Search results for: smart camera networks

Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

Procedia PDF Downloads 86

Authors: Kuei-Chun Liu, Yu-Yu Lai, Ching-Hong Wu, Hsiao-Han Huang

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The number of Android applications (Apps) has increased rapidly in recent years. In order to get better programmatic control over Apps, we designed a record-and-replay mechanism to record Android input events and accessibility service events then make shortcuts. The shortcut is useful for complicated routine works and to Android beginners. We also generated graphical user interface (GUI) API by these shortcuts. GUI API helps developers make integrated Apps which can control other third-party Apps even if the official API is not offered by their providers. We demonstrated the usage of GUI API with two integrated Apps: Universal Bank App and Universal Communication App. Universal Bank App integrates three accounts from different banks and Universal Communication App integrates Line with WhatsApp. Both of them show the advantage of extendable GUI API. Furthermore, using our mechanism, shortcuts could replay almost all of the Top-100 Apps on Google Play correctly. In sum, the approach we present can help both Android developers and general users.

Keywords: graphical user interface, GUI API, record-and-replay, third-party apps

Procedia PDF Downloads 407

Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

Procedia PDF Downloads 224

Authors: G. Santamato, M. Solazzi, A. Frisoli

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Systems for detection of damages in railway pantographs effectively reduce the cost of maintenance and improve time scheduling. In this paper, we present an approach to design a monitoring tool fitting strong customer requirements such as portability and ease of use. Pantograph has been modeled to estimate its dynamical properties, since no data are available. With the aim to focus on suspensions health, a two Degrees of Freedom (DOF) scheme has been adopted. Parameters have been calculated by means of analytical dynamics. A Finite Element Method (FEM) modal analysis verified the former model with an acceptable error. The detection strategy seeks phase-plots topology alteration, induced by defects. In order to test the suitability of the method, leakage in the dashpot was simulated on the lumped model. Results are interesting because changes in phase plots are more appreciable than frequency-shift. Further calculations as well as experimental tests will support future developments of this smart strategy.

Keywords: pantograph models, phase plots, structural health monitoring, damage detection

Procedia PDF Downloads 362

Authors: Hosuk Shin, Young-Hyun Seo, Eunhak Lee, Seung-Young Kho

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Currently, in Seoul, users have the privilege to avoid riding crowded buses with the installation of Bus Information System (BIS). BIS has three levels of on-board bus ridership level information (spacious, normal, and crowded). However, there are flaws in the system due to it being real time which could provide incomplete information to the user. For example, a bus comes to the station, and on the BIS it shows that the bus is crowded, but on the stop that the user is waiting many people get off, which would mean that this station the information should show as normal or spacious. To fix this problem, this study predicts the bus ridership level using smart card data to provide more accurate information about the passenger ridership level on the bus. An Artificial Neural Network (ANN) is an interconnected group of nodes, that was created based on the human brain. Forecasting has been one of the major applications of ANN due to the data-driven self-adaptive methods of the algorithm itself. According to the results, the ANN algorithm was stable and robust with somewhat small error ratio, so the results were rational and reasonable.

Keywords: smartcard data, ANN, bus, ridership

Procedia PDF Downloads 167

Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

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In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

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Authors: Arezou Javadi

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The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 88

Authors: Arezou Javadi

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The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

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Authors: Emma J. Dale, Christina D. Buesching, Kevin R. Theis, David W. Macdonald

