Search results for: parallel processing

Authors: Travis Morris

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The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: propaganda analysis, emotive triggers environmental security, frames

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Authors: Patrick Mueller, Alan Martin, Justin Stockwell, Robert Goldblatt

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Elevated concentrations of inorganic nitrogen (N) compounds (nitrate, nitrite, and ammonia) are a ubiquitous feature to mine-influenced drainages due to the leaching of blasting residues and use of cyanide in the milling of gold ores. For many mines, the management of N is a focus for environmental protection, therefore understanding the factors controlling the speciation and behavior of N is central to effective decision making. In this paper, the passive attenuation of ammonia and nitrite is described for three northern water bodies (two lakes and a tailings pond) influenced by mining activities. In two of the water bodies, inorganic N compounds originate from explosives residues in mine water and waste rock. The third water body is a decommissioned tailings impoundment, with N compounds largely originating from the breakdown of cyanide compounds used in the processing of gold ores. Empirical observations from water quality monitoring indicate nitrification (the oxidation of ammonia to nitrate) occurs in all three waterbodies, where enrichment of nitrate occurs commensurately with ammonia depletion. The N species conversions in these systems occurred more rapidly than chemical oxidation kinetics permit, indicating that microbial mediated conversion was occurring, despite the cool water temperatures. While nitrification of ammonia and nitrite to nitrate was the primary process, in all three waterbodies nitrite was consistently present at approximately 0.5 to 2.0 % of total N, even following ammonia depletion. The persistence of trace amounts of nitrite under these conditions suggests the co-occurrence denitrification processes in the water column and/or underlying substrates. The implications for N management in mine waters are discussed.

Keywords: explosives, mining, nitrification, water

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Authors: Deepak Loura

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The most contemporary method of producing horticulture crops both qualitatively and quantitatively is protected cultivation, or greenhouse cultivation, which has gained widespread acceptance in recent decades. Protected farming, commonly referred to as controlled environment agriculture (CEA), is extremely productive, land- and water-wise, as well as environmentally friendly. The technology entails growing horticulture crops in a controlled environment where variables such as temperature, humidity, light, soil, water, fertilizer, etc. are adjusted to achieve optimal output and enable a consistent supply of them even during the off-season. Over the past ten years, protected cultivation of high-value crops and cut flowers has demonstrated remarkable potential. More and more agricultural and horticultural crop production systems are moving to protected environments as a result of the growing demand for high-quality products by global markets. By covering the crop, it is possible to control the macro- and microenvironments, enhancing plant performance and allowing for longer production times, earlier harvests, and higher yields of higher quality. These shielding features alter the environment of the plant while also offering protection from wind, rain, and insects. Protected farming opens up hitherto unexplored opportunities in agriculture as the liberalised economy and improved agricultural technologies advance. Typically, the revenues from fruit, vegetable, and flower crops are 4 to 8 times higher than those from other crops. If any of these high-value crops are cultivated in protected environments like greenhouses, net houses, tunnels, etc., this profit can be multiplied. Vegetable and cut flower post-harvest losses are extremely high (20–0%), however sheltered growing techniques and year-round cropping can greatly minimize post-harvest losses and enhance yield by 5–10 times. Seasonality and weather have a big impact on the production of vegetables and flowers. The variety of their products results in significant price and quality changes for vegetables. For the application of current technology in crop production, achieving a balance between year-round availability of vegetables and flowers with minimal environmental impact and remaining competitive is a significant problem. The future of agriculture will be protected since population growth is reducing the amount of land that may be held. Protected agriculture is a particularly profitable endeavor for tiny landholdings. Small greenhouses, net houses, nurseries, and low tunnel greenhouses can all be built by farmers to increase their income. Protected agriculture is also aided by the rise in biotic and abiotic stress factors. As a result of the greater productivity levels, these technologies are not only opening up opportunities for producers with larger landholdings, but also for those with smaller holdings. Protected cultivation can be thought of as a kind of precise, forward-thinking, parallel agriculture that covers almost all aspects of farming and is rather subject to additional inspection for technical applicability to circumstances, farmer economics, and market economics.

