Search results for: Neural Processing Element (NPE)

Authors: Jayeola A. O., Ayodele O. S., Olususi J. I.

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From field studies, six (6) lithological units were identified to be common around the study area, which includes quartzites, granites, granite gneiss, porphyritic granites, amphibolite and pegmatites. Petrographical analysis was done to establish the major mineral assemblages and accessory minerals present in selected rock samples, which represents the major rock types in the area. For the purpose of this study, twenty (20) pulverized rock samples were taken to the laboratory for geochemical analysis with their results used in the classification, as well as suggest the geochemical attributes of the rocks. Results from petrographical studies of the rocks under both plane and cross polarized lights revealed the major minerals identified under thin sections to include quartz, feldspar, biotite, hornblende, plagioclase and muscovite with opaque other accessory minerals, which include actinolite, spinel and myrmekite. Geochemical results obtained and interpreted using various geochemical plots or discrimination plots all classified the rocks in the area as belonging to both the peralkaline metaluminous and peraluminous types. Results for the major oxides ratios produced for Na₂O/K₂O, Al₂O₃/Na₂O + CaO + K₂O and Na₂O + CaO + K₂O/Al₂O₃ show the excess of alumina, Al₂O₃ over the alkaline Na₂O +CaO +K₂O thus suggesting peraluminous rocks. While the excess of the alkali over the alumina suggests the peralkaline metaluminous rock type. The results of correlation coefficient show a perfect strong positive correlation, which shows that they are of same geogenic sources, while negative correlation coefficient values indicate a perfect weak negative correlation, suggesting that they are of heterogeneous geogenic sources. From factor analysis, five component groups were identified as Group 1 consists of Ag-Cr-Ni elemental associations suggesting Ag, Cr, and Ni mineralization, predicting the possibility of sulphide mineralization. in the study area. Group ll and lll consist of As-Ni-Hg-Fe-Sn-Co-Pb-Hg element association, which are pathfinder elements to the mineralization of gold. Group 1V and V consist of Cd-Cu-Ag-Co-Zn, which concentrations are significant to elemental associations and mineralization. In conclusion, from the potassium radiometric anomaly map produced, the eastern section (northeastern and southeastern) is observed to be the hot spot and mineralization zone for the study area.

Keywords: petrography, Ila Orangun, petrochemistry, pegmatites, peraluminous

Procedia PDF Downloads 43

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 74

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

Procedia PDF Downloads 112

Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

Procedia PDF Downloads 52

Authors: Djamel Boussaa

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Cultural heritage and tourism have become during the last two decades dynamic areas of development in the world. The idea of heritage is crucial to the critical decision-making process as to how irreplaceable resources are to be utilized by people of the present or conserved for future generations in a fast changing world. In view of the importance of ‘heritage’ to the development of a tourist destination the emphasis on developing appropriate adaptive reuse strategies cannot be overemphasized. In October 1999, the 12th general assembly of the ICOMOS in Mexico stated, that in the context of sustainable development, two interrelated issues need urgent attention, cultural tourism and historic towns and cities. These two issues underscore the fact that historic resources are non-renewable, belonging to all of humanity. Without adequate adaptive reuse actions to ensure a sustainable future for these historic resources, may lead to their complete vanishing. The growth of tourism and its role in dispersing cultural heritage to everyone is developing rapidly. According to the World Tourism Organization, natural and cultural heritage resources are and will remain motivating factors for travel in the foreseeable future. According to the experts, people choose travel destinations where they can learn about traditional and distinct cultures in their historic context. The Qatar rich urban heritage is now being recognized as a valuable resource for future development. This paper discusses the role of cultural heritage and tourism in regenerating Souk Waqif, and consequently the city of Doha. Therefore, in order to use cultural heritage wisely, it will be necessary to position heritage as an essential element of sustainable development, giving particular attention to cultural heritage and tourism. The research methodology is based on an empirical survey of the situation, based on several visits, meetings and interviews with the local heritage players. The rehabilitation project initiated since 2004 will be examined and assessed. Therefore, there is potential to assess the situation and propose directions for a sustainable future to this historic landmark. Conservation for the sake of conservation appears to be an outdated concept. Many irreplaceable natural and cultural sites are being compromised because local authorities are not giving economic consideration to the value of rehabilitating such sites. The question to be raised here is 'How can cultural heritage be used wisely for tourism without compromising its social sustainability within the emerging global world?'

