Search results for: spatial audio processing

Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori

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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.

Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing

Procedia PDF Downloads 132

Authors: Antonio Gioiosa, Simone Doanti, Eric Flumerfelt, Luca Morescalchi, Elena Pedreschi, Gianantonio Pezzullo, Ryan A. Rivera, Franco Spinella

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The Mu2e experiment at Fermilab aims to measure the charged-lepton flavour violating neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. With the expected experimental sensitivity, Mu2e will improve the previous limit of four orders of magnitude. The Mu2e data acquisition (DAQ) system provides hardware and software to collect digitized data from the tracker, calorimeter, cosmic ray veto, and beam monitoring systems. Mu2e’s trigger and data acquisition system (TDAQ) uses otsdaq as its solution. developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under-the-hood, for event transfer, filtering, and processing. Otsdaq is an online DAQ software suite with a focus on flexibility and scalability while providing a multi-user, web-based interface accessible through the Chrome or Firefox web browser. The detector read out controller (ROC) from the tracker and calorimeter stream out zero-suppressed data continuously to the data transfer controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes from a cosmic ray veto system (CRV).

Keywords: trigger, daq, mu2e, Fermilab

Procedia PDF Downloads 155

Authors: Mayowa Philips Ibitola, Abe Oluwaseun Banji, Olorunfemi Akinade-Solomon

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A total of 20 bottom sediment samples were collected from the Lekki Lagoon during the wet and dry season. The study was carried out to determine the textural characteristics, sediment distribution pattern and energy of transportation within the lagoon system. The sediment grain sizes and depth profiling was analyzed using dry sieving method and MATLAB algorithm for processing. The granulometric reveals fine grained sand both for the wet and dry season with an average mean value of 2.03 ϕ and -2.88 ϕ, respectively. Sediments were moderately sorted with an average inclusive standard deviation of 0.77 ϕ and -0.82 ϕ. Skewness varied from strongly coarse and near symmetrical 0.34- ϕ and 0.09 ϕ. The kurtosis average value was 0.87 ϕ and -1.4 ϕ (platykurtic and leptokurtic). Entirely, the bathymetry shows an average depth of 4.0 m. The deepest and shallowest area has a depth of 11.2 m and 0.5 m, respectively. High concentration of fine sand was observed at deep areas compared to the shallow areas during wet and dry season. Statistical parameter results show that the overall sediments are sorted, and deposited under low energy condition over a long distance. However, sediment distribution and sediment transport pattern of Lekki Lagoon is controlled by a low energy current and the down slope configuration of the bathymetry enhances the sorting and the deposition rate in the Lekki Lagoon.

Keywords: Lekki Lagoon, Marine sediment, bathymetry, grain size distribution

Procedia PDF Downloads 231

Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

Procedia PDF Downloads 128

Authors: Stephanie Ducrot, Marie Vernet, Eve Meiss, Yves Chaix

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Learning to read is a key topic of debate today, both in terms of its implications on school failure and illiteracy and regarding what are the best teaching methods to develop. It is estimated today that four to six percent of school-age children suffer from specific developmental disorders that impair learning. The findings from people with dyslexia and typically developing readers suggest that the problems children experience in learning to read are related to the preliteracy skills that they bring with them from kindergarten. Most tools available to professionals are designed for the evaluation of child language problems. In comparison, there are very few tools for assessing the relations between visual skills and the process of learning to read. Recent literature reports that visual-motor skills and visual-spatial attention in preschoolers are important predictors of reading development — the main goal of this study aimed at improving screening for future reading difficulties in preschool children. We used a prospective, longitudinal approach where oculomotor processes (assessed with the DiagLECT test) were measured in pre-readers, and the impact of these skills on future reading development was explored. The dialect test specifically measures the online time taken to name numbers arranged irregularly in horizontal rows (horizontal time, HT), and the time taken to name numbers arranged in vertical columns (vertical time, VT). A total of 131 preschoolers took part in this study. At Time 0 (kindergarten), the mean VT, HT, errors were recorded. One year later, at Time 1, the reading level of the same children was evaluated. Firstly, this study allowed us to provide normative data for a standardized evaluation of the oculomotor skills in 5- and 6-year-old children. The data also revealed that 25% of our sample of preschoolers showed oculomotor impairments (without any clinical complaints). Finally, the results of this study assessed the validity of the DiagLECT test for predicting reading outcomes; the better a child's oculomotor skills are, the better his/her reading abilities will be.

