presented, using hydrogen permeation testing as a method to correlate the different charging settings to equivalent hydrogen concentrations and effective diffusivity coefficients, not only on the base material but also on the heat affected zone and weld of the pipelines. The experimental work is being complemented with AFGROW, a useful FCG modelling software that has helped inform testing parameters and which will also be developed to ultimately help industry experts perform structural integrity analysis and remnant life characterisation of pipeline steels under representative conditions. The results from this research will allow to conclude if there is an acceleration of the crack growth rate of API 5L X65 under the influence of a hydrogen-rich environment, an important aspect that needs to be rectified instandards and codes of practice on pipeline integrity evaluation and maintenance.

Keywords: AFGROW, electrolytic hydrogen charging, fatigue crack growth, hydrogen, pipeline, steel

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Authors: Lewis Wallace, William Dempster, David Nash, Alexandros Boukis, Craig Maclean

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This paper, through traditional test methods and close adherence to international standards, presents a characterization study of a woven Polyethylene Terephthalate (PET). Testing is undergone in the axial, shear, and out-of-plane (bend) directions, and the results are fitted to the *FABRIC material model with ABAQUS FEA. The non-linear behaviors of the fabric in the axial and shear directions and behaviors on the macro scale are explored at the meso scale level. The medical grade bio-fabric is tested in untreated and heat-treated forms, and deviations are closely analyzed at the micro, meso, and macro scales to determine the effects of the process. The heat-treatment process was found to increase the stiffness of the fabric during axial and bending stiffness testing but had a negligible effect on the shear response. The ability of *FABRIC to capture behaviors unique to fabric deformation is discussed, whereby the unique phenomenological input can accurately represent the experimentally derived inputs.

Keywords: experimental techniques, FEA modelling, materials characterization, post-processing techniques

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Authors: Kehinde Adeyeye Adelabu

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Computer applications has completely revolutionized the way of life of people which does not exclude the field of sport education. There are computer technologies which help to enhance teaching in every field of education. Invention of computers has done great to the field of education. This study was therefore carried out to examine the effects and merits of computer operations in Human Kinetics Education and Sports. The study was able to identify the component of computer, uses of computer in Human Kinetics education (sports), computer applications in some branches of human kinetics education. A qualitative research method was employed by the author in gathering experts’ views and used to analyze the effects and merits of computer applications in the field of human kinetics education. No experiment was performed in the cause of carrying out the study. The source of information for the study was text-books, journal, articles, past project reports, internet i.e. Google search engine. Computer has significantly helped to improve Education (Human Kinetic), it has complemented the basic physical fitness testing and gave a more scientific basis to the testing. The use of the software and packages has made cost projections, database applications, inventory control, management of events, word processing, electronic mailing and record keeping easier than the pasts.

Keywords: application, computer operation, education, human kinetics

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Authors: Chunyang Miao, Bingxin Li, Shanglong Ning, Christopher J. B. Ford

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While it is challenging to fabricate electronic devices close to atomic dimensions in conventional top-down lithography, molecular electronics is promising to help maintain the exponential increase in component densities via using molecular building blocks to fabricate electronic components from the bottom up. It offers smaller, faster, and more energy-efficient electronic and photonic systems. A self-assembled monolayer (SAM) of molecules is a layer of molecules that self-assembles on a substrate. They are mechanically flexible, optically transparent, low-cost, and easy to fabricate. A large-area multi-layer structure has been designed and investigated by the team, where a SAM of designed molecules is sandwiched between graphene and gold electrodes. Each molecule can act as a quantum dot, with all molecules conducting in parallel. When a source-drain bias is applied, significant current flows only if a molecular orbital (HOMO or LUMO) lies within the source-drain energy window. If electrons tunnel sequentially on and off the molecule, the charge on the molecule is well-defined and the finite charging energy causes Coulomb blockade of transport until the molecular orbital comes within the energy window. This produces ‘Coulomb diamonds’ in the conductance vs source-drain and gate voltages. For different tunnel barriers at either end of the molecule, it is harder for electrons to tunnel out of the dot than in (or vice versa), resulting in the accumulation of two or more charges and a ‘Coulomb staircase’ in the current vs voltage. This nanostructure exhibits highly reproducible Coulomb-staircase patterns, together with additional oscillations, which are believed to be attributed to molecular vibrations. Molecules are more isolated than semiconductor dots, and so have a discrete phonon spectrum. When tunnelling into or out of a molecule, one or more vibronic states can be excited in the molecule, providing additional transport channels and resulting in additional peaks in the conductance. For useful molecular electronic devices, achieving the optimum orbital alignment of molecules to the Fermi energy in the leads is essential. To explore it, a drop of ionic liquid is employed on top of the graphene to establish an electric field at the graphene, which screens poorly, gating the molecules underneath. Results for various molecules with different alignments of Fermi energy to HOMO have shown highly reproducible Coulomb-diamond patterns, which agree reasonably with DFT calculations. In summary, this large-area SAM molecular junction is a promising candidate for future electronic circuits. (1) The small size (1-10nm) of the molecules and good flexibility of the SAM lead to the scalable assembly of ultra-high densities of functional molecules, with advantages in cost, efficiency, and power dissipation. (2) The contacting technique using graphene enables mass fabrication. (3) Its well-observed Coulomb blockade behaviour, narrow molecular resonances, and well-resolved vibronic states offer good tuneability for various functionalities, such as switches, thermoelectric generators, and memristors, etc.