Keywords: cultural heritage, tourism, regeneration, economy, social sustainability

Procedia PDF Downloads 411

Authors: Bo Wang

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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 270

Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

Procedia PDF Downloads 176

Authors: Jeff Moussodji, Dominique Drouin

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The highly complex technology requirements of today’s integrated circuits (ICs), lead to the increased use of several materials types such as metal structures, brittle and porous low-k materials which are used in both front end of line (FEOL) and back end of line (BEOL) process for wafer manufacturing. In order to singulate chip from wafer, a critical laser-grooving process, prior to blade dicing, is used to remove these layers of materials out of the dicing street. The combination of laser-grooving and blade dicing allows to reduce the potential risk of induced mechanical defects such micro-cracks, chipping, on the wafer top surface where circuitry is located. It seems, therefore, essential to have a fundamental understanding of the physics involving laser-dicing in order to maximize control of these critical process and reduce their undesirable effects on process efficiency, quality, and reliability. In this paper, the study was based on the convergence of two approaches, numerical and experimental studies which allowed us to investigate the interaction of a nanosecond pulsed laser and BEOL wafer materials. To evaluate this interaction, several laser grooved samples were compared with finite element modeling, in which three different aspects; phase change, thermo-mechanical and optic sensitive parameters were considered. The mathematical model makes it possible to highlight a groove profile (depth, width, etc.) of a single pulse or multi-pulses on BEOL wafer material. Moreover, the heat affected zone, and thermo-mechanical stress can be also predicted as a function of laser operating parameters (power, frequency, spot size, defocus, speed, etc.). After modeling validation and calibration, a satisfying correlation between experiment and modeling, results have been observed in terms of groove depth, width and heat affected zone. The study proposed in this work is a first step toward implementing a quick assessment tool for design and debug of multiple laser grooving conditions with limited experiments on hardware in industrial application. More correlations and validation tests are in progress and will be included in the full paper.

Keywords: laser-dicing, nano-second pulsed laser, wafer multi-stack, multiphysics modeling

Procedia PDF Downloads 192

Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

Procedia PDF Downloads 121

Authors: D. Nagalakshmi, S. Parashuramulu K. Sadasiva Rao, G. Aruna, L. Vikram

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The zinc (Zn) is the second most abundant trace element in mammals and birds, forming structural component of over 300 enzymes, playing an important role in anti-oxidant defense, immune response and reproduction. Organic trace minerals are more readily absorbed from the digestive tract and more biologically available compared with its inorganic salt. Thus, the present study was undertaken on 60 adult female Sprague Dawley rats (275±2.04 g) for experimental duration of 12 weeks to investigate the effect of dietary Zn supplementation from various organic sources on immunity, reproduction, oxidative defense mechanism and blood biochemical profile. The rats were randomly allotted to 30 replicates (2 per replicate) which were in turn randomly allotted to 5 dietary treatments varying in Zn source i.e., one inorganic source (Zn carbonate) and 4 organic sources (Zn-proteinate, Zn-propionate, Zn-amino acid complex and Zn-methionine) so as to supply NRC recommended Zn concentration (12 ppm Zn). Supplementation of organic Zn had no effect on various haematological and serum biochemical constituents compared to inorganic Zn fed rats. The TBARS and protein carbonyls concentration in liver indicative of oxidative stress was comparable between various organic and inorganic groups. The glutathione reductase activity in haemolysate (P<0.05) and reduced glutathione concentration in liver (P<0.01) was higher when fed organic Zn and RBC catalase activity was higher (P<0.01) on Zn methionine compared to other organic sources tested and the inorganic source. The humoral immune response assessed as antibody titres against sheep RBC was higher (P<0.05) when fed organic sources of zinc compared to inorganic source. The cell mediated immune response expressed as delayed type hypersensitivity reaction was higher (P<0.05) in rats fed Zn propionate with no effect of other organic Zn sources. The serum progesterone concentration was higher (P<0.05) in rats fed organic Zn sources compared to inorganic zinc. The data on ovarian folliculogenesis indicated that organic Zn supplementation increased (P<0.05) the number of graafian follicles and corpus luteum with no effect on primary, secondary and tertiary follicle number. The study indicated that rats fed organic sources of Zn had higher antioxidant enzyme activities, immune response and serum progesterone concentration with higher number of mature follicles. Though the effect of feeding various organic sources were comparable, rats fed zinc methionine had higher antioxidant activity and cell mediated immune response was higher in rats on Zn propionate.