Keywords: vision, attention, oculomotor processes, reading, preschoolers

Procedia PDF Downloads 147

Authors: Roya Biabani, Mentore Vaccari, Piero Ferrari

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Accumulated microplastic (MPLs) in soil pose the risk of adsorbing and transporting polychlorinated biphenyls (PCBs) into the food chain or bodies. PCBs belong to a class of man-made hydrophobic organic chemicals (HOCs) that are classified as probable human carcinogens and a hazard to biota. Therefore, to take effective action and not aggravate the already recognized problems, the knowledge of PCB remediation in the presence of MPLs needs to be complete. Due to the high efficiency and little secondary pollution production, thermal desorption (TD) has been widely used for processing a variety of pollutants, especially for removing volatile and semi-volatile organic matter from contaminated solids and sediment. This study investigates the fate of PCB compounds during the thermal remediation method. For this, the PCB-contaminated soil was collected from the earth-canal downstream Caffaro S.p.A. chemical factory, which produced PCBs and PCB mixtures between 1930 and 1984. For MPL analysis, MPLs were separated by density separation and oxidation of organic matter. An operational range for the key parameters of thermal desorption processes was experimentally evaluated. Moreover, the temperature treatment characteristics of the PCBs-contaminated soil under anaerobic and aerobic conditions were studied using the Thermogravimetric Analysis (TGA).

Keywords: contaminated soils, microplastics, polychlorinated biphenyls, thermal desorption

Procedia PDF Downloads 104

Authors: Guozhen Li, Philip Hall, Nick Miles, Tao Wu

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This paper presents a numerical investigation of two horizontally mounted four-lobed swirl pipes in terms of swirl induction effectiveness into flows passing through them. The swirl flows induced by the two swirl pipes have the potential to improve the efficiency of Clean-In-Place procedures in a closed processing system by local intensification of hydrodynamic impact on the internal pipe surface. Pressure losses, swirl development within the two swirl pipe, swirl induction effectiveness, swirl decay and wall shear stress variation downstream of two swirl pipes are analyzed and compared. It was found that a shorter length of swirl inducing pipe used in joint with transition pipes is more effective in swirl induction than when a longer one is used, in that it has a less constraint to the induced swirl and results in slightly higher swirl intensity just downstream of it with the expense of a smaller pressure loss. The wall shear stress downstream of the shorter swirl pipe is also slightly larger than that downstream of the longer swirl pipe due to the slightly higher swirl intensity induced by the shorter swirl pipe. The advantage of the shorter swirl pipe in terms of swirl induction is more significant in flows with a larger Reynolds Number.

Keywords: swirl pipe, swirl effectiveness, CFD, wall shear stress, swirl intensity

Procedia PDF Downloads 606

Authors: Ioan Corneliu Salisteanu, Valentin Dogaru Ulieru, Mihaita Nicolae Ardeleanu, Alin Pohoata, Bogdan Salisteanu, Stefan Broscareanu

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Creating a personalized statistic for an individual within the population using IT systems, based on the searches and intercepted spheres of interest they manifest, is just one 'atom' of the artificial intelligence analysis network. However, having the ability to generate statistics based on individual data intercepted from large demographic areas leads to reasoning like that issued by a human mind with global strategic ambitions. The DiaMOTO device is a technical sensory system that allows the interception of car events caused by a driver, positioning them in time and space. The device's connection to the vehicle allows the creation of a source of data whose analysis can create psychological, behavioural profiles of the drivers involved. The SiaMOTO system collects data from many vehicles equipped with DiaMOTO, driven by many different drivers with a unique fingerprint in their approach to driving. In this paper, we aimed to explain the software infrastructure of the SiaMOTO system, a system designed to monitor and improve driver driving behaviour, as well as the criteria and algorithms underlying the intelligent analysis process.