Keywords: molecular electronics, Coulomb blokade, electron-phonon coupling, self-assembled monolayer

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Authors: Min Hae Song, Jooyong Park

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Even though assessment using information and communication technology will most likely lead the future of educational assessment, there is little research on this topic. Computerized assessment will not only cut costs but also measure students' performance in ways not possible before. In this context, this study introduces a tool which can overcome the problems of multiple choice tests. Multiple-choice tests (MC) are efficient in automatic grading, however structural problems of multiple-choice tests allow students to find the correct answer from options even though they do not know the answer. A computerized modified multiple-choice testing system (CMMT) was developed using the interactivity of computers, that presents questions first, and options later for a short time when the student requests for them. This study was conducted to find out whether penalizing for wrong answers in CMMT could lower random guessing. In this study, we checked whether students knew the answers by having them respond to the short-answer tests before choosing the given options in CMMT or MC format. Ninety-four students were tested with the directions that they will be penalized for wrong answers, but not for no response. There were 4 experimental conditions: two conditions of high or low percentage of penalizing, each in traditional multiple-choice or CMMT format. In the low penalty condition, the penalty rate was the probability of getting the correct answer by random guessing. In the high penalty condition, students were penalized at twice the percentage of the low penalty condition. The results showed that the number of no response was significantly higher for the CMMT format and the number of random guesses was significantly lower for the CMMT format. There were no significant between the two penalty conditions. This result may be due to the fact that the actual score difference between the two conditions was too small. In the discussion, the possibility of applying CMMT format tests while penalizing wrong answers in actual testing settings was addressed.

Keywords: computerized modified multiple choice test format, multiple-choice test format, penalizing, test format

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Authors: Pierre Kancir, Jean-Philippe Diguet, Marc Sevaux

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One of the main difficulties in developing multi-robot systems (MRS) is related to the simulation and testing tools available. Indeed, if the differences between simulations and real robots are too significant, the transition from the simulation to the robot won’t be possible without another long development phase and won’t permit to validate the simulation. Moreover, the testing of different algorithmic solutions or modifications of robots requires a strong knowledge of current tools and a significant development time. Therefore, the availability of tools for MRS, mainly with flying drones, is crucial to enable the industrial emergence of these systems. This research aims to present the most commonly used tools for MRS simulations and their main shortcomings and presents complementary tools to improve the productivity of designers in the development of multi-vehicle solutions focused on a fast learning curve and rapid transition from simulations to real usage. The proposed contributions are based on existing open source tools as Gazebo simulator combined with ROS (Robot Operating System) and the open-source multi-platform autopilot ArduPilot to bring them to a broad audience.