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This study investigates the oral and intestinal microbiomes of wild-living European badgers (Meles meles) and will relate inter-individual differences to social contact networks, somatic and reproductive fitness, varying susceptibility to bovine tuberculous (bTB) and to the olfactory advertisement. Badgers are an interesting model for this research, as they have great variation in body condition, despite living in complex social networks and having access to the same resources. This variation in somatic fitness, in turn, affects breeding success, particularly in females. We postulate that microbiota have a central role to play in determining the successfulness of an individual. Our preliminary results, characterising the microbiota of individual badgers, indicate unique compositions of microbiota communities within social groups of badgers. This basal information will inform further questions related to the extent microbiota influence fitness. Hitherto, the potential role of microbiota has not been considered in determining host condition, but also other key fitness variables, namely; communication and resistance to disease. Badgers deposit their faeces in communal latrines, which play an important role in olfactory communication. Odour profiles of anal and subcaudal gland secretions are highly individual-specific and encode information about group-membership and fitness-relevant parameters, and their chemical composition is strongly dependent on symbiotic microbiota. As badgers sniff/ lick (using their Vomeronasal organ) and over-mark faecal deposits of conspecifics, these microbial communities can be expected to vary with social contact networks. However, this is particularly important in the context of bTB, where badgers are assumed to transmit bTB to cattle as well as conspecifics. Interestingly, we have found that some individuals are more susceptible to bTB than are others. As acquired immunity and thus potential susceptibility to infectious diseases are known to depend also on symbiotic microbiota in other members of the mustelids, a role of particularly oral microbiota can currently not be ruled out as a potential explanation for inter-individual differences in infection susceptibility of bTB in badgers. Tri annually badgers are caught in the context of a long-term population study that began in 1987. As all badgers receive an individual tattoo upon first capture, age, natal as well as previous and current social group-membership and other life history parameters are known for all animals. Swabs (subcaudal ‘scent gland’, anal, genital, nose, mouth and ear) and fecal samples will be taken from all individuals, stored at -80oC until processing. Microbial samples will be processed and identified at Wayne State University’s Theis (Host-Microbe Interactions) Lab, using High Throughput Sequencing (16S rRNA-encoding gene amplification and sequencing). Acknowledgments: Gas-Chromatography/ Mass-spectrometry (in the context of olfactory communication) analyses will be performed through an established collaboration with Dr. Veronica Tinnesand at Telemark University, Norway.

Keywords: communication, energetics, fitness, free-ranging animals, immunology

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Authors: C. Trapp, A. Vijay, M. Khorasani

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Decentralised micro-grids with sector coupling can combat the spatial and temporal intermittence of renewable energy by combining power, transportation and infrastructure sectors. Intelligent energy conversion concepts such as electrolysers, hydrogen engines and fuel cells combined with energy storage using intelligent batteries and hydrogen storage form the back-bone of such a system. This paper describes a micro-grid based on Photo-Voltaic cells, battery storage, innovative modular and scalable Anion Exchange Membrane (AEM) electrolyzer with an efficiency of up to 73%, high-pressure hydrogen storage as well as cutting-edge combustion-engine based Combined Heat and Power (CHP) plant with more than 85% efficiency at the university campus to address the challenges of decarbonization whilst eliminating the necessity for expensive high-voltage infrastructure.

Keywords: sector coupling, micro-grids, energy self-sufficiency, decarbonization, AEM electrolysis, hydrogen CHP

Procedia PDF Downloads 183

Authors: Iwan Cony Setiadi, Aulia M. T. Nasution

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The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of in-vivo skin chromophores by analyzing spectral data at each reflected image pixel. For ergonomic purpose, our multispectral imaging system is decomposed in two parts: a light source compartment based on LED with 11 different wavelenghts and a monochromatic 8-Bit CCD camera with C-Mount Objective Lens. The software based on GUI MATLAB to control the system was also developed. Our system provides 11 monoband images and is coupled with a software reconstructing hyperspectral cubes from these multispectral images. In this paper, we proposed a new method to build a hyperspectral reflectance cube based on artificial neural network algorithm. After preliminary corrections, a neural network is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure involves acquisition, by a spectrophotometer. This neural network is then used to retrieve a megapixel multispectral cube between 380 and 880 nm with a 5 nm resolution from a low-spectral-resolution multispectral acquisition. As hyperspectral cubes contain spectra for each pixel; comparison should be done between the theoretical values from the spectrophotometer and the reconstructed spectrum. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). To validate reconstruction, the set of 8 colour patches reconstructed by our MSI system and the one recorded by the spectrophotometer were compared. The average GFC was 0.9990 (standard deviation = 0.0010) and the average RMSE is 0.2167 (standard deviation = 0.064).