Keywords: artificial intelligence, data processing, driver behaviour, driver monitoring, SiaMOTO

Procedia PDF Downloads 91

Authors: David Downey

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With the introduction of additive manufacturing (3D printing) to produce titanium (Ti6Al4V) components in the medical/aerospace and automotive industries, intricate geometries can be produced with virtually complete design freedom. However, the consideration of microstructural anisotropy resulting from the additive manufacturing process becomes necessary due to this design flexibility and the need to print a geometric shape that can consist of numerous angles, radii, and swept surfaces. A femoral knee implant serves as an example of a 3D-printed near-net-shaped product. The mechanical properties of the printed components, and consequently, their machinability, are affected by microstructural anisotropy. Currently, finish-machining operations performed on titanium printed parts using selective laser melting (SLM) utilize the same cutting tools employed for processing wrought titanium components. Cutting forces for components manufactured through SLM can be up to 70% higher than those for their wrought counterparts made of Ti6Al4V. Moreover, temperatures at the cutting interface of 3D printed material can surpass those of wrought titanium, leading to significant tool wear. Although the criteria for tool wear may be similar for both 3D printed and wrought materials, the rate of wear during the machining process may differ. The impact of these issues on the choice of cutting tool material and tool lifetimes will be discussed.

Keywords: additive manufacturing, build orientation, microstructural anisotropy, printed titanium Ti6Al4V, tool wear

Procedia PDF Downloads 91

Authors: Rahul Warmoota, Aditya Bhardwaj, Steffy Angural, Monika Rana, Sunena Jassal, Neena Puri, Naveen Gupta

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Seafood processing generates large volumes of waste products such as skin, heads, tails, shells, scales, backbones, etc. Pollution due to conventional methods of seafood waste disposal causes negative implications on the environment, aquatic life, and human health. Moreover, these waste products can be used for the production of high-value products which are still untapped due to inappropriate management. Paenibacillus sp. AD is known to act on chitinolytic and proteinaceous waste and was explored for its potential to degrade various types of seafood waste in solid-state fermentation. Effective degradation of seafood waste generated from a variety of sources such as fish scales, crab shells, prawn shells, and a mixture of such wastes was observed. 30 to 40 percent degradation in terms of decrease in the mass was achieved. Along with the degradation, chitinolytic and proteolytic enzymes were produced, which can have various biotechnological applications. Apart from this, value-added products such as chitin oligosaccharides and peptides of various degrees of polymerization were also produced, which can be used for various therapeutic purposes. Results indicated that Paenibacillus sp. AD can be used for the development of a process for the infield degradation of seafood waste.

Keywords: chitin, chitin-oligosaccharides, chitinase, protease, biodegradation, crab shells, prawn shells, fish scales

Procedia PDF Downloads 98

Authors: Hemabushan K., Manikandan

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In a swirl atomizer, fluid undergoes a swirling motion as a result of centrifugal force created by opposed tangential inlets in the swirl chamber. The angular momentum of fluid continually increases as it reaches the exit orifice and forms a hollow sheet. Which disintegrates to form ligaments and droplets respectively as it flows downstream. This type of atomizers used in rocket injectors and oil burner furnaces. In this present investigation a swirl atomizer with two opposed tangential inlets has been designed. Water as working fluid, experiments had been conducted for the fluid injection pressures in regime of 0.033 bar to 0.519 bar. The fluid has been pressured by a 0.5hp pump and regulated by a pressure regulator valve. Injection pressure of fluid has been measured by a U-tube mercury manometer. The spray pattern and the droplets has been captured with a high resolution camera in black background with a high intensity flash highlighting the fluid. The unprocessed images were processed in ImageJ processing software for measuring the droplet diameters and its shape characteristics along the downstream. The parameters such as mean droplet diameter and distribution, wave pattern, rupture distance and spray angle were studied for this atomizer. The above results were compared with theoretical results and also analysed for deviation with design parameters.