Keywords: organic zinc, immune, rats, reproductive

Procedia PDF Downloads 273

Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

Procedia PDF Downloads 116

Authors: Giuseppina Settanni, Antonio Panarese, Raffaele Vaira, Maurizio Galiano

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Nowdays, artificial intelligence is used successfully in academia and industry for its ability to learn from a large amount of data. In particular, in recent years the use of machine learning algorithms in the field of e-commerce has spread worldwide. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a chatbot and a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. The recommendation systems perform the important function of automatically filtering and personalizing information, thus allowing to manage with the IT overload to which the user is exposed on a daily basis. Recently, international research has experimented with the use of machine learning technologies with the aim to increase the potential of traditional recommendation systems. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Artificial intelligence algorithms have been implemented and trained on historical data collected from user browsing. Finally, the testing phase allowed to validate the implemented model, which will be further tested by letting customers use it.

Keywords: machine learning, recommender system, software platform, support vector machine

Procedia PDF Downloads 120

Authors: Mia Bahar, Özlem Bozkurt

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Obsessive-compulsive disorder (OCD) is a typical, persistent, and long-lasting mental health condition in which a person experiences uncontrollable, recurrent thoughts (or "obsessions") and/or activities (or "compulsions") that they feel compelled to engage in repeatedly. Obsessive-compulsive disorder is both underdiagnosed and undertreated. It frequently manifests in a variety of medical settings and is persistent, expensive, and burdensome. Obsessive-compulsive neurosis was long believed to be a condition that offered valuable insight into the inner workings of the unconscious mind. Obsessive-compulsive disorder is now recognized as a prime example of a neuropsychiatric condition susceptible to particular pharmacotherapeutic and psychotherapy therapies and mediated by pathology in particular neural circuits. An obsessive-compulsive disorder which is called OCD, usually has two components, one cognitive and the other behavioral, although either can occur alone. Obsessions are often repetitive and intrusive thoughts that invade consciousness. These obsessions are incredibly hard to control or dismiss. People who have OCD often engage in rituals to reduce anxiety associated with intrusive thoughts. Once the ritual is formed, the person may feel extreme relief and be free from anxiety until the thoughts of contamination intrude once again. These thoughts are strengthened through a manifestation of negative reinforcement because they allow the person to avoid anxiety and obscurity. These thoughts are described as autogenous, meaning they most likely come from nowhere. These unwelcome thoughts are related to actions which we can describe as Thought Action Fusion. The thought becomes equated with an action, such as if they refuse to perform the ritual, something bad might happen, and so people perform the ritual to escape the intrusive thought. In almost all cases of OCD, the person's life gets extremely disturbed by compulsions and obsessions. Studies show OCD is an estimated 1.1% prevalence, making it a challenging issue with high co-morbidities with other issues like depressive episodes, panic disorders, and specific phobias. The first to reveal brain anomalies in OCD were numerous CT investigations, although the results were inconsistent. A few studies have focused on the orbitofrontal cortex (OFC), anterior cingulate gyrus (AC), and thalamus, structures also implicated in the pathophysiology of OCD by functional neuroimaging studies, but few have found consistent results. However, some studies have found abnormalities in the basal ganglion. There have also been some discussions that OCD might be genetic. OCD has been linked to families in studies of family aggregation, and findings from twin studies show that this relationship is somewhat influenced by genetic variables. Some Research has shown that OCD is a heritable, polygenic condition that can result from de novo harmful mutations as well as common and unusual variants. Numerous studies have also presented solid evidence in favor of a significant additive genetic component to OCD risk, with distinct OCD symptom dimensions showing both common and individual genetic risks.

Keywords: compulsions, obsessions, neuropsychiatric, genetic

Procedia PDF Downloads 57

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 120

Authors: Nicholas S. Norbert Jr., John E. Bischoff, Christopher J. Willy

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Knowledge Management (KM) is globally recognized as a crucial element in securing competitive advantage through building and maintaining organizational memory, codifying and protecting intellectual capital and business intelligence, and providing mechanisms for collaboration and innovation. KM frameworks and approaches have been developed and defined identifying critical success factors for conducting KM within numerous industries ranging from scientific to business, and for ranges of organization scales from small groups to large enterprises. However, engineering and technical teams operating within restricted environments are subject to unique barriers and KM challenges which cannot be directly treated using the approaches and tools prescribed for other industries. This research identifies barriers in conducting KM within Hardware Development Engineering (HDE) teams and statistically compares significance to barriers upholding the four KM pillars of organization, technology, leadership, and learning for HDE teams. HDE teams suffer from restrictions in knowledge sharing (KS) due to classification of information (national security risks), customer proprietary restrictions (non-disclosure agreement execution for designs), types of knowledge, complexity of knowledge to be shared, and knowledge seeker expertise. As KM evolved leveraging information technology (IT) and web-based tools and approaches from Web 1.0 to Enterprise 2.0, KM may also seek to leverage emergent tools and analytics including expert locators and hybrid recommender systems to enable KS across barriers of the technical teams. The research will test hypothesis statistically evaluating if KM barriers for HDE teams affect the general set of expected benefits of a KM System identified through previous research. If correlations may be identified, then generalizations of success factors and approaches may also be garnered for HDE teams. Expert elicitation will be conducted using a questionnaire hosted on the internet and delivered to a panel of experts including engineering managers, principal and lead engineers, senior systems engineers, and knowledge management experts. The feedback to the questionnaire will be processed using analysis of variance (ANOVA) to identify and rank statistically significant barriers of HDE teams within the four KM pillars. Subsequently, KM approaches will be recommended for upholding the KM pillars within restricted environments of HDE teams.