Keywords: protected cultivation, horticulture, greenhouse, vegetable, controlled environment agriculture

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Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

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Authors: Karla D. Vazquez-Valdez, Bradley P. Wynne

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In the last decades manufacturing needs have been changing, leading to the study of manufacturing methods that were underdeveloped, such as incremental forming processes like shear forming. These processes use rotating tools in constant local contact with the workpiece, which is often also rotating, to generate shape. This means much lower loads to forge large parts and no need for expensive special tooling. Potential has already been established by demonstrating manufacture of high-value products, e.g., turbine and satellite parts, with high dimensional accuracy from difficult to manufacture materials. Thus, huge opportunities exist for these processes to replace the current method of manufacture for a range of high value components, e.g., eliminating lengthy machining, reducing material waste and process times; or the manufacture of a complicated shape without the development of expensive tooling. However, little is known about the exact deformation conditions during processing and why certain materials are better than others for shear forming, leading to a lot of trial and error before production. Three alloys were used for this study: Ti-54M, Jethete M154, and IN718. General Microscopy and Electron Backscatter Diffraction (EBSD) were used to measure strains and orientation maps during shear forming. A Design of Experiments (DOE) analysis was also made in order to understand the impact of process parameters in the properties of the final workpieces. Such information was the key to develop a reliable Finite Element Method (FEM) model that closely resembles the deformation paths of this process. Finally, the potential of these three materials to be shear spun was studied using the FEM model and their Forming Limit Diagram (FLD) which led to the development of a rough methodology for testing the shear spinnability of various metals.

Keywords: shear forming, damage, principal strains, forming limit diagram

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Authors: Ian Omung'a

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Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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Authors: Ajibola Isola, Shattri Mansor, Ojogbane Sani, Olugbemi Tope

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The cadastral map is the rationale behind city management planning and development. For years, cadastral maps have been produced by ground and photogrammetry platforms. Recent evolution in photogrammetry and remote sensing sensors ignites the use of Unmanned Aerial Vehicle systems (UAVs) for cadastral mapping. Despite the time-saving and multi-dimensional cost-effectiveness of the UAV platform, issues related to cadastral map accuracy are a hindrance to the wide applicability of UAVs' cadastral mapping. This study aims to present an approach leading to the generation and assessing the credibility of UAV cadastral mapping. Different sets of Red, Green, and Blue (RGB) photos were obtained from the Tarot 680-hexacopter UAV platform flown over the Universiti Putra Malaysia campus sports complex at an altitude range of 70 m, 100 m, and 250. Before flying the UAV, twenty-eight ground control points were evenly established in the study area with a real-time kinematic differential global positioning system. The second phase of the study utilizes an image-matching algorithm for photos alignment wherein camera calibration parameters and ten of the established ground control points were used for estimating the inner, relative, and absolute orientations of the photos. The resulting orthoimages are exported to ArcGIS software for digitization. Visual, tabular, and graphical assessments of the resulting cadastral maps showed a different level of accuracy. The results of the study show a gradual approach for generating UAV cadastral mapping and that the cadastral map acquired at 70 m altitude produced better results.

Keywords: aerial mapping, orthomosaic, cadastral map, flying altitude, image processing

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Authors: R. T. Aggangan

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Woodfuels continue to be a major component of the energy supply mix of the Philippines due to increasing demand for energy that are not adequately met by decreasing supply and increasing prices of fuel oil such as liquefied petroleum gas (LPG) and kerosene. The Development Academy of the Philippines projects the demand of woodfuels in 2016 as 28.3 million metric tons in the household sector and about 105.4 million metric tons combined supply potentials of both forest and non-forest lands. However, the Revised Master Plan for Forestry Development projects a demand of about 50 million cu meters of fuelwood in 2016 but the capability to supply from local sources is only about 28 million cu meters indicating a 44 % deficiency. Household demand constitutes 82% while industries demand is 18%. Domestic household demand for energy is for cooking needs while the industrial demand is for steam power generation, curing barns of tobacco: brick, ceramics and pot making; bakery; lime production; and small scale food processing. Factors that favour increased use of wood-based energy include the relatively low prices (increasing oil-based fuel prices), availability of efficient wood-based energy utilization technology, increasing supply, and increasing population that cannot afford conventional fuels. Moreover, innovations in combustion technology and cogeneration of heat and power from biomass for modern applications favour biomass energy development. This paper recommends policies and strategic directions for the development of the woodfuel industry with the twin goals of sustainably supplying the energy requirements of households and industry.

Keywords: biomass energy development, fuelwood, households and industry, innovations in combustion technology, supply and demand

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Authors: Angelika Dorawa, Lena Kreppel

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Writing in the disciplines plays a major role at Universities. On the one hand, lectures look at the substance of assignments and on the other hand, they expect students to meet professional standards of layout and proofreading. However, the integration of writing concepts into the range of subjects is new to German Universities of Applied Sciences, which are focused on technical and scientific contexts. The Westphalian University of Applied Sciences (WH) established a successful program Talente_schreiben (Writing_Talents) that was funded by the Federal Ministry of Education and Research to improve written language skills for first-semester students at the WH. Besides having the main focus on basic language skills on all language levels, we also concentrate on subject-specific programs such as writing in the disciplines and are pioneers in this field in Germany. Since 2013, we started to include learning-to-write programs since first-semester students of Business Law studies must complete a writing assignment in the form and writing style of a legal opinion in order to fulfill their undergraduate degree requirements. To support our students at its best, our course for business lawyers focuses not only on the writing skills per se, but also on teaching both, the content and the particular discourse of the discipline. Hence, a specialist in German studies and a faculty tutor share the experience of processing, producing and reflecting a text. Whereas the German studies specialist refers to the rhetorical context such as orthography, grammar etc., the tutor acts as a guide on the side referring to the course content itself. In our presentation, we want to give an insight of the practice of a business law discipline, the combination of rhetoric and composition and discuss the methodological and didactic approaches.