Keywords: swirl atomizer, injector, spray, SWIRL

Procedia PDF Downloads 490

Authors: Jesha Faye T. Librea, Leslie Joy L. Diaz

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Fuel-derived rice husk ash (fRHA) is a waste material from industries employing rice husk as a biomass fuel which, on the downside, causes disposal and environmental problems. To mitigate this, the fRHA was evaluated for use in other applications such as a pozzolanic material for the construction industry. In this study, the assessment of the potential of fRHA as pozzolanic supplementary cementitious material was conducted by determining the chemical and physical properties of fRHA according to ASTM C618, evaluating the fineness of the material according to ASTM C430, and determining its pozzolanic activity using Luxan Method. The material was found to have a high amorphous silica content of around 95.82 % with traces of alkaline and carbon impurities. The retained carbon residue is 7.18 %, which is within the limit of the specifications for natural pozzolans indicated in ASTM C618. The fineness of the fRHA is at 88.88 % retained at a 45-micron sieve, which, however, exceeded the limit of 34 %. This large particle size distribution was found to affect the pozzolanic activity of the fRHA. This was shown in the Luxan test, where the fRHA was identified as non-pozzolan due to its low pozzolanic activity index of 0.262. Thus, further processing must be done to the fRHA to pass the required ASTM fineness, have a higher pozzolanic activity index, and fully qualify as a pozzolanic material.

Keywords: rice husk ash, pozzolanic, fuel-derived ash, supplementary cementitious material

Procedia PDF Downloads 66

Authors: Kung-Jen Tu

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Many public housing properties developed by local governments in Taiwan in the 1980s have deteriorated severely as these rental apartment buildings aged. The lack of building maintainability considerations during project design phase as well as insufficient maintenance funds have made it difficult and costly for local governments to maintain and keep public housing properties in good shape. In order to assist the local governments in achieving and delivering sustainable public housing, this paper intends to present a developed design evaluation method to be used to evaluate the presented design schemes from property management and financial feasibility perspectives during project design phase of public housing projects. The design evaluation results, i.e. the property management and financial implications of presented design schemes that could occur later during the building operation and maintenance phase, will be reported to the client (the government) and design schemes revised consequently. It is proposed that the design evaluation be performed from two main perspectives: (1) Operation and property management perspective: Three criteria such as spatial appropriateness, people and vehicle circulation and control, property management working spaces are used to evaluate the ‘operation and PM effectiveness’ of a design scheme. (2) Financial feasibility perspective: Four types of financial analyses are performed to assess the long term financial feasibility of a presented design scheme, such as operational and rental income analysis, management fund analysis, regular operational and property management service expense analysis, capital expense analysis. The ongoing Chung-Li Public Housing Project developed by the Taoyuan City Government will be used as a case to demonstrate how the presented design evaluation method is implemented. The results of property management assessment as well as the annual operational and capital expenses of a proposed design scheme are presented.

Keywords: design evaluation method, management fund, operational and capital expenses, rental apartment buildings