Keywords: engineering management, knowledge barriers, knowledge management, knowledge sharing

Procedia PDF Downloads 256

Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

Procedia PDF Downloads 152

Authors: M. Çevik, S. Sabancı, D. Tezcan, C. Çelebi, F. İçier

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Ultrasound technology is the one of the non-thermal food processing method in recent years which has been used widely in the food industry. Ultrasound application in the food industry is divided into two groups: low and high intensity ultrasound application. While low intensity ultrasound is used to obtain information about physicochemical properties of foods, high intensity ultrasound is used to extract bioactive components and to inactivate microorganisms and enzymes. In this study, the ultrasound pre-treatment at a constant power (1500 W) and fixed frequency (20 kHz) was applied to the red beetroot slices having the dimension of 25×25×50 mm at the constant temperature (25°C) for different application times (0, 5, 10, 15 and 20 min). The red beet root slices pretreated with ultrasonication was squeezed immediately. The changes on rheological properties of red beet root juice depending on ultrasonication duration applied to slices were investigated. Rheological measurements were conducted by using Brookfield viscometer (LVDV-II Pro, USA). Shear stress-shear rate data was obtained from experimental measurements for 0-200 rpm range by using spindle 18. Rheological properties of juice were determined by fitting this data to some rheological models (Newtonian, Bingham, Power Law, Herschel Bulkley). It was investigated that the best model was Power Law model for both untreated red beet root juice (R2=0.991, χ2=0.0007, RMSE=0.0247) and red beetroot juice produced from ultrasonicated slices (R2=0.993, χ2=0.0006, RMSE=0.0216 for 20 min pre-treatment). k (consistency coefficient) and n (flow behavior index) values of red beetroot juices were not affected from the duration of ultrasonication applied to the slices. Ultrasound treatment does not result in any changes on the rheological properties of red beetroot juice. This can be explained by lack of ability to homogenize of the intensity of applied ultrasound.

Keywords: ultrasonication, rheology, red beet root slice, juice

Procedia PDF Downloads 390

Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil

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The paper is devoted to numerically investigating the influence of the air supply outlets geometry on human comfort inside living looms. A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The work focuses on air flow patterns, thermal behavior in the room with few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angles and velocity. Air supply diffusers locations and numbers were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software “Fluent 6.3” is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well-developed two equation turbulence model. In this work, the so-called standard k-ε turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on ADPI (Air Diffusion Performance Index),the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.

Keywords: thermal comfort, Fanger's model, ADPI, energy effeciency

Procedia PDF Downloads 398

Authors: Ionela-Daniela Carja, Diana Serbezeanu, Tachita Vlad-Bubulac, Corneliu Hamciuc

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Nowadays, epoxy materials are extensively used in ever more areas and under ever more demanding environmental conditions due to their remarkable combination of properties, light weight and ease of processing. However, these materials greatly increase the fire risk due to their flammability and possible release of toxic by-products as a result of their chemical composition which consists mainly from carbon and hydrogen atoms. Therefore, improving the fire retardant behaviour to prevent the loss of life and property is of particular concern among government regulatory bodies, consumers and manufacturers alike. Modification of epoxy resins with organophosphorus compounds, as reactive flame retardants or additives, is the key to achieving non-flammable advanced epoxy materials. Herein, a detailed characterization of fire behaviour for a series of phosphorus-containing epoxy thermosets is reported. A carefully designed phosphorus flame retardant additive was simply blended with a bifunctional bisphenol-A based epoxy resin. Further thermal cross-linking in the presence of various aminic hardeners led to eco-friendly flame retardant epoxy resins. The type of hardener, concentration of flame retardant additive, compatibility between the components of the mixture, char formation and morphology, thermal stability, flame retardant mechanisms were investigated. It was found that even a very low content of phosphorus introduced into the epoxy matrix increased the limiting oxygen index value to about 30%. In addition, the peak of the heat release rate value decreased up to 45% as compared to the one of the neat epoxy system. The main flame retardant mechanism was the condensed-phase one as revealed by SEM and XPS measurements.