Keywords: ROS, ArduPilot, MRS, simulation, drones, Gazebo

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Authors: Alexandra Sargent, Sarah Ferris, Ioannis Theofanous

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The Abbott RealTime High Risk HPV test (RealTime HPV) is one of five assays clinically validated and approved by the English NHS Cervical Screening Programme (CSP) for HPV triage of low grade dyskaryosis and test-of-cure of treated Cervical Intraepithelial Neoplasia. The assay is a highly automated multiplex real-time PCR test for detecting 14 high risk (hr) HPV types, with simultaneous differentiation of HPV 16 and HPV 18 versus non-HPV 16/18 hrHPV. An endogenous internal control ensures sample cellularity, controls extraction efficiency and PCR inhibition. The original cervical specimen collected in SurePath (SP) liquid-based cytology (LBC) medium (BD Diagnostics) and the SP post-gradient cell pellets (SPG) after cytological processing are both CE marked for testing with the RealTime HPV test. During the 2011 NHSCSP validation of new tests only the original aliquot of SP LBC medium was investigated. Residual sample volume left after cytology slide preparation is low and may not always have sufficient volume for repeat HPV testing or for testing of other biomarkers that may be implemented in testing algorithms in the future. The SPG samples, however, have sufficient volumes to carry out additional testing and necessary laboratory validation procedures. This study investigates the correlation of RealTime HPV results of cervical specimens collected in SP LBC medium from women with low grade cytological abnormalities observed with matched pairs of original SP LBC medium and SP post-gradient cell pellets (SPG) after cytology processing. Matched pairs of SP and SPG samples from 750 women with borderline (N = 392) and mild (N = 351) cytology were available for this study. Both specimen types were processed and parallel tested for the presence of hrHPV with RealTime HPV according to the manufacturer´s instructions. HrHPV detection rates and concordance between test results from matched SP and SPGCP pairs were calculated. A total of 743 matched pairs with valid test results on both sample types were available for analysis. An overall-agreement of hrHPV test results of 97.5% (k: 0.95) was found with matched SP/SPG pairs and slightly lower concordance (96.9%; k: 0.94) was observed on 392 pairs from women with borderline cytology compared to 351 pairs from women with mild cytology (98.0%; k: 0.95). Partial typing results were highly concordant in matched SP/SPG pairs for HPV 16 (99.1%), HPV 18 (99.7%) and non-HPV16/18 hrHPV (97.0%), respectively. 19 matched pairs were found with discrepant results: 9 from women with borderline cytology and 4 from women with mild cytology were negative on SPG and positive on SP; 3 from women with borderline cytology and 3 from women with mild cytology were negative on SP and positive on SPG. Excellent correlation of hrHPV DNA test results was found between matched pairs of SP original fluid and post-gradient cell pellets from women with low grade cytological abnormalities tested with the Abbott RealTime High-Risk HPV assay, demonstrating robust performance of the test with both specimen types and reassuring the utility of the assay for cytology triage with both specimen types.

Keywords: Abbott realtime test, HPV, SurePath liquid based cytology, surepath post-gradient cell pellet

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Authors: John Olav Bjornestad, Bjorn Tore Johansen

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The number of people suffering from mental illnesses is increasing, and such illness is currently one of the major causes of disability and poor health. The reason for this is most likely a lack of physical activity. The purpose of this study was to discover if physical activity was an effective mode of treatment for psychiatric patients at an out-patient treatment facility. The study included an exploration of whether or not patients having physical activity included as an integral part of their treatment (to a greater degree than do patients who are physically inactive) would achieve 1) an improvement in their physical condition 2) a reduction in symptomatic pressure and 3) an increase in their health-related quality of life. The intervention period lasted a total of 12 weeks. The training group completed a minimum of 2 training sessions per week with an intensity of 60-75% of maximum heart rate. The participants’ health-related quality of life (SF-36), symptomatic pressure (SCL-90-R) and physical condition (UKK-walking test) were measured before and after intervention. Twenty participants were pre-tested, and out of this initial group, nine patients completed the intervention program and participated thereafter in post-testing. The results showed that participants on average improved their physical condition, reduced their symptomatic pressure and increased their health-related quality of life over the course of the intervention period. The training group experienced significant changes in their symptomatic pressure (the anxiety dimension) and health-related quality of life (the mental health dimension) from the pre-testing stage to the post-testing one. Furthermore, there was a significant connection between symptomatic pressure and health-related quality of life. The patients who were admitted to the psychiatric out-patient clinic were in a physical condition that was significantly poorer than that of persons of the same age in the remainder of the population. Experiences from the study and the relatively large defection from it demonstrate that there is a great need for close follow-up of psychiatric patients’ physical activity levels when physical activity and lifestyle changes are included as part of their treatment program.