Procedia PDF Downloads 307

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

Procedia PDF Downloads 111

Authors: Minh Nguyen

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Today, QR or Quick Response Codes are prevalent, and mobile/smart devices can efficiently read and understand them. Therefore, we can see their appearance in many areas, such as storing web pages/websites, business phone numbers, redirecting to an app download, business location, social media. The popularity of the QR Code is mainly because of its many advantages, such as it can hold a good amount of information, is small, easy to scan and read by a general RGB camera, and it can still work with some damages on its surface. However, there are still some issues. For instance, some areas needed to be kept untouched for its successful decode (e.g., the “Finder Patterns,” the “Quiet Zone,” etc.), the capability of built-in auto-correction is not robust enough, and it is not flexible enough for many application such as Augment Reality (AR). We proposed a new Colour Quick Response Code that has several advantages over the original ones: (1) there is no untouchable area, (2) it allows up to 40% of the entire code area to be damaged, (3) it is more beneficial for Augmented Reality applications, and (4) it is back-compatible and readable by available QR Code scanners such as Pyzbar. From our experience, our Colour Quick Response Code is significantly more flexible on damage compared to the original QR Code. Our code is believed to be suitable in situations where standard 2D Barcodes fail to work, such as curved and shiny surfaces, for instance, medical blood test sample tubes and syringes.

Keywords: QR code, computer vision, image processing, 2D barcode

Procedia PDF Downloads 118

Authors: Rakesh Prajapati, Purvik Patel, Avadhoot Rajurkar

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Nowadays, manufacturing industries augment their production lines with modern machining centers backed by CAM software. Several attempts are being made to cut down the programming time for machining complex geometries. Special programs/software have been developed to generate the digital numerical data and to prepare NC programs by using suitable post-processors for different machines. By selecting the tools and manufacturing process then applying tool paths and NC program are generated. More and more complex mechanical parts that earlier were being cast and assembled/manufactured by other processes are now being machined. Majority of these parts require lots of pocketing operations and find their applications in die and mold, turbo machinery, aircraft, nuclear, defense etc. Pocketing operations involve removal of large quantity of material from the metal surface. The modeling of warm cast and clamping a piece of food processing parts which the used of Pro-E and MasterCAM^® software. Pocketing operation has been specifically chosen for toolpath optimization. Then after apply Pocketing toolpath, Multi Tool Selection and Reduce Air Time give the results of software simulation time and experimental machining time.

Keywords: toolpath, part program, optimization, pocket

Procedia PDF Downloads 288

Authors: Md. Refat Jahan Rakiba, M. Belal Hossaina, Rakesh Kumarc, Md. Akram Ullaha, Sultan Al Nahiand, Nazmun Naher Rimaa, Tasrina Rabia Choudhury, Samia Islam Libaf, Jimmy Yub, Mayeen Uddin Khandakerg, Abdelmoneim Suliemanh, Mohamed Mahmoud Sayedi

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Microplastics (MPs) have become an emerging global pollutant due to their wide spread and dispersion and potential threats to marine ecosystems. However, studies on MPs of estuarine and coastal ecosystems of Bangladesh are very limited or not available. In this study, we conducted the first study on the abundance, distribution, characteristics and potential risk assessment of microplastics in the sediment of Karnaphuli River estuary, Bangladesh. Microplastic particles were extracted from sediments of 30 stations along the estuary by density separation, and then enumerated and characterize by using steromicroscope and Fourier Transform Infrared (FT-IR) spectroscopy. In the collected sediment, the number of MPs varied from 22.29 - 59.5 items kg−1 of dry weight (DW) with an average of 1177 particles kg−1 DW. The mean abundance was higher in the downstream and left bank of estuary where the predominant shape, colour, and size of MPs were films (35%), white (19%), and >5000 μm (19%), respectively. The main polymer types were polyethylene terephthalate, polystyrene, polyethylene, cellulose, and nylon. MPs were found to pose risks (low to high) in the sediment of the estuary, with the highest risk occuring at one station near a sewage outlet, according to the results of risk analyses using the pollution risk index (PRI), polymer risk index (H), contamination factors (CFs), and pollution load index (PLI). The single value index, PLI clearly demonastated that all sampling sites were considerably polluted (as PLI >1) with microplastics. H values showed toxic polymers even in lower proportions possess higher polymeric hazard scores and vice versa. This investigation uncovered new insights on the status of MPs in the sediments of Karnaphuli River estuary, laying the groundwork for future research and control of microplastic pollution and management.