Keywords: condensed-phase mechanism, eco-friendly phosphorus flame retardant, epoxy resin, thermal stability

Procedia PDF Downloads 296

Authors: K. Al Ammari, B. G. Clarke

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Soil improvement using vibro stone column techniques consists of two main parts: (1) the installed load bearing columns of well-compacted, coarse-grained material and (2) the improvements to the surrounding soil due to vibro compaction. Extensive research work has been carried out over the last 20 years to understand the improvement in the composite foundation performance due to the second part mentioned above. Nevertheless, few of these studies have tried to quantify some of the key design parameters, namely the changes in the stiffness and stress state of the treated soil, or have consider these parameters in the design and calculation process. Consequently, empirical and conservative design methods are still being used by ground improvement companies with a significant variety of results in engineering practice. Two-dimensional finite element study to develop an axisymmetric model of a single stone column reinforced foundation was performed using PLAXIS 2D AE to quantify the effect of the vibro installation of this column in soft saturated clay. Settlement and bearing performance were studied as an essential part of the design and calculation of the stone column foundation. Particular attention was paid to the large deformation in the soft clay around the installed column caused by the lateral expansion. So updated mesh advanced option was taken in the analysis. In this analysis, different degrees of stone column lateral expansions were simulated and numerically analyzed, and then the changes in the stress state, stiffness, settlement performance and bearing capacity were quantified. It was found that application of radial expansion will produce a horizontal stress in the soft clay mass that gradually decrease as the distance from the stone column axis increases. The excess pore pressure due to the undrained conditions starts to dissipate immediately after finishing the column installation, allowing the horizontal stress to relax. Changes in the coefficient of the lateral earth pressure K ٭, which is very important in representing the stress state, and the new stiffness distribution in the reinforced clay mass, were estimated. More encouraging results showed that increasing the expansion during column installation has a noticeable effect on improving the bearing capacity and reducing the settlement of reinforced ground, So, a design method should include this significant effect of the applied lateral displacement during the stone column instillation in simulation and numerical analysis design.

Keywords: bearing capacity, design, installation, numerical analysis, settlement, stone column

Procedia PDF Downloads 363

Authors: Maydariana Ayuningtyas, Bambang Riyanto, Akhiruddin Maddu

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Industrial waste of crustacean shells, such as shrimp and crab, has been considered as one of the major issues contributing to environmental pollution. The waste processing mechanisms to form new, practical substances with added value have been developed. Chitosan, a derived matter from chitin, which is obtained from crab and shrimp shells, performs prodigiously in broad range applications. A chitosan composite-based diaphragm is a new inspiration in fiber optic acoustic sensor advancement. Elastic modulus, dynamic response, and sensitivity to acoustic wave of chitosan-based composite film contribute great potentials of organic-based sound-detecting material. The objective of this research was to develop chitosan diaphragm application in fiber optic microphone system. The formulation was conducted by blending 5% polyvinyl alcohol (PVA) solution with dissolved chitosan at 0%, 1% and 2% in 1:1 ratio, respectively. Composite diaphragms were characterized for the morphological and mechanical properties to predict the desired acoustic sensor sensitivity. The composite with 2% chitosan indicated optimum performance with 242.55 µm thickness, 67.9% relative humidity, and 29-76% light transmittance. The Young’s modulus of 2%-chitosan composite material was 4.89×104 N/m2, which generated the voltage amplitude of 0.013V and performed sensitivity of 3.28 mV/Pa at 1 kHz. Based on the results above, chitosan from crustacean shell waste can be considered as a viable alternative material for fiber optic acoustic sensor sensing pad development. Further, the research in chitosan utilisation is proposed as novel optical microphone development in anthropogenic noise controlling effort for environmental and biodiversity conservation.