Keywords: German for business lawyers, talent development, pioneer program, Germany

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Authors: Paula Pascoal-Faria, Rúben Pereira, Elodie Pinto, Miguel Belbut, Ana Rosa, Inês Sousa, Nuno Alves

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Apple bruise damage from harvesting, handling, transporting and sorting is considered to be the major source of reduced fruit quality, resulting in loss of profits for the entire fruit industry. The three factors which can physically cause fruit bruising are vibration, compression load and impact, the latter being the most common source of bruise damage. Therefore, prediction of the level of damage, stress distribution and deformation of the fruits under external force has become a very important challenge. In this study, experimental and numerical methods were used to better understand the impact caused when an apple is dropped from different heights onto a plastic surface and a conveyor belt. Results showed that the extent of fruit damage is significantly higher for plastic surface, being dependent on the height. In order to support the development of a biomimetic electronic device for the determination of fruit damage, the mechanical properties of the apple fruit were determined using mechanical tests. Preliminary results showed different values for the Young’s modulus according to the zone of the apple tested. Along with the mechanical characterization of the apple fruit, the development of the first two prototypes is discussed and the integration of the results obtained to construct the final element model of the apple is presented. This work will help to reduce significantly the bruise damage of fruits or vegetables during the entire processing which will allow the introduction of exportation destines and consequently an increase in the economic profits in this sector.

Keywords: apple, fruit damage, impact during crop and post-crop, mechanical characterization of the apple, numerical evaluation of fruit damage, electronic device

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Authors: E. Tarantino, G. Disciglio, G. Gatta, L. Frabboni, A. Libutti, A. Tarantino

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Worldwide, about two-thirds of industrial and domestic wastewater effluent is discharged without treatment, which can cause contamination and eutrophication of the water. In particular, for Mediterranean countries, irrigation with treated wastewater would mitigate the water stress and support the agricultural sector. Changing global weather patterns will make the situation worse, due to increased susceptibility to drought, which can cause major environmental, social, and economic problems. The study was carried out in open field in an intensive agricultural area of the Apulian region in Southern Italy where freshwater resources are often scarce. As well as providing a water resource, irrigation with treated wastewater represents a significant source of nutrients for soil–plant systems. However, the use of wastewater might have further effects on soil. This study thus investigated the long-term impact of irrigation with reclaimed agro-industrial wastewater on the chemical characteristics of the soil. Two crops (processing tomato and broccoli) were cultivated in succession in Stornarella (Foggia) over four years from 2012 to 2016 using two types of irrigation water: groundwater and tertiary treated agro-industrial wastewater that had undergone an activated sludge process, sedimentation filtration, and UV radiation. Chemical analyses were performed on the irrigation waters and soil samples. The treated wastewater was characterised by high levels of several chemical parameters including TSS, EC, COD, BOD₅, Na⁺, Ca²⁺, Mg²⁺, NH₄-N, PO₄-P, K⁺, SAR and CaCO₃, as compared with the groundwater. However, despite these higher levels, the mean content of several chemical parameters in the soil did not show relevant differences between the irrigation treatments, in terms of the chemical features of the soil.

Keywords: agro-industrial wastewater, broccoli, long-term re-use, tomato

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Authors: Yulan Wu

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The spread of fake news on social media has posed significant societal harm to the public and the nation, with its threats spanning various domains, including politics, economics, health, and more. News on social media often covers multiple domains, and existing models studied by researchers and relevant organizations often perform well on datasets from a single domain. However, when these methods are applied to social platforms with news spanning multiple domains, their performance significantly deteriorates. Existing research has attempted to enhance the detection performance of multi-domain datasets by adding single-domain labels to the data. However, these methods overlook the fact that a news article typically belongs to multiple domains, leading to the loss of domain knowledge information contained within the news text. To address this issue, research has found that news records in different domains often use different vocabularies to describe their content. In this paper, we propose a fake news detection framework that combines domain knowledge and expert knowledge. Firstly, it utilizes an unsupervised domain discovery module to generate a low-dimensional vector for each news article, representing domain embeddings, which can retain multi-domain knowledge of the news content. Then, a feature extraction module uses the domain embeddings discovered through unsupervised domain knowledge to guide multiple experts in extracting news knowledge for the total feature representation. Finally, a classifier is used to determine whether the news is fake or not. Experiments show that this approach can improve multi-domain fake news detection performance while reducing the cost of manually labeling domain labels.