Keywords: microplastics, polymers, pollution risk assessment, Karnaphuli esttuary

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

Procedia PDF Downloads 112

Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park

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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.

Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement

Procedia PDF Downloads 235

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

Procedia PDF Downloads 218

Authors: S. Aouabdi, M. Taibi

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The supervision of chemical processes is the subject of increased development because of the increasing demands on reliability and safety. An important aspect of the safe operation of chemical process is the earlier detection of (process faults or other special events) and the location and removal of the factors causing such events, than is possible by conventional limit and trend checks. With the aid of process models, estimation and decision methods it is possible to also monitor hundreds of variables in a single operating unit, and these variables may be recorded hundreds or thousands of times per day. In the absence of appropriate processing method, only limited information can be extracted from these data. Hence, a tool is required that can project the high-dimensional process space into a low-dimensional space amenable to direct visualization, and that can also identify key variables and important features of the data. Our contribution based on powerful techniques for development of a new monitoring method based on multi-scale entropy MSE in order to characterize the behaviour of the concentrations of different gases present in synthesis and soft sensor based on PCA is applied to estimate these variables.

Keywords: ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivarite statistics

Procedia PDF Downloads 336

Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

Procedia PDF Downloads 50

Authors: Gordana S. Ćetković, Vesna T. Tumbas Šaponjac, Sonja M. Djilas, Jasna M. Čanadanović-Brunet, Sladjana M. Stajčić, Jelena J. Vulić

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Bilberry is one of the most important dietary sources of phenolic compounds, including anthocyanins, phenolic acids, flavonol glycosides and flavan-3-ols. These phytochemicals have different biological activities and therefore may improve our health condition. Also, anthocyanins are interesting to the food industry as colourants. In the present study, bilberry pomace, a by-product of juice processing, was used as a potential source of bioactive compounds. The contents of total phenolic acids, flavonoids and anthocyanins in bilberry pomace were determined by HPLC/UV-Vis. The biological activities of bilberry pomace were evaluated by reducing power (RP) and α-glucosidase inhibitory potential (α-GIP), and expressed as RP0.5 value (the effective concentration of bilberry pomace extract assigned at 0.5 value of absorption) and IC50 value (the concentration of bilberry pomace extract necessary to inhibit 50% of α-glucosidase enzyme activity). Total phenolic acids content was 807.12 ± 25.16 mg/100 g pomace, flavonoids 54.36 ± 1.83mg/100 g pomace and anthocyanins 3426.18 ± 112.09 mg/100 g pomace. The RP0.5 value of bilberry pomace was 0.38 ± 0.02 mg/ml, while IC50 value was 1.82 ± 0.11 mg/ml. These results have revealed the potential for valorization of bilberry juice production by-products for further industrial use as a rich source of bioactive compounds and natural colourants (mainly anthocyanins).

Keywords: bilberry pomace, phenolics, antioxidant activity, reducing power, α-glucosidase enzyme activity

Procedia PDF Downloads 599

Authors: Ning Kang, Marius Doornenbal

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Funding is a very important – if not crucial – resource for research projects. Usually, funding organizations will publish a description of the funded research to describe the scope of the funding award. Logically, we would expect research outcomes to align with this funding award. For that reason, we might be able to predict future research topics based on present funding award data. That said, it remains to be shown if and how future research topics can be predicted by using the funding information. In this paper, we extract funding project information and their generated paper abstracts from the Gateway to Research database as a group, and use the papers from the same domains and publication years in the Scopus database as a baseline comparison group. We annotate both the project awards and the papers resulting from the funded projects with linguistic features (noun phrases), and then calculate tf-idf and cosine similarity between these two set of features. We show that the cosine similarity between the project-generated papers group is bigger than the project-baseline group, and also that these two groups of similarities are significantly different. Based on this result, we conclude that the funding information actually correlates with the content of future research output for the funded project on the topical level. How funding really changes the course of science or of scientific careers remains an elusive question.