Keywords: acoustic sensor, chitosan, composite, crab shell, diaphragm, waste utilisation

Procedia PDF Downloads 244

Authors: Dinoo Kirthinanda, Sujani Wijeratne

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Pseudohyperkalaemia is a common benign in vitro phenomenon caused by the release of potassium ions (K+) from cells during specimen processing. Analysis of haemolysed blood samples for predominantly intracellular electrolytes may lead to re-investigation and potentially harmful interventions. We report a case of a 52-year male with myeloproliferative disease manifested as Polycythaemia Rubra Vera, Hypertension and hypertensive nephropathy with stage 3 chronic kidney disease admitted to Neuro-intensive care unit (NICU) with an intra-cerebral haemorrhage secondary to hypertensive bleed. His initial blood investigations showed hyperkalemia with serum K+ 6.2 mmol/L yet the bedside arterial blood gas analysis yielded K+ of 4.6 mmol/L. The patient was however given hyperkalemia regime twice based on venous electrolyte analysis. The discrepancy between the bedside electrolyte analysis using arterial blood and venous blood prompted further evaluation. The 12 lead Electrocardiogram showed U waves and sinus bradycardia corresponding to the serum K+ of 2.8 mmol/L on arterial blood gas analysis. Immediate K+ replacement ensured the patient did not develop life-threatening cardiac complications. Pseudohyperkalaemia may pose diagnostic challenges in the absence of detectable haemolysis and should be suspected in susceptible patients with normal Electrocardiogram and Glomerular Filtration Rate to avoid potentially life-threatening interventions. When in doubt, rapid analysis of arterial blood gas may be useful for accurate quantification of potassium.

Keywords: patient safety, pseudohyperkalaemia, haemolysis, myeloproliferative disorder

Procedia PDF Downloads 134

Authors: Hanna Schübel, Ivo Wallimann-Helmer

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In order to reach the goal of the Paris Agreement to not overshoot 1.5°C of warming above pre-industrial levels, various countries including the UK and Switzerland have committed themselves to net zero emissions by 2050. The employment of negative emission technologies (NETs) is very likely going to be necessary for meeting these national objectives as well as other internationally agreed climate targets. NETs are methods of removing carbon from the atmosphere and are thus a means for addressing climate change. They range from afforestation to technological measures such as direct air capture and carbon storage (DACCS), where CO2 is captured from the air and stored underground. As all so-called geoengineering technologies, the development and deployment of NETs are often subject to moral hazard arguments. As these technologies could be perceived as an alternative to mitigation efforts, so the argument goes, they are potentially a dangerous distraction from the main target of mitigating emissions. We think that this is a dangerous argument to make as it may hinder the development of NETs which are an essential element of net zero emission targets. In this paper we argue that the moral hazard argument is only problematic if we do not reflect upon which levels of emissions are at stake in order to meet net zero emissions. In response to the moral hazard argument we develop an account of which levels of emissions in given societies should be mitigated and not be the target of NETs and which levels of emissions can legitimately be a target of NETs. For this purpose, we define four different levels of emissions: the current level of individual emissions, the level individuals emit in order to appear in public without shame, the level of a fair share of individual emissions in the global budget, and finally the baseline of net zero emissions. At each level of emissions there are different subjects to be assigned responsibilities if societies and/or individuals are committed to the target of net zero emissions. We argue that all emissions within one’s fair share do not demand individual mitigation efforts. The same holds with regard to individuals and the baseline level of emissions necessary to appear in public in their societies without shame. Individuals are only under duty to reduce their emissions if they exceed this baseline level. This is different for whole societies. Societies demanding more emissions to appear in public without shame than the individual fair share are under duty to foster emission reductions and are not legitimate to reduce by introducing NETs. NETs are legitimate for reducing emissions only below the level of fair shares and for reaching net zero emissions. Since access to NETs to achieve net zero emissions demands technology not affordable to individuals there are also no full individual responsibilities to achieve net zero emissions. This is mainly a responsibility of societies as a whole.

Keywords: climate change, mitigation, moral hazard, negative emission technologies, responsibility

Procedia PDF Downloads 103

Authors: Hyehyeon Lee, Jiwon Yu, Juwon Kim, Raquel Kristina Leoni Tumiar, Taewon Kim, Juae Kim, Hongsuk Suh