Keywords: fake news, deep learning, natural language processing, multiple domains

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Authors: J. K Adedeji, O. H Olowomofe, C. O Alo, S.T Ijatuyi

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The issue of high blood sugar level, the effects of which might end up as diabetes mellitus, is now becoming a rampant cardiovascular disorder in our community. In recent times, a lack of awareness among most people makes this disease a silent killer. The situation calls for urgency, hence the need to design a device that serves as a monitoring tool such as a wrist watch to give an alert of the danger a head of time to those living with high blood glucose, as well as to introduce a mechanism for checks and balances. The neural network architecture assumed 8-15-10 configuration with eight neurons at the input stage including a bias, 15 neurons at the hidden layer at the processing stage, and 10 neurons at the output stage indicating likely symptoms cases. The inputs are formed using the exclusive OR (XOR), with the expectation of getting an XOR output as the threshold value for diabetic symptom cases. The neural algorithm is coded in Java language with 1000 epoch runs to bring the errors into the barest minimum. The internal circuitry of the device comprises the compatible hardware requirement that matches the nature of each of the input neurons. The light emitting diodes (LED) of red, green, and yellow colors are used as the output for the neural network to show pattern recognition for severe cases, pre-hypertensive cases and normal without the traces of diabetes mellitus. The research concluded that neural network is an efficient Accu-Chek design tool for the proper monitoring of high glucose levels than the conventional methods of carrying out blood test.

Keywords: Accu-Check, diabetes, neural network, pattern recognition

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Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

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Authors: Ana Lucia Molina

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Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique for the investigation and modulation of cortical excitability in humans. The modulation of the processing of different cortical areas can result in several areas for rehabilitation, showing great potential in the treatment of motor disorders. In the human brain, the supplementary motor area (SMA) is involved in the control of the pelvic floor muscles (MAP), where dysfunctions of these muscles can lead to urinary incontinence. Peripheral magnetic stimulation, specifically sacral magnetic stimulation, has been used as a safe and effective treatment option for patients with lower urinary tract dysfunction. A systematic literature review was carried out (Pubmed, Medline and Google academic database) without a time limit using the keywords: "transcranial magnetic stimulation", "sacral neuromodulation", and "urinary incontinence", where 11 articles attended to the inclusion criteria. Results: Thirteen articles were selected. Magnetic stimulation is a non-invasive neuromodulation technique widely used in the evaluation of cortical areas and their respective peripheral areas, as well as in the treatment of lesions of brain origin. With regard to pelvic-perineal disorders, repetitive transcranial stimulation showed significant effects in controlling urinary incontinence, as well as sacral peripheral magnetic stimulation, in addition to exerting the potential to restore bladder sphincter function. Conclusion: Data from the literature suggest that both transcranial stimulation and peripheral stimulation are non-invasive references that can be promising and effective means of treatment in pelvic and perineal disorders. More prospective and randomized studies on a larger scale are needed, adapting the most appropriate and resolving parameters.

Keywords: urinary incontinence, non-invasive neuromodulation, sacral neuromodulation, transcranial magnetic stimulation.

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Authors: Siddhi Khaire, Samarth Hawaldar, Baladitya Suri

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As efforts towards quantum communication advance, the need for single photon sources becomes imminent. Due to the extremely low energy of a single microwave photon, efforts to build single photon sources and detectors in the microwave range are relatively recent. We plan to use a Cooper Pair Box (CPB) that has a ‘sweet-spot’ where the two energy levels have minimal separation. Moreover, these qubits have fairly large anharmonicity making them close to ideal two-level systems. If the external gate voltage of these qubits is varied rapidly while passing through the sweet-spot, due to Landau-Zener effect, the qubit can be excited almost deterministically. The rapid change of the gate control voltage through the sweet spot induces a non-adiabatic population transfer from the ground to the excited state. The qubit eventually decays into the emission line emitting a single photon. The advantage of this setup is that the qubit can be excited without any coherent microwave excitation, thereby effectively increasing the usable source efficiency due to the absence of control pulse microwave photons. Since the probability of a Landau-Zener transition can be made almost close to unity by the appropriate design of parameters, this source behaves as an on-demand source of single microwave photons. The large anharmonicity of the CPB also ensures that only one excited state is involved in the transition and multiple photon output is highly improbable. Such a system has so far not been implemented and would find many applications in the areas of quantum optics, quantum computation as well as quantum communication.

Keywords: quantum computing, quantum communication, quantum optics, superconducting qubits, flux qubit, charge qubit, microwave single photon source, quantum information processing

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Authors: Adepoju Abiola Lydia, Adeyanju James Abiodun, Abioye A. O.