Keywords: natural language processing, noun phrase, tf-idf, cosine similarity

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Authors: Assia Amri, Naima Layachi, Ali Ladjama

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The characterization of some Algerian honey was carried out on the basis of their physico-chemical properties: moisture,hydroxy methyl furfural, diastase activity, pH,free, total and lactonic acidity, electrical conductivity, minerals and proline content. Studied samples are found to be low in moisture and therefore safe from fermentation, low in HMF level and high in diastase activity. Additionally the diastase activity and the HMF content are widely recognized parameters indicating the freshness of honey. Phenolic compounds present in honey are classified into two groups - simple phenols and polyphenols. The simple phenols in honey are various phenol acids, but polyphenols are various flavonoids and flavonides. The aim of our work was to determine antioxidant properties of various Algerian honey samples–the total phenol content, total flavonoids content, as well as honey anti radical activity.The quality of honey samples differs on account of various factors such as season, packaging and processing conditions, floral source, geographical origin and storage period. It is important that precautions should be taken to ensure standardization and rationalization of beekeeping techniques, manufacturing procedures and storing processes to improve honey quality.

Keywords: honey, physico-chemical characterization, phenolic coumpound, HMF, diastase activity

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Authors: Martin Klaumünzer, Jakob Hübner, Denis Spitzer

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Within this paper, latest results on processing of energetic nanomaterials by means of the Spray Flash Evaporation technique are presented. This technology constitutes a highly effective and continuous way to prepare fascinating materials on the nano- and micro-scale. Within the process, a solution is set under high pressure and sprayed into an evacuated atomization chamber. Subsequent ultrafast evaporation of the solvent leads to an aerosol stream, which is separated by cyclones or filters. No drying gas is required, so the present technique should not be confused with spray dying. Resulting nanothermites, insensitive explosives or propellants and compositions are foreseen to replace toxic (according to REACH) and very sensitive matter in military and civil applications. Diverse examples are given in detail: nano-RDX (n-Cyclotrimethylentrinitramin) and nano-aluminum based systems, mixtures (n-RDX/n-TNT - trinitrotoluene) or even cocrystalline matter like n-CL-20/HMX (Hexanitrohexaazaisowurtzitane/ Cyclotetra-methylentetranitramin). These nanomaterials show reduced sensitivity by trend without losing effectiveness and performance. An analytical study for material characterization was performed by using Atomic Force Microscopy, X-Ray Diffraction, and combined techniques as well as spectroscopic methods. As a matter of course, sensitivity tests regarding electrostatic discharge, impact, and friction are provided.

Keywords: continuous synthesis, energetic material, nanoscale, nanoexplosive, nanothermite

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Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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Authors: Liseane Padilha Thives, Mayara S. S. Lima, João Victor Staub De Melo, Glicério Trichês

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Red mud is a waste resulting from the processing of bauxite to alumina, the raw material of the production of aluminum. The large quantity of red mud generated and inadequately disposed in the environment has motivated researchers to develop methods for reinsertion of this waste into the productive cycle. This work aims to evaluate the resistance to permanent deformation of dense asphalt mixtures with red mud filler. The red mud was characterized by tests of X-ray diffraction, fluorescence, specific mass, laser granulometry, pH and scanning electron microscopy. For the analysis of the influence of the quantity of red mud in the mechanical performance of asphalt mixtures, a total filler content of 7% was established. Asphalt mixtures with 3%, 5% and 7% red mud were produced. A conventional mixture with 7% stone powder filler was used as reference. The asphalt mixtures were evaluated for performance to permanent deformation in the French Rutting Tester (FRT) traffic simulator. The mixture with 5% red mud presented greater resistance to permanent deformation with rutting depth at 30,000 cycles of 3.50%. The asphalt mixtures with red mud presented better performance, with reduction of the rutting of 12.63 to 42.62% in relation to the reference mixture. This study confirmed the viability of reinserting the red mud in the production chain and possible usage in the construction industry. The red mud as filler in asphalt mixtures is a reuse option of this waste and mitigation of the disposal problems, as well as being an environmentally friendly alternative.