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Photovoltaics, which have many advantages in cost, easy processing, and light-weight, have attracted attention. We synthesized pyrimidine-based conjugated polymers with 2-{4-[4,6-bis-(4-hexyl-thiophen-2-yl)-pyrimidin-2-yl]-phenyl}-thiazolo[5,4-b]pyridine (pPTP) which have an ability of powerful electron withdrawing and introduced into the PSCs. By Stille polymerization, we designed the conjugated polymers, pPTPBDT-12, pPTPBDT-EH, pPTPBDTT-EH and pPTPTTI. The HOMO energy levels of four polymers (pPTPBDT-12, pPTPBDT-EH, pPTPBDTT-EH and pPTPTTI) were at -5.61 ~ -5.89 eV, their LUMO (Lowest Unoccupied Molecular Orbital) energy levels were at -3.95 ~ -4.09 eV. The device including pPTPBDT-12 and PC71BM (1:2) indicated a V_oc of 0.67 V, a J_sc of 1.33 mA/cm², and a fill factor (FF) of 0.25, giving a power conversion efficiency (PCE) of 0.23%. The device including pPTPBDT-EH and PC71BM (1:2) indicated a V_oc of 0.72 V, a J_sc of 2.56 mA/cm², and a fill factor (FF) of 0.30, giving a power conversion efficiency of 0.56%. The device including pPTPBDTT-EH and PC71BM (1:2) indicated a V_oc of 0.72 V, a J_sc of 3.61 mA/cm², and a fill factor (FF) of 0.29, giving a power conversion efficiency of 0.74%. The device including pPTPTTI and PC71BM (1:2) indicated a V_oc of 0.83 V, a J_sc of 4.41 mA/cm², and a fill factor (FF) of 0.31, giving a power conversion efficiency of 1.13%. Therefore, pPTPBDT-12, pPTPBDT-EH, pPTPBDTT-EH, and pPTPTTI were synthesized by Stille polymerization. And We find one of the best efficiency for these polymers, called pPTPTTI. Their optical properties were measured and the results show that pyrimidine-based polymers especially like pPTPTTI have a great promise to act as the donor of the active layer.

Keywords: polymer solar cells, pyrimidine-based polymers, photovoltaics, conjugated polymer

Procedia PDF Downloads 183

Authors: Liu Yang

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Calligraphy has a unique aesthetic value in Chinese traditional culture. Calligraphy reflects the physical beauty and the dynamic beauty of things through the structure of writing and the order of strokes to standardize the style of writing. In recent years, Chinese researchers have carried out research on the appreciation of calligraphy works from the perspective of psychology, such as how Chinese people appreciate the beauty of stippled lines, the beauty of virtual and real, and the beauty of the composition. However, there is currently no domestic research on how foreigners appreciate Chinese calligraphy. People's appreciation of calligraphy is mainly in the form of visual perception, and psychologists have been working on the use of eye trackers to record eye tracking data to explore the relationship between eye tracking and psychological activities. The purpose of this experimental study is to use eye tracking recorders to analyze the eye gaze trajectories of college students with different cultural backgrounds when they appreciate the same calligraphy work to reveal the differences in cognitive processing with different cultural backgrounds. It was found that Chinese students perceived calligraphy as words when viewing calligraphy works, so they first noticed fonts with easily recognizable glyphs, and the overall viewed time was short. Foreign students perceived calligraphy works as graphics, and they first noticed novel and abstract fonts, and the overall viewing time is longer. The understanding of calligraphy content has a certain influence on the appreciation of calligraphy works by foreign students. It is shown that when foreign students who understand the content of calligraphy works. The eye tracking path is more consistent with the calligraphy writing path, and it helps to develop associations with calligraphy works to better understand the connotation of calligraphy works. This result helps us understand the impact of cultural background differences on calligraphy appreciation and helps us to take more effective strategies to help foreign audiences understand Chinese calligraphy art.

Keywords: Chinese calligraphy, eye-tracking, cross-cultural, cultural communication

Procedia PDF Downloads 91

Authors: Anicet Dansou

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Textile reinforced concrete (TRC)is increasingly used nowadays in various fields, in particular civil engineering, where it is mainly used for the reinforcement of damaged reinforced concrete structures. TRC is a composite material composed of multi- or uni-axial textile reinforcements coupled with a fine-grained cementitious matrix. The TRC composite is an alternative solution to the traditional Fiber Reinforcement Polymer (FRP) composite. It has good mechanical performance and better temperature stability but also, it makes it possible to meet the criteria of sustainable development better.TRCs are highly anisotropic composite materials with nonlinear hardening behavior; their macroscopic behavior depends on multi-scale mechanisms. The characterization of these materials through numerical simulation has been the subject of many studies. Since TRCs are multiscale material by definition, numerical multi-scale approaches have emerged as one of the most suitable methods for the simulation of TRCs. They aim to incorporate information pertaining to microscale constitute behavior, mesoscale behavior, and macro-scale structure response within a unified model that enables rapid simulation of structures. The computational costs are hence significantly reduced compared to standard simulation at a fine scale. The fine scale information can be implicitly introduced in the macro scale model: approaches of this type are called non-classical. A representative volume element is defined, and the fine scale information are homogenized over it. Analytical and computational homogenization and nested mesh methods belong to these approaches. On the other hand, in classical approaches, the fine scale information are explicitly introduced in the macro scale model. Such approaches pertain to adaptive mesh refinement strategies, sub-modelling, domain decomposition, and multigrid methods This research presents the main principles of numerical multiscale approaches. Advantages and limitations are identified according to several criteria: the assumptions made (fidelity), the number of input parameters required, the calculation costs (efficiency), etc. A bibliographic study of recent results and advances and of the scientific obstacles to be overcome in order to achieve an effective simulation of textile reinforced concrete in civil engineering is presented. A comparative study is further carried out between several methods for the simulation of TRCs used for the structural reinforcement of reinforced concrete structures.