Keywords: multispectral imaging, reflectance cube, spectral reconstruction, artificial neural network

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Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

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Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

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Authors: Tamar Trop

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Bike sharing systems can be important elements of smart cities as they have the potential for impact on multiple levels. These systems can add a significant alternative to other modes of mass transit in cities that are continuously looking for measures to become more livable and maintain their attractiveness for citizens, businesses and tourism. Bike-sharing began in Europe in 1965, and a viable format emerged in the mid-2000s thanks to the introduction of information technology. The rate of growth in bike-sharing schemes and fleets has been very rapid since 2008 and has probably outstripped growth in every other form of urban transport. Today, public bike-sharing systems are available on five continents, including over 700 cities, operating more than 800,000 bicycles at approximately 40,000 docking stations. Since modern bike sharing systems have become prevalent only in the last decade, the existing literature analyzing these systems and their sustainability is relatively new. The purpose of the presented study is to assess the sustainability of these newly emerging transportation systems, by using the Envision™ rating system as a methodological framework and the Israeli 'Tel -O-Fun' – bike sharing project as a case study. The assessment was conducted by project team members. Envision™ is a new guidance and rating system used to assess and improve the sustainability of all types and sizes of infrastructure projects. This tool provides a holistic framework for evaluating and rating the community, environmental, and economic benefits of infrastructure projects over the course of their life cycle. This evaluation method has 60 sustainability criteria divided into five categories: Quality of life, leadership, resource allocation, natural world, and climate and risk. 'Tel -O-Fun' project was launched in Tel Aviv-Yafo on 2011 and today provides about 1,800 bikes for rent, at 180 rental stations across the city. The system is based on a complex computer terminal that is located in the docking stations. The highest-rated sustainable features that the project scored include: (a) Improving quality of life by: offering a low cost and efficient form of public transit, improving community mobility and access, enabling the flexibility of travel within a multimodal transportation system, saving commuters time and money, enhancing public health and reducing air and noise pollution; (b) improving resource allocation by: offering inexpensive and flexible last-mile connectivity, reducing space, materials and energy consumption, reducing wear and tear on public roads, and maximizing the utility of existing infrastructure, and (c) reducing of greenhouse gas emissions from transportation. Overall, 'Tel -O-Fun' project was highly scored as an environmentally sustainable and socially equitable infrastructure. The use of this practical framework for evaluation also yielded various interesting insights on the shortcoming of the system and the characteristics of good solutions. This can contribute to the improvement of the project and may assist planners and operators of bike sharing systems to develop a sustainable, efficient and reliable transportation infrastructure within smart cities.

Keywords: bike sharing, Envision™, sustainability rating system, sustainable infrastructure

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Authors: Xiaohui Zhao, Shahan Mafuz

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Context-aware technologies provide system applications with the awareness of environmental conditions, customer behaviour, object movements, etc. Further, with such capability system applications can be smart to adapt intelligently their responses to the changing conditions. Concerning business operations, this promises businesses that their business processes can run more intelligently, adaptively and flexibly, and thereby either improve customer experience, enhance reliability of service delivery, or lower operational cost, to make the business more competitive and sustainable. Aiming at realizing such context-aware business process management, this paper firstly explores its potential benefit and then identifies some gaps between the current business process management support and the expected. In addition, some preliminary solutions are also discussed with context definition, rule-based process execution, run-time process evolution, etc. A framework is also presented to give a conceptual architecture of context-aware business process management system to guide system implementation.

Keywords: business process adaptation, business process evolution, business process modelling, and context awareness

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Authors: Yang Xiao-Jun, Yu Tian-Hao, Hu Ying-Qi

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Breathing in foreign objects during the operation of the aircraft engine, impurities in the aircraft fuel and products of incomplete combustion can produce deposits on the surface of the turbine blades. These deposits reduce not only the turbine's operating efficiency but also the life of the turbine blades. Based on the small open wind tunnel, the simulation of deposits on the leading edge of the turbine has been carried out in this work. The effect of film cooling on particulate deposition was investigated. Based on the analysis, the adhesive mechanism for the molten pollutants’ reaching to the turbine surface was simulated by matching the Stokes number, TSP (a dimensionless number characterizing particle phase transition) and Biot number of the test facility and that of the real engine. The thickness distribution and growth trend of the deposits have been observed by high power microscope and infrared camera under different temperature of the main flow, the solidification temperature of the particulate objects, and the blowing ratio. The experimental results from the leading edge particulate deposition demonstrate that the thickness of the deposition increases with time until a quasi-stable thickness is reached, showing a striking effect of the blowing ratio on the deposition. Under different blowing ratios, there exists a large difference in the thickness distribution of the deposition, and the deposition is minimal at the specific blow ratio. In addition, the temperature of main flow and the solidification temperature of the particulate have a great influence on the deposition.