Keywords: asphalt mixtures, permanent deformation, red mud, pavements

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Authors: Dina Helmy El-Ghonemy, Thanaa Hamed Ali

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The aim of this study was to purify and characterize a keratinolytic enzyme produced by Aspergillus sp. DHE7 cultured in basal medium containing chicken feather as substrate. The enzyme was purified through ammonium sulfate saturation of 60%, followed by gel filtration chromatography in Sephadex G-100, with a 16.4-purification fold and recovery yield of 52.2%. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis revealed that the purified enzyme is a monomeric enzyme with an apparent molecular mass of 30 kDa — the purified keratinase of Aspergillus sp. DHE7 exhibited activity in a broad range of pH (7- 9) and temperature (40℃-60℃) profiles with an optimal activity at pH eight and 50℃. The keratinolytic activity was inhibited by protease inhibitors such as phenylmethylsulfonyl fluoride and ethylenediaminetetraacetate, while no reduction of activity was detected by the addition of dimethyl sulfoxide (DMSO). Bivalent cations, Ca²⁺ and Mn²⁺, were able to greatly enhance the activity of keratinase by 125.7% and 194.8%, respectively, when used at one mM final concentration. On the other hand, Cu²⁺ and Hg²⁺ inhibited the enzyme activity, which might be indicative of essential vicinal sulfhydryl groups of the enzyme for productive catalysis. Furthermore, the purified keratinase showed significant stability and compatibility against the tested commercial detergents at 37ºC. Therefore, these results suggested that the purified keratinase from Aspergillus sp. DHE7 may have potential use in the detergent industry and should be of interest in the processing of poultry feather waste.

Keywords: Aspergillus sp. DHE7, biochemical characterization, keratinase, purification, waste management

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Authors: James Britton, Vijaya Krishna, Manus Biggs, Abhay Pandit

Abstract:

Regeneration of the spinal cord after injury remains a great challenge due to the complexity of this organ. Inflammation and gliosis at the injury site hinder the outgrowth of axons and hence prevent synaptic reconnection and reinnervation. Hyaluronic acid (HA) is the main component of the spinal cord extracellular matrix and plays a vital role in cell proliferation and axonal guidance. In this study, we have synthesized and characterized a photo-cross-linkable HA-tyramine (tyr) hydrogel from a chemical, mechanical, electrical, biological and structural perspective. From our experimentation, we have found that HA-tyr can be synthesized with controllable degrees of tyramine substitution using click chemistry. The complex modulus (G*) of HA-tyr can be tuned to mimic the mechanical properties of the native spinal cord via optimization of the photo-initiator concentration and UV exposure. We have examined the degree of tyramine-tyramine covalent bonding (polymerization) as a function of UV exposure and photo-initiator use via Photo and Nuclear magnetic resonance spectroscopy. Both swelling and enzymatic degradation assays were conducted to examine the resilience of our 3D printed hydrogel constructs in-vitro. Using a femtosecond 780nm laser, the two-photon polymerization of HA-tyr hydrogel in the presence of riboflavin photoinitiator was optimized. A laser power of 50mW and scan speed of 30,000 μm/s produced high-resolution spatial patterning within the hydrogel with sustained mechanical integrity. Using dorsal root ganglion explants, the cytocompatibility of photo-crosslinked HA-tyr was assessed. Using potentiometry, the electrical conductivity of photo-crosslinked HA-tyr was assessed and compared to that of native spinal cord tissue as a function of frequency. In conclusion, we have developed a biocompatible hydrogel that can be used for photolithographic 3D printing to fabricate tissue engineered constructs for neural tissue regeneration applications.

Keywords: 3D printing, hyaluronic acid, photolithography, spinal cord injury

Procedia PDF Downloads 152