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Spray drying, an innovative and sustainable preservation method, is increasingly gaining recognition for its potential to enhance food security by extending the shelf life of fruits. This technique involves the atomization of fruit pulp into fine droplets, followed by rapid drying with hot air, resulting in a powdered product that retains much of the original fruit's nutritional value, flavor, and color. By encapsulating sensitive bioactive compounds within a dry matrix, spray drying mitigates nutrient degradation and extends product usability. This technology aligns with sustainability goals by reducing post-harvest losses, minimizing the need for preservatives, and lowering energy consumption compared to conventional drying methods. Furthermore, spray drying enables the use of imperfect or surplus fruits, contributing to waste reduction and providing a continuous supply of nutritious fruit-based ingredients regardless of seasonal variations. The powdered form enhances versatility, allowing incorporation into various food products, thus broadening the scope of fruit utilization. Innovations in spray drying, such as the use of novel carrier agents and optimization of processing parameters, enhance the quality and functionality of the final product. Moreover, the scalability of spray drying makes it suitable for both industrial applications and smaller-scale operations, supporting local economies and food systems. In conclusion, spray drying stands out as a key technology in enhancing food security by ensuring a stable supply of high-quality, nutritious food ingredients while fostering sustainable agricultural practices.

Keywords: spray drying, sustainable, process parameters, carrier agents, fruits

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Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

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UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

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Authors: Can Huang, Xiaoliang Wang, Qingquan Liu

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Soil‒water coupling is an important process in landslide-generated impulse waves (LGIW) problems, accompanied by large deformation of soil, strong interface coupling and three-dimensional effect. A meshless particle method, smooth particle hydrodynamics (SPH) has great advantages in dealing with complex interface and multiphase coupling problems. This study presents an improved soil‒water coupled model to simulate LGIW problems based on an open source code DualSPHysics (v4.0). Aiming to solve the low efficiency problem in modeling real large-scale LGIW problems, graphics processing unit (GPU) acceleration technology is implemented into this code. An experimental example, subaerial landslide-generated water waves, is simulated to demonstrate the accuracy of this model. Then, the Huangtian LGIW, a real large-scale LGIW problem is modeled to reproduce the entire disaster chain, including landslide dynamics, fluid‒solid interaction, and surge wave generation. The convergence analysis shows that a particle distance of 5.0 m can provide a converged landslide deposit and surge wave for this example. Numerical simulation results are in good agreement with the limited field survey data. The application example of the Huangtian LGIW provides a typical reference for large-scale LGIW assessments, which can provide reliable information on landslide dynamics, interface coupling behavior, and surge wave characteristics.

Keywords: soil‒water coupling, landslide-generated impulse wave, large-scale, SPH

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Authors: Rahul Kumar, Pavuluri Srinivasa Rao

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This study investigates the effect of ultrasound-assisted high pressure (HP) treatment on the soaking characteristic of soybeans and extracted soy milk quality. The soybean (variety) was subjected to sonication (US) at ambient temperature for 15 and 30 min followed by HP treatment in the range of 200-400 MPa for dwell times 5-10 min. The bean samples were also compared with HPP samples (200-400 MPa; 5-10 mins), overnight soaked samples(12-15 h) and thermal treated samples (100°C/30 min) followed by overnight soaking for 12-15 h soaking. Rapid soaking within 40 min was achieved by the combined US-HPP treatment, and it reduced the soaking time by about 25 times in comparison to overnight soaking or thermal treatment followed by soaking. Reducing the soaking time of soybeans is expected to suppress the development of undesirable beany flavor of soy milk developed during normal soaking milk extraction. The optimum moisture uptake by the sonicated-pressure treated soybeans was 60-62% (w.b) similar to that obtained after overnight soaking for 12-15 h or thermal treatment followed by overnight soaking. pH of soy milk was not much affected by the different US-HPP treatments and overnight soaking which centered around the range of 6.6-6.7 much like the normal cow milk. For milk extracted from thermally treated soy samples, pH reduced to 6.2. Total soluble solids were found to be maximum for the normal overnight soaked soy samples, and it was in the range of 10.3-10.6. For the HPP treated soy milk, the TSS reduced to 7.4 while sonication further reduced it to 6.2. TSS was found to be getting reduced with increasing time of ultrasonication. Further reduction in TSS to 2.3 was observed in soy milk produced from thermally treated samples following overnight soaking. Our results conclude that thermally treated beans' milk is less stable and more acidic, soaking is very rapid compared to overnight soaking hence milk productivity can be enhanced with less development of undesirable beany flavor.