Keywords: composites structures, multiscale methods, numerical modeling, textile reinforced concrete

Procedia PDF Downloads 93

Authors: Meng Miao, Jeongwoo Han, Cam Nguyen

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Ultra-wideband (UWB) time-domain impulse communication and radar systems use ultra-short duration pulses in the sub-nanosecond regime, instead of continuous sinusoidal waves, to transmit information. The pulse directly generates a very wide-band instantaneous signal with various duty cycles depending on specific usages. In UWB systems, the total transmitted power is spread over an extremely wide range of frequencies; the power spectral density is extremely low. This effectively results in extremely small interference to other radio signals while maintains excellent immunity to interference from these signals. UWB devices can therefore work within frequencies already allocated for other radio services, thus helping to maximize this dwindling resource. Therefore, impulse UWB technique is attractive for realizing high-data-rate, short-range communications, ground penetrating radar (GPR), and military radar with relatively low emission power levels. UWB antennas are the key element dictating the transmitted and received pulse shape and amplitude in both time and frequency domain. They should have good impulse response with minimal distortion. To facilitate integration with transmitters and receivers employing microwave integrated circuits, UWB antennas enabling direct integration are preferred. We present the development of two UWB antennas operating from 3.1 to 10.6 GHz and 0.3-6 GHz for UWB systems that provide direct integration with microwave integrated circuits. The operation of these antennas is based on the principle of wave propagation on a non-uniform transmission line. Time-domain EM simulation is conducted to optimize the antenna structures to minimize reflections occurring at the open-end transition. Calculated and measured results of these UWB antennas are presented in both frequency and time domains. The antennas have good time-domain responses. They can transmit and receive pulses effectively with minimum distortion, little ringing, and small reflection, clearly demonstrating the signal fidelity of the antennas in reproducing the waveform of UWB signals which is critical for UWB sensors and communication systems. Good performance together with seamless microwave integrated-circuit integration makes these antennas good candidates not only for UWB applications but also for integration with printed-circuit UWB transmitters and receivers.

Keywords: antennas, ultra-wideband, UWB, UWB communication systems, UWB radar systems

Procedia PDF Downloads 223

Authors: Longxiang Guo, Haoyan Hao, Xueli Sheng, Hanjun Yu, Jingwei Yin

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In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration.

Keywords: data fusion, multi-static sonar detection, offline estimation, sensor registration problem

Procedia PDF Downloads 153

Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

Procedia PDF Downloads 94

Authors: Emine Yılmaz, Serap Fındık

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Baker’s yeast industry uses molasses as a raw material. Molasses is end product of sugar industry. Wastewater from molasses processing presents large amount of coloured substances that give dark brown color and high organic load to the effluents. The main coloured compounds are known as melanoidins. Melanoidins are product of Maillard reaction between amino acid and carbonyl groups in molasses. Dark colour prevents sunlight penetration and reduces photosynthetic activity and dissolved oxygen level of surface waters. Various methods like biological processes (aerobic and anaerobic), ozonation, wet air oxidation, coagulation/flocculation are used to treatment of baker’s yeast effluent. Before effluent is discharged adequate treatment is imperative. In addition to this, increasingly stringent environmental regulations are forcing distilleries to improve existing treatment and also to find alternative methods of effluent management or combination of treatment methods. Sonochemical oxidation is one of the alternative methods. Sonochemical oxidation employs ultrasound resulting in cavitation phenomena. In this study, decolorization of baker’s yeast effluent was investigated by using ultrasound. Baker’s yeast effluent was supplied from a factory which is located in the north of Turkey. An ultrasonic homogenizator used for this study. Its operating frequency is 20 kHz. TiO2-ZnO catalyst has been used as sonocatalyst. The effects of molar proportion of TiO2-ZnO, calcination temperature and time, catalyst amount were investigated on the decolorization of baker’s yeast effluent. The results showed that prepared composite TiO2-ZnO with 4:1 molar proportion treated at 700°C for 90 min provides better result. Initial decolorization rate at 15 min is 3% without catalyst, 14,5% with catalyst treated at 700°C for 90 min respectively.

Keywords: baker’s yeast effluent, decolorization, sonocatalyst, ultrasound

Procedia PDF Downloads 454