Keywords: health-related quality, mental health, physical activity, physical condition

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Authors: Kholil Kholil, Soecahyadi Soecahyadi

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Geographically, Padang Panjang Regency which located in the heart of Western Sumatra has great potentials for the tourism industry. However, these potentials have not been strategically developed for increasing local economic development and people's welfare. The purpose of this research is to design the strategy of sustainable tourism area development using Strategic Assumption Surfacing and Testing (SAST) and Exponential Rank Method (ERM). Result study showed, there are four aspects which importance and certainly for developing tourism area destination in Padang Panjang Regency; (1) tourist information center and promotion, (2) regional cooperation development; (3) minangese center as a center of excellence; and (4) building the center of the public market. To build an attractive tourist area required action plan includes the construction of an information center, center of excellence of minangese, and tourist infrastructure; and public participation is a key success factor for ensuring sustainability of tourism development in Padang Panjang Regency.

Keywords: local economic development, tourism attraction, SAST, ERM

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Authors: Muneeb Ahmad, Ali Raza

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A computational method inspired by the immune system (IS) is presented, leveraging its shared characteristics of robustness, fault tolerance, scalability, and adaptability with swarm intelligence. This method aims to showcase flocking behaviors in a swarm of robots (SR). The innate part of the IS offers a variety of reactive and probabilistic cell functions alongside its self-regulation mechanism which have been translated to enable swarming behaviors. Although, the research is specially focused on flocking behaviors in a variety of simulated environments using e-puck robots in a physics-based simulator (CoppeliaSim); the artificial innate immune system (AIIS) can exhibit other swarm behaviors as well. The effectiveness of the immuno-inspired approach has been established with extensive experimentations, for scalability and adaptability, using standard swarm benchmarks as well as the immunological regulatory functions (i.e., Dendritic Cells’ Maturity and Inflammation). The AIIS-based approach has proved to be a scalable and adaptive solution for emulating the flocking behavior of SR.

Keywords: artificial innate immune system, flocking swarm, immune system, swarm intelligence

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Authors: Arturo Daag

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The Philippine Institute of Volcanology and Seismology (PHIVOLCS) is enhancing its liquefaction hazard map towards a detailed probabilistic approach using SDS and geophysical data. Target sites for liquefaction assessment are public schools in Metro Manila. Since target sites are in highly urbanized-setting, the objective of the project is to conduct both non-destructive geotechnical studies using Screw Driving Testing (SDFS) combined with geophysical data such as refraction microtremor array (ReMi), 3 component microtremor Horizontal to Vertical Spectral Ratio (HVSR), and ground penetrating RADAR (GPR). Initial test data was conducted in liquefaction impacted areas from the Mw 6.1 earthquake in Central Luzon last April 22, 2019 Province of Pampanga. Numerous accounts of liquefaction events were documented areas underlain by quaternary alluvium and mostly covered by recent lahar deposits. SDS estimated values showed a good correlation to actual SPT values obtained from available borehole data. Thus, confirming that SDS can be an alternative tool for liquefaction assessment and more efficient in terms of cost and time compared to SPT and CPT. Conducting borehole may limit its access in highly urbanized areas. In order to extend or extrapolate the SPT borehole data, non-destructive geophysical equipment was used. A 3-component microtremor obtains a subsurface velocity model in 1-D seismic shear wave velocity of the upper 30 meters of the profile (Vs30). For the ReMi, 12 geophone array with 6 to 8-meter spacing surveys were conducted. Microtremor data were computed through the Factor of Safety, which is the quotient of Cyclic Resistance Ratio (CRR) and Cyclic Stress Ratio (CSR). Complementary GPR was used to study the subsurface structure and used to inferred subsurface structures and groundwater conditions.

Keywords: screw drive testing, microtremor, ground penetrating RADAR, liquefaction

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Authors: Harish Aryal, Roger Hague, Daniel Sotelo, Felipe Astete Salinas

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This paper presents a comparative study of different coolants, materials, and temperatures that can affect the effectiveness of heat exchangers that are used in small modular reactors. The corrugated plate heat exchangers were chosen out of different plate options for testing purposes because of their ease of access and better performance than other existing heat exchangers in recent years. SolidWorks enables us to see various results between water coolants and helium coolants acting upon different types of conducting metals, which were selected from different fluids that ultimately satisfied accessibility requirements and were compatible with the software. Though not every element, material, fluid, or method was used in the testing phase, their purpose is to help further research that is to come since the innovation of nuclear power is the future. The tests that were performed are to help better understand the constant necessities that are seen in heat exchangers and through every adjustment see what the breaking points or improvements in the machine are. Depending on consumers and researchers, the results may give further feedback as to show why different types of materials and fluids would be preferred and why it is necessary to keep failures to improve future research.