Keywords: beany flavor, high pressure processing, high pressure, soybean, soaking, milk, ultrasound, wet basis

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Authors: Kubra Dogan, Fatih Tornuk

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Due to increasing consumer demand for the high-quality food products and awareness regarding the health benefits of different nutrients in food minimal processing becomes more popular in modern food preservation. To date, heat treatment is often used for inactivation of spoilage microorganisms in foods. However, it may cause significant changes in the quality and nutritional properties of food. In order to overcome the detrimental effects of heat treatment, several alternatives of non-thermal microbial inactivation processes have been investigated. Ultraviolet (UV) inactivation is a promising and feasible method for better quality and longer shelf life as an alternative to heat treatment, which aims to inhibit spoilage and pathogenic microorganisms and to inactivate the enzymes in vegetable juice production. UV-C is a sub-class of UV treatment which shows the highest microcidal effect between 250-270 nm. The wavelength of 254 nm is used for the surface disinfection of certain liquid food products such as vegetable juice. Effects of UV-C treatment on microbiological load and quality parameter of vegetable juice which is a mix of celery, carrot, lemon and orange was investigated. Our results showed that storing of UV-C applied vegetable juice for three months, reduced the count of TMAB by 3.5 log cfu/g and yeast-mold by 2 log cfu/g compared to control sample. Total phenolic content was found to be 514.3 ± 0.6 mg gallic acid equivalent/L, and there wasn’t a significant difference compared to control. The present work suggests that UV-C treatment is an alternative method for disinfection of vegetable juice since it enables adequate microbial inactivation, longer shelf life and has minimal effect on degradation of quality parameters of vegetable juice.

Keywords: heat treatment, phenolic content, shelf life, ultraviolet (UV-C), vegetable juice

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Jun-Lun Jiang, Bing-Sheng Yu

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Processing of flat-panel displays generates huge amount of wasted glass polishing powder, with high concentration of cerium and other elements such as lanthanum. According to the current statistics, consumption of polishing powder was approximately ten thousand tons per year in the world. Nevertheless, wasted polishing powder was usually buried or burned. If the lanthanum and cerium compounds in the wasted polishing powder could be recycled, that will greatly reduce enterprise cost and implement waste circulation. Cathodes of SOFCs are the principal consisting of rare earth elements such as lanthanum and cerium. In this study, we recycled the lanthanum and cerium from wasted glass polishing powder by acid-solution method, and synthesized La0.8Sr0.05Ca0.15Fe0.8Co0.8O3-δ and Gd0.1Ce0.9O2 (LSCCF-GDC) composite cathode material for SOFCs by glycinenitrate combustion (GNP) method. The results show that the recovery rates of lanthanum and cerium could accomplish up to 80% and 100% under 10N nitric acid solution within one hour. Comparing with the XRD data of the commercial LSCCF-GDC powder and the LSCCF-GDC product synthesized with chemicals, we find that the LSCCF-GDC was successfully synthesized with the recycled La & Ce solution by GNP method. The effect of adding ammonia to the product was also discussed, the grain size is finer and recovery rate of the product is higher without the addition of ammonia to the solution.

Keywords: glass polishing powder, acid solution, recycling, composite cathodes of solid oxide fuel, cell (SOFC), perovskite, glycine-nitrate combustion(GNP) method

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Authors: F. Portet-Koltalo, Y. Tian, I. Berger, C. Boulanger-Lecomte, A. Benamar, N. Machour