Keywords: deposition, experiment, film cooling, leading edge, paraffin particles

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Authors: Ahmet Erten, Adil Mustafa, Ayşenur Eser, Özlem Yalçın

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We present a new viscometer based on a microfluidic chip with elastic high aspect ratio micropillar arrays. The displacement of pillar tips in flow direction can be used to analyze viscosity of liquid. In our work, Computational Fluid Dynamics (CFD) is used to analyze pillar displacement of various micropillar array configurations in flow direction at different viscosities. Following CFD optimization, micro-CNC based rapid prototyping is used to fabricate molds for microfluidic chips. Microfluidic chips are fabricated out of polydimethylsiloxane (PDMS) using soft lithography methods with molds machined out of aluminum. Tip displacements of micropillar array (300 µm in diameter and 1400 µm in height) in flow direction are recorded using a microscope mounted camera, and the displacements are analyzed using image processing with an algorithm written in MATLAB. Experiments are performed with water-glycerol solutions mixed at 4 different ratios to attain 1 cP, 5 cP, 10 cP and 15 cP viscosities at room temperature. The prepared solutions are injected into the microfluidic chips using a syringe pump at flow rates from 10-100 mL / hr and the displacement versus flow rate is plotted for different viscosities. A displacement of around 1.5 µm was observed for 15 cP solution at 60 mL / hr while only a 1 µm displacement was observed for 10 cP solution. The presented viscometer design optimization is still in progress for better sensitivity and accuracy. Our microfluidic viscometer platform has potential for tailor made microfluidic chips to enable real time observation and control of viscosity changes in biological or chemical reactions.

Keywords: Computational Fluid Dynamics (CFD), high aspect ratio, micropillar array, viscometer

Procedia PDF Downloads 246

Authors: Rob van den Dam

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Today’s Internet of Things (IoT) comprises more than a billion intelligent devices, connected via wired/wireless communications. The expected proliferation of hundreds of billions more places us at the threshold of a transformation sweeping across the communications industry. Yet, we found that the IoT architecture and solutions that currently work for billions of devices won’t necessarily scale to tomorrow’s hundreds of billions of devices because of high cost, lack of privacy, not future-proof, lack of functional value and broken business models. As the IoT scales exponentially, decentralized networks have the potential to reduce infrastructure and maintenance costs to manufacturers. Decentralization also promises increased robustness by removing single points of failure that could exist in traditional centralized networks. By shifting the power in the network from the center to the edges, devices gain greater autonomy and can become points of transactions and economic value creation for owners and users. To validate the underlying technology vision, IBM jointly developed with Samsung Electronics the autonomous decentralized peer-to- peer proof-of-concept (PoC). The primary objective of this PoC was to establish a foundation on which to demonstrate several capabilities that are fundamental to building a decentralized IoT. Though many commercial systems in the future will exist as hybrid centralized-decentralized models, the PoC demonstrated a fully distributed proof. The PoC (a) validated the future vision for decentralized systems to extensively augment today’s centralized solutions, (b) demonstrated foundational IoT tasks without the use of centralized control, (c) proved that empowered devices can engage autonomously in marketplace transactions. The PoC opens the door for the communications and electronics industry to further explore the challenges and opportunities of potential hybrid models that can address the complexity and variety of requirements posed by the internet that continues to scale. Contents: (a) The new approach for an IoT that will be secure and scalable, (b) The three foundational technologies that are key for the future IoT, (c) The related business models and user experiences, (d) How such an IoT will create an 'Economy of Things', (e) The role of users, devices, and industries in the IoT future, (f) The winners in the IoT economy.