Keywords: heat exchangers, Solidworks, coolants, small modular reactors, nuclear power, nanofluids, Nusselt number, friction factor, Reynolds number

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Authors: Kate E Morris, Mark Sumner, Mark Taylor, Amanda Joynes, Yue Guo

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Garment durability, which encompasses physical and emotional factors, has been identified as a critical ingredient in producing clothing with increased lifespans, battling overconsumption, and subsequently tackling the catastrophic effects of climate change. Eco-design for Sustainable Products Regulation (ESPR) and Extended Producer Responsibility (EPR) schemes have been suggested and will be implemented across Europe and the UK which might require brands to declare a garment’s durability credentials to be able to sell in that market. There is currently no consistent method of measuring the overall durability of a garment. Measuring the physical durability of garments is difficult and current assessment methods lack objectivity and reliability or don’t reflect the complex nature of durability for different garment categories. This study presents a novel and reproducible methodology for testing and ranking the absolute durability of 5 commercially available garment types, Formal Trousers, Casual Trousers, Denim Jeans, Casual Leggings and Underwear. A total of 112 garments from 21 UK brands were assessed. Due to variations in end use, different factors were considered across the different garment categories when evaluating durability. A physical testing protocol was created, tailored to each category, to dictate the necessary test results needed to measure the absolute durability of the garments. Multiple durability factors were used to modulate the ranking as opposed to previous studies which only reported on single factors to evaluate durability. The garments in this study were donated by the signatories of the Waste Resource Action Programme’s (WRAP) Textile 2030 initiative as part of their strategy to reduce the environmental impact of UK fashion. This methodology presents a consistent system for brands and policymakers to follow to measure and rank various garment type’s physical durability. Furthermore, with such a methodology, the durability of garments can be measured and new standards for improving durability can be created to enhance utilisation and improve the sustainability of the clothing on the market.

Keywords: circularity, durability, garment testing, ranking

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Authors: Belalia Douma Omar, Bakhta Boukhatem, Mohamed Ghrici

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Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, super plasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.

Keywords: self-compacting concrete, fly ash, strength prediction, fuzzy logic

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Authors: Mohammad I. Hossain, Omar F. Hamim

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This paper presents a case study on a pile integrity test for assessing the integrity of piles as well as a physical dimension (e.g., cross-sectional area, length), continuity, and consistency of the pile materials. The recent boom in the socio-economic condition of Bangladesh has given rise to the building of high-rise commercial and residential infrastructures. The advantage of the pile integrity test lies in the fact that it is possible to get an approximate indication regarding the quality of the sub-structure before commencing the construction of the super-structure. This paper aims at providing a classification of cast-in-situ piles based on characteristic reflectograms obtained using the Sonic Integrity Testing program for the sub-soil condition of Narayanganj, Bangladesh. The piles have been classified as 'Pile Type-1', 'Pile Type-2', 'Pile Type-3', 'Pile type-4', 'Pile Type-5' or 'Pile Type-6' from the visual observations of reflections from the generated stress waves by striking the pile head with a handheld hammer. With respect to construction quality and integrity, piles have been further classified into three distinct categories, i.e., satisfactory, may be satisfactory, and unsatisfactory.

Keywords: cast-in-situ piles, characteristic reflectograms, pile integrity test, sonic integrity testing program

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Authors: Yong Xue, Daniel A. Menascé

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Automated and end-to-end network resource management and provisioning for virtual service networks in a multiple autonomous systems (a.k.a multi-AS) environment is a challenging and open problem. This paper proposes a novel, scalable and interoperable high-level architecture that incorporates a number of emerging enabling technologies including Software Defined Network (SDN), Network Function Virtualization (NFV), Service Oriented Architecture (SOA), and Autonomic Computing. The proposed architecture can be used to not only automate network resource management and provisioning for virtual service networks across multiple autonomous substrate networks, but also provide an adaptive capability for achieving optimal network resource management and maintaining network-level end-to-end network performance as well. The paper argues that this SDN and autonomic computing based architecture lays a solid foundation that can facilitate the development of the future Internet based on the pluralistic paradigm.