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Sediments are complex environments which can accumulate a great variety of persistent toxic contaminants such as polychlorobiphenyles (PCBs), polycyclic aromatic hydrocarbons (PAHs) and some of their more toxic degradation metabolites such as hydroxylated PAHs (OH-PAHs). Owing to their composition, fine clayey sediments can be more difficult to extract than soils using conventional solvent extraction processes. So this study aimed to compare the potential of MSPD (matrix solid phase dispersive extraction) to extract PCBs, PAHs and OH-PAHs, in comparison with microwave assisted extraction (MAE). Methodologies: MAE extraction with various solvent mixtures was used to extract PCBs, PAHs and OH-PAHs from sediments in two runs, followed by two GC-MS analyses. MSPD consisted in crushing the dried sediment with dispersive agents, introducing the mixture in cartridges and eluting the target compounds with an appropriate volume of selected solvents. So MSPD combined with cartridges containing MIPs (molecularly imprinted polymers) designed for OH-PAHs was used to extract the three families of target compounds in only one run, followed by parallel analyses in GC-MS for PAHs/PCBs and HPLC-FLD for OH-PAHs. Results: MAE extraction was optimized to extract from clayey sediments, in two runs, PAHs/PCBs in one hand and OH-PAHs in the other hand. Indeed, the best conditions of extractions (mixtures of extracting solvents, temperature) were different if we consider the polarity and the thermodegradability of the different families of target contaminants: PAHs/PCBs were better extracted using an acetone/toluene 50/50 mixture at 130°C whereas OH-PAHs were better extracted using an acetonitrile/toluene 90/10 mixture at 100°C. Moreover, the two consecutive GC-MS analyses contributed to double the total analysis time. A matrix solid phase dispersive (MSPD) extraction procedure was also optimized, with the first objective of increasing the extraction recovery yields of PAHs and PCBs from fine-grained sediment. The crushing time (2-10 min), the nature of the dispersing agents added for purifying and increasing the extraction yields (Florisil, octadecylsilane, 3-chloropropyle, 4-benzylchloride), the nature and the volume of eluting solvents (methylene chloride, hexane, hexane/acetone…) were studied. It appeared that in the best conditions, MSPD was a better extraction method than MAE for PAHs and PCBs, with respectively, mean increases of 8.2% and 71%. This method was also faster, easier and less expensive. But the other advantage of MSPD was that it allowed to introduce easily, just after the first elution process of PAHs/PCBs, a step permitting the selective recovery of OH-PAHs. A cartridge containing MIPs designed for phenols was coupled to the cartridge containing the dispersed sediment, and various eluting solvents, different from those used for PAHs and PCBs, were tested to selectively concentrate and extract OH-PAHs. Thereafter OH-PAHs could be analyzed at the same time than PAHs and PCBs: the OH-PAH extract could be analyzed with HPLC-FLD, whereas the PAHs/PCBs extract was analyzed with GC-MS, adding only few minutes more to the total duration of the analytical process. Conclusion: MSPD associated to MIPs appeared to be an easy, fast and low expensive method, able to extract in one run a complex mixture of toxic apolar and more polar contaminants present in clayey fine-grained sediments, an environmental matrix which is generally difficult to analyze.

Keywords: contaminated fine-grained sediments, matrix solid phase dispersive extraction, microwave assisted extraction, molecularly imprinted polymers, multi-pollutant analysis

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Authors: Seung-Min Yang, Seong-Han Park, Sang-Hoon Lee, Seung-Wan Yoo, Chan-Soo Kim, Nong-Moon Hwang

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The theory of charged nanoparticles suggested that in many Chemical Vapour Depositions (CVD) processes, Charged Nanoparticles (CNPs) are generated in the gas-phase and become a building block of thin films and nanowires. Recently, the nanoparticle-based crystallization has become a big issue since the growth of nanorods or crystals by the building block of nanoparticles was directly observed by transmission electron microscopy observations in the liquid cell. In an effort to confirm charged gas-phase nuclei, that might be generated under conventional processing conditions of thin films and nanowires during CVD, we performed an in-situ measurement using differential mobility analyser and particle beam mass spectrometer. The size distribution and number density of CNPs were affected by process parameters such as precursor flow rate and working temperature. It was shown that many films and nanostructures, which have been believed to grow by individual atoms or molecules, actually grow by the building blocks of such charged nuclei. The electrostatic interaction between CNPs and the growing surface induces the self-assembly into films and nanowires. In addition, the charge-enhanced atomic diffusion makes CNPs liquid-like quasi solid. As a result, CNPs tend to land epitaxial on the growing surface, which results in the growth of single crystalline nanowires with a smooth surface.

Keywords: chemical vapour deposition, charged nanoparticle, electrostatic force, nanostructure evolution, differential mobility analyser, particle beam mass spectrometer

Procedia PDF Downloads 452

Authors: Fakhreia A. Al Sagheer, Enas I. Ibrahim, Khaled D. Khalil

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N-Acryloyl morpholine, NAM, was grafted onto chitosan utilizing homogeneous conditions with 1% acetic acid as the solvent, and potassium persulfate and sodium sulfite as the redox initiator. The effects of various reaction parameters, such as time, temperature, and monomer and initiator concentrations, on the percentage of grafting (G%) and the grafting efficiency (E%) were determined. The graft copolymer showed a remarkably improved crystallinity, as compared to the unmodified chitosan, based on the FESEM, XRD, and DSC results. Chitosan-g-poly(N-acryloyl morpholine) (Cs-PNAM), the copolymer obtained by using this procedure, was characterized by utilizing FTIR, FESEM, TGA, and XRD analysis. As expected, the results of an evaluation of antibacterial and antifungal activities show that the grafted chitosan copolymers exhibit stronger inhibitory effects against both types of microbes than does chitosan. Moreover, the size of the inhibition zone created by the graft copolymer was observed to be proportional to its G% corresponding to its morpholine content. Fortunately, the graft copolymer showed a marked growth inhibition against candidiasis (C.Albicans and C.Kefyr). We conclude that the graft copolymer may be highly effective in the prevention and treatment of candidiasis. In addition, the extent and pH dependence of uptake of different types of dyes (acidic: EBT, and MV; and basic: MB) by grafted chitosan in pH 6.5 aqueous solutions was determined. The results show that, the grafted copolymer exhibited a greater affinity to absorb the acid dyes more than the basic ones especially at relatively low temperature. Thus the modified chitosan can be used, in wastewater treatment, as efficient economic absorbent especially for anionic dyes from the industrial processing effluents.