Keywords: IoT, internet, wired, wireless

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Authors: Fatemeh Karimi

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The fashion and textile industry is undergoing a profound transformation, with polymers playing an increasingly pivotal role in driving innovation and sustainability. This paper explores the application of polymers in fashion and textile engineering, focusing on their impact on material properties, sustainability, and the future of garment production. Polymers, both synthetic and bio-based, offer unique opportunities to enhance the performance, durability, and environmental footprint of textiles. By examining recent advancements in polymer science and their integration into fashion design and production, we provide insights into how these materials are reshaping the industry. This paper also discusses the challenges and opportunities associated with the use of polymers, particularly in the context of sustainable fashion and circular economy practices. Through case studies and industry examples, we highlight the innovative ways in which polymers are being utilized to meet the evolving demands of consumers and the industry's sustainability goals.

Keywords: polymer textiles, sustainable fashion, bio-based polymers, smart textiles, fashion innovation, circular economy, textile engineering

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Authors: Bercem Kiran-Yildirim, Volker Gaukel

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Ice recrystallization (IR) which occurs especially during frozen storage is an undesired process due to the possible influence on the quality of products. As a result of recrystallization, the total volume of ice remains constant, but the size, number, and shape of ice crystals change. For instance, as indicated in the literature, the size of ice crystals in ice cream increases due to recrystallization. This results in texture deterioration. Therefore, the inhibition of ice recrystallization is of great importance, not only for food industry but also for several other areas where sensitive products are stored frozen, like pharmaceutical products or organs and blood in medicine. Ice-binding proteins (IBPs) have the unique ability to inhibit ice growth and in consequence inhibit recrystallization. This effect is based on their ice binding affinity. In the presence of IBP in a solution, ice crystal growth is inhibited during temperature decrease until a certain temperature is reached. The melting during temperature increase is not influenced. The gap between melting and freezing points is known as thermal hysteresis (TH). In literature, the TH activity is usually investigated under laboratory conditions in IBP buffer solutions. In product applications (e.g., food) there are many other solutes present which may influence the TH activity. In this study, a subset of IBPs, so-called antifreeze proteins (AFPs), is used for the investigation of the influence of sucrose solution concentration on the TH activity. For the investigation, a polarization microscope (Nikon Eclipse LV100ND) equipped with a digital camera (Nikon DS-Ri1) and a cold stage (Linkam LTS420) was used. In a first step, the equipment was established and validated concerning the accuracy of TH measurements based on literature data.

Keywords: ice binding proteins, ice crystals, sucrose solution, thermal hysteresis

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Authors: George Kurian, Hongmei Chi

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Digital evidence plays a critical role in most legal investigations. In many cases, thumbnail databases show important information in that investigation. The probability of having digital evidence retrieved from a computer or smart device has increased, even though the previous user removed data and deleted apps on those devices. Due to the increase in digital forensics, the ability to store residual information from various thumbnail applications has improved. This paper will focus on investigating thumbnail information from Windows 10. Thumbnail images of interest in forensic investigations may be intact even when the original pictures have been deleted. It is our research goal to recover useful information from thumbnails. In this research project, we use various forensics tools to collect left thumbnail information from deleted videos or pictures. We examine and describe the various thumbnail sources in Windows and propose a methodology for thumbnail collection and analysis from laptops or desktops. A machine learning algorithm is adopted to help speed up content from thumbnail pictures.

Keywords: digital forensic, forensic tools, soundness, thumbnail, machine learning, OCR

Procedia PDF Downloads 132

Authors: Y. Zheng, M. Busi, A. F. Pedersen, M. A. Beltran, C. Gundlach

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X-ray phase contrast imaging has shown to yield a better contrast compared to conventional attenuation X-ray imaging, especially for soft tissues in the medical imaging energy range. This can potentially lead to better diagnosis for patients. However, phase contrast imaging has mainly been performed using highly brilliant Synchrotron radiation, as it requires high coherence X-rays. Many research teams have demonstrated that it is also feasible using a laboratory source, bringing it one step closer to clinical use. Nevertheless, the requirement of fine gratings and high precision stepping motors when using a laboratory source prevents it from being widely used. Recently, a random phase object has been proposed as an analyzer. This method requires a much less robust experimental setup. However, previous studies were done using a particular X-ray source (liquid-metal jet micro-focus source) or high precision motors for stepping. We have been working on a much simpler setup with just small modification of a commercial bench-top micro-CT (computed tomography) scanner, by introducing a piece of sandpaper as the phase analyzer in front of the X-ray source. However, it needs a suitable algorithm for speckle tracking and 3D reconstructions. The precision and sensitivity of speckle tracking algorithm determine the resolution of the system, while the 3D reconstruction algorithm will affect the minimum number of projections required, thus limiting the temporal resolution. As phase contrast imaging methods usually require much longer exposure time than traditional absorption based X-ray imaging technologies, a dynamic phase contrast micro-CT with a high temporal resolution is particularly challenging. Different reconstruction methods, including neural network based techniques, will be evaluated in this project to increase the temporal resolution of the phase contrast micro-CT. A Monte Carlo ray tracing simulation (McXtrace) was used to generate a large dataset to train the neural network, in order to address the issue that neural networks require large amount of training data to get high-quality reconstructions.