Keywords: virtual network, software defined network, virtual service network, adaptive resource management, SOA, multi-AS, inter-domain

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: Alexander Musyoki, Collins Odour

Abstract:

Over the past few years, the bakery industry in Kenya has experienced significant growth largely in part to the increased adoption of technology and automation in their processes; more specifically due to the adoption of bakery management systems to help in running bakeries. While they have been largely responsible for the improved productivity and efficiency in bakeries, most of them are now outdated and pose more challenges than benefits. The proposed online bakery management system mentioned in this paper aims to address this by allowing bakery owners to track inventory, budget, job progress, and data analytics on each job and in doing so, promote the Sustainable Development Goals 3 and 12, which aim to ensure healthy lives and promote sustainable economic growth as the proposed benefits of these features include scalability, easy accessibility, reduced acquisition costs, better reliability, and improved functionality that will allow bakeries to become more competitive, reduce waste and track inventory more efficiently. To better understand the challenges, a comprehensive study has been performed to assess these traditional systems and try to understand if an online bakery management system can prove to be advantageous to bakery owners. The study conducted gathered feedback from bakery owners and employees in Nairobi County, Kenya using an online survey with a response rate of about 86% from the target population. The responses cited complex and hard to use bakery management systems (59.7%), lack of portability from one device to the other (58.1%) and high acquisition costs (51.6%) as the top challenges of traditional bakery management systems. On the other hand, some of the top benefits that most of the respondents would realize from the online bakery management system was better reliability (58.1%) and reduced acquisition costs (58.1%). Overall, the findings suggest that an online bakery management system has a lot of advantages over traditional systems and is likely to be well-received in the market. In conclusion, the proposed online bakery management system has the potential to improve the efficiency and competitiveness of small-sized bakeries in Nairobi County. Further research is recommended to expand the sample size and diversity of respondents and to conduct more in-depth analyses of the data collected.

Keywords: ICT, technology and automation, bakery management systems, food innovation

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: moving object detection, histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine

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Authors: Virender Singh Gurau, Akash Deep, Sarbjot S. Sandhu

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Vegetable oils are produced from numerous oil seed crops. While all vegetable oils have high energy content, most require some processing to assure safe use in internal combustion engines. Some of these oils already have been evaluated as substitutes for diesel fuels. In the present research work Bitter Apricot kernel oil was employed as a feedstock for the production of biodiesel. The physicochemical properties of the Bitter Apricot kernel oil methyl ester were investigated as per ASTM D6751. From the series of engine testing, it is concluded that the brake thermal efficiency (BTE) with biodiesel blend was little lower than that of diesel. BSEC is slightly higher for Bitter apricot kernel oil methyl ester blends than neat diesel. For biodiesel blends, CO emission was lower than diesel fuel as B 20 reduced CO emissions by 18.75%. Approximately 11% increase in NOx emission was observed with 20% biodiesel blend. It is observed that HC emissions tend to decrease for biodiesel based fuels and Smoke opacity was found lower for biodiesel blends in comparison to diesel fuel.

Keywords: biodiesel, transesterification, bitter apricot kernel oil, performance and emission testing

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Authors: Mayank Sharma, Anubhaw Kumar, Siddharth Desai, Ankit Tomar

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With the advent of cost-effective hardware and communication technologies, the scope of digitalising operations within a supply chain has tremendously increased. This has provided the opportunity to create digital twins of entire supply chains through the use of Internet-of-Things (IoT) and communication technologies. Adverse events like the COVID-19 pandemic and unpredictable geo-political situations have further warranted the importance of digitalization and remote operability of day-to-day operations at critical nodes. Globalisation, rising consumerism & e-commerce has exponentially increased the complexities of existing supply chains. We discuss here a scalable, future-ready and inclusive framework for creating digital twins developed along with the industry leaders from Cisco, Bosch, Accenture, Intel, Deloitte & IBM. We have proposed field-tested key technologies and frameworks required for creating digital twins. We also present case studies of real-life stable deployments done by us in the supply chains of a few marquee industry leaders.

Keywords: internet-of-things, digital twins, smart factory, industry 4.0, smart manufacturing

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Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

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Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

Procedia PDF Downloads 341