Keywords: chitosan, N-Acryloyl morpholine, homogeneous grafting, antimicrobial activity, dye uptake

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Authors: Tibor Ajtai, Noémi Utry, Máté Pintér, Gábor Szabó, Zoltán Bozóki

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Beyond its climate and health related issues ambient light absorbing carbonaceous particulate matter (LAC) has also become a great scientific interest in terms of its regulations recently. It has been experimentally demonstrated in recent studies, that LAC is dominantly composed of traffic and wood burning aerosol particularly under wintertime urban conditions, when the photochemical and biological activities are negligible. Several methods have been introduced to quantitatively apportion aerosol fractions emitted by wood burning and traffic but most of them require costly and time consuming off-line chemical analysis. As opposed to chemical features, the microphysical properties of airborne particles such as optical absorption and size distribution can be easily measured on-line, with high accuracy and sensitivity, especially under highly polluted urban conditions. Recently a new method has been proposed for the apportionment of wood burning and traffic aerosols based on the spectral dependence of their absorption quantified by the Aerosol Angström Exponent (AAE). In this approach the absorption coefficient is deduced from transmission measurement on a filter accumulated aerosol sample and the conversion factor between the measured optical absorption and the corresponding mass concentration (the specific absorption cross section) are determined by on-site chemical analysis. The recently developed multi-wavelength photoacoustic instruments provide novel, in-situ approach towards the reliable and quantitative characterization of carbonaceous particulate matter. Therefore, it also opens up novel possibilities on the source apportionment through the measurement of light absorption. In this study, we demonstrate an in-situ spectral characterization method of the ambient carbon fraction based on light absorption and size distribution measurements using our state-of-the-art multi-wavelength photoacoustic instrument (4λ-PAS) and Single Mobility Particle Sizer (SMPS) The carbonaceous particulate selective source apportionment study was performed for ambient particulate matter in the city center of Szeged, Hungary where the dominance of traffic and wood burning aerosol has been experimentally demonstrated earlier. The proposed model is based on the parallel, in-situ measurement of optical absorption and size distribution. AAEff and AAEwb were deduced from the measured data using the defined correlation between the AOC(1064nm)/AOC(266nm) and N100/N20 ratios. σff(λ) and σwb(λ) were determined with the help of the independently measured temporal mass concentrations in the PM1 mode. Furthermore, the proposed optical source apportionment is based on the assumption that the light absorbing fraction of PM is exclusively related to traffic and wood burning. This assumption is indirectly confirmed here by the fact that the measured size distribution is composed of two unimodal size distributions identified to correspond to traffic and wood burning aerosols. The method offers the possibility of replacing laborious chemical analysis with simple in-situ measurement of aerosol size distribution data. The results by the proposed novel optical absorption based source apportionment method prove its applicability whenever measurements are performed at an urban site where traffic and wood burning are the dominant carbonaceous sources of emission.

Keywords: absorption, size distribution, source apportionment, wood burning, traffic aerosol

Procedia PDF Downloads 228

Authors: Henrique Fernandes, Sofia Catalucci, Richard Leach, Kapil Sugand

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Background: Holograms are 3D images formed by the interference of light beams from a laser or other coherent light source. Pepper’s ghost is a form of hologram conceptualised in the 18th century. This Holographic visualisation with metrology measuring techniques by displaying measurements taken in real-time in holographic form can assist in research and education. New structural designs such as the Plexiglass Stand and the Hologram Box can optimise the holographic experience. Method: The equipment used included: (i) Zeiss’s ATOS Core 300 optical coordinate measuring instrument that scanned real-world objects; (ii) Cloud Compare, open-source software used for point cloud processing; and (iii) Hologram Box, designed and manufactured during this research to provide the blackout environment needed to display 3D point clouds in real-time measurements in holographic format, in addition to a portability aspect to holograms. The equipment was tailored to realise the goal of displaying measurements in an innovative technique and to improve on conventional methods. Three test scans were completed before doing a holographic conversion. Results: The outcome was a precise recreation of the original object in the holographic form presented with dense point clouds and surface density features in a colour map. Conclusion: This work establishes a way to visualise data in a point cloud system. To our understanding, this is a work that has never been attempted. This achievement provides an advancement in holographic visualisation. The Hologram Box could be used as a feedback tool for measurement quality control and verification in future smart factories.

Keywords: holography, 3D scans, hologram box, metrology, point cloud

Procedia PDF Downloads 89

Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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Authors: Bo Wang

Abstract:

The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

Procedia PDF Downloads 284