Keywords: micro-ct, neural networks, reconstruction, speckle-based x-ray phase contrast

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Authors: Song Zhang, Hui Wang, Johannes Henrich Schleifenbaum

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Due to the increasing demand for quality assurance and reliability for additive manufacturing, the development of an advanced in-situ monitoring system is required to monitor the process anomalies as input for further process control. Optical-based monitoring systems, such as CMOS cameras and NIR cameras, are proved as effective ways to monitor the geometrical distortion and exceptional thermal distribution. Therefore, many studies and applications are focusing on the availability of the optical-based monitoring system for detecting varied types of defects. However, the capability of the monitoring setup is not quantified. In this study, a quantification model to evaluate the capability of the monitoring setups for the LPBF machine based on acquired monitoring data of a designed test artifact is presented, while the design of the relevant test artifacts is discussed. The monitoring setup is evaluated based on its hardware properties, location of the integration, and light condition. Methodology of data processing to quantify the capacity for each aspect is discussed. The minimal capability of the detectable size of the monitoring set up in the application is estimated by quantifying its resolution and accuracy. The quantification model is validated using a CCD camera-based monitoring system for LPBF machines in the laboratory with different setups. The result shows the model to quantify the monitoring system's performance, which makes the evaluation of monitoring systems with the same concept but different setups possible for the LPBF process and provides the direction to improve the setups.

Keywords: data processing, in-situ monitoring, LPBF process, optical system, quantization model, test artifact

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Authors: Thanasis K. Barlas, Helge A. Madsen

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A novel Active Flap System (AFS) has been developed at DTU Wind Energy, as a result of a 3-year R\&D project following almost 10 years of innovative research in this field. The full-scale AFS comprises an active deformable trailing edge has been tested at the unique rotating test facility at the Risoe Campus of DTU Wind Energy in Denmark. The design and instrumentation of the wing section and the active flap system (AFS) are described. The general description and objectives of the rotating test rig at the Risoe campus of DTU are presented, as used for the aeroelastic testing of the AFS in the recently finalized INDUFLAP project. The general description and objectives are presented, along with an overview of sensors on the setup and the test cases. The post-processing of data is discussed and results of steady flap step and azimuth control flap cases are presented.

Keywords: morphing, adaptive, flap, smart blade, wind turbine

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Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

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Authors: Faraji Sepideh

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Nowadays, purchase rate of the smart device is increasing and user authentication is one of the important issues in information security. Alphanumeric strong passwords are difficult to memorize and also owners write them down on papers or save them in a computer file. In addition, text password has its own flaws and is vulnerable to attacks. Graphical password can be used as an alternative to alphanumeric password that users choose images as a password. This type of password is easier to use and memorize and also more secure from pervious password types. In this paper we have designed a more secure graphical password system to prevent shoulder surfing, smudge and brute force attack. This scheme is a combination of two types of graphical passwords recognition based and Cued recall based. Evaluation the usability and security of our proposed scheme have been explained in conclusion part.

Keywords: brute force attack, graphical password, shoulder surfing attack, smudge attack

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Authors: Andrey A. Tyuftin, David Clarke, Malco C. Cruz-Romero, Declan Bolton, Seamus Fanning, Shashi K. Pankaj, Carmen Bueno-Ferrer, Patrick J. Cullen, Joe P. Kerry

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Prolonging of shelf-life is essential in order to address issues such as; supplier demands across continents, economical profit, customer satisfaction, and reduction of food wastage. Smart packaging solutions presented in the form of naturally occurred antimicrobially-active packaging may be a solution to these and other issues. Gelatin film forming solution with adding of natural sourced antimicrobials is a promising tool for the active smart packaging. The objective of this study was to coat conventional plastic hydrophobic packaging material with hydrophilic antimicrobial active beef gelatin coating and conduct shelf life trials on beef sub-primal cuts. Minimal inhibition concentration (MIC) of Caprylic acid sodium salt (SO) and commercially available Auranta FV (AFV) (bitter oranges extract with mixture of nutritive organic acids) were found of 1 and 1.5 % respectively against bacterial strains Bacillus cereus, Pseudomonas fluorescens, Escherichia coli, Staphylococcus aureus and aerobic and anaerobic beef microflora. Therefore SO or AFV were incorporated in beef gelatin film forming solution in concentration of two times of MIC which was coated on a conventional plastic LDPE/PA film on the inner cold plasma treated polyethylene surface. Beef samples were vacuum packed in this material and stored under chilling conditions, sampled at weekly intervals during 42 days shelf life study. No significant differences (p < 0.05) in the cook loss was observed among the different treatments compared to control samples until the day 29. Only for AFV coated beef sample it was 3% higher (37.3%) than the control (34.4 %) on the day 36. It was found antimicrobial films did not protect beef against discoloration. SO containing packages significantly (p < 0.05) reduced Total viable bacterial counts (TVC) compared to the control and AFV samples until the day 35. No significant reduction in TVC was observed between SO and AFV films on the day 42 but a significant difference was observed compared to control samples with a 1.40 log of bacteria reduction on the day 42. AFV films significantly (p < 0.05) reduced TVC compared to control samples from the day 14 until the day 42. Control samples reached the set value of 7 log CFU/g on day 27 of testing, AFV films did not reach this set limit until day 35 and SO films until day 42 of testing. The antimicrobial AFV and SO coated films significantly prolonged the shelf-life of beef steaks by 33 or 55% (on 7 and 14 days respectively) compared to control film samples. It is concluded antimicrobial coated films were successfully developed by coating the inner polyethylene layer of conventional LDPE/PA laminated films after plasma surface treatment. The results indicated that the use of antimicrobial active packaging coated with SO or AFV increased significantly (p < 0.05) the shelf life of the beef sub-primal. Overall, AFV or SO containing gelatin coatings have the potential of being used as effective antimicrobials for active packaging applications for muscle-based food products.

Keywords: active packaging, antimicrobials, edible coatings, food packaging, gelatin films, meat science

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Authors: Wiem Ben Khalifa, Dalila Souilem, Mahmoud Neji

Abstract:

The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time.

Keywords: Semantic Web, semantic system, ontology, evaluation, e-learning

Procedia PDF Downloads 334

Authors: Michelle Micah Augustine

Abstract:

Soap opera narrative creates a sense of community. Uzalo is a South African local soap opera television series. It is unique because Uzalo tells the story of black people and their everyday struggle centered in KwaMashu township community, which is an excellent example of how moving image culture has contributed in portraying township community that was once marginalized by the apartheid regime in contemporary South Africa. While soap opera importance and promotion of social change and behaviours have been extensively studied throughout history, little research has examined the importance of space and place in its narrative. This study explored the conventional community space and place, the core elements that drive soap opera narrative. By means of qualitative content analysis, the study investigated the construction of public meeting places in Uzalo, using a purposive sampling technique to collect data by choosing episodes. The result indicates that characters convergence in public meeting places in soap opera creates disequilibrium which drives the narrative; reveals that construction of a public meeting place is an important way of creating a minimum of homogeneousness among disparate characters, gives a sense of unified experience drawing on the notion of the particular characteristics or attitude generated from such place. The result shows that the use of camera angles, movements, editing, music and usual tricks (mise-en-scene) applied in the narrative setting function as a guide for viewers comprehension of emotional responses of the story and to connect with the space in which the narrative is set.

Keywords: community, narrative, place, space, soap opera

Procedia PDF Downloads 146

Authors: Erfan Niazi, Marianne Fenech

Abstract:

Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x10³(±0.3 x10³) 1/s.

Keywords: red blood cell, rouleaux, microfluidics, image processing, population balance modeling

Procedia PDF Downloads 355

Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

Abstract:

Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

Procedia PDF Downloads 113