Search results for: spatial audio processing

Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

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Authors: Desmond F. Bellamy

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Discourses about animal rights usually assume an ontological abyss between human and animal. This supposition of non-animality allows us to utilise and exploit non-humans, particularly those with commercial value, with little regard for their rights or interests. We can and do confine them, inflict painful treatments such as castration and branding, and slaughter them at an age determined only by financial considerations. This paper explores the way images and texts depicting human cannibalism reflect this deprivation of rights back onto our species and examines how this offers new perspectives on our granting or withholding of rights to farmed animals. The animals we eat – sheep, pigs, cows, chickens and a small handful of other species – are during processing de-animalised, turned into commodities, and made unrecognisable as formerly living beings. To do the same to a human requires the cannibal to enact another step – humans must first be considered as animals before they can be commodified or de-animalised. Different iterations of cannibalism in a selection of fiction and non-fiction texts will be considered: survivalism (necessitated by catastrophe or dystopian social collapse), the primitive savage of colonial discourses, and the inhuman psychopath. Each type of cannibalism shows alternative ways humans can be animalised and thereby dispossessed of both their human and animal rights. Human rights, summarised in the UN Universal Declaration of Human Rights as ‘life, liberty, and security of person’ are stubbornly denied to many humans, and are refused to virtually all farmed non-humans. How might this paradigm be transformed by seeing the animal victim replaced by an animalised human? People are fascinated as well as repulsed by cannibalism, as demonstrated by the upsurge of films on the subject in the last few decades. Cannibalism is, at its most basic, about envisaging and treating humans as objects: meat. It is on the dinner plate that the abyss between human and ‘animal’ is most challenged. We grasp at a conscious level that we are a species of animal and may become, if in the wrong place (e.g., shark-infested water), ‘just food’. Culturally, however, strong traditions insist that humans are much more than ‘just meat’ and deserve a better fate than torment and death. The billions of animals on death row awaiting human consumption would ask the same if they could. Depictions of cannibalism demonstrate in graphic ways that humans are animals, made of meat and that we can also be butchered and eaten. These depictions of us as having the same fleshiness as non-human animals reminds us that they have the same capacities for pain and pleasure as we do. Depictions of cannibalism, therefore, unconsciously aid in deconstructing the human/animal binary and give a unique glimpse into the often unnoticed repudiation of animal rights.

Keywords: animal rights, cannibalism, human/animal binary, objectification

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Authors: Birgul Hizlar, Sibel Karakaya

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Recently, increasing attention has been given to carotenoid bioaccessibility and bioavailability in the field of nutrition research. As a consequence of their lipophilic nature and their specific localization in plant-based tissues, carotenoid bioaccessibility and bioavailability is generally quite low in raw fruits and vegetables, since carotenoids need to be released from the cellular matrix and incorporated in the lipid fraction during digestion before being absorbed. Today’s approach related to improving the bioaccessibility is to design food matrix. Recently, the newest approach, excipient food, has been introduced to improve the bioavailability of orally administered bioactive compounds. The main idea is combining food and another food (the excipient food) whose composition and/or structure is specifically designed for improving health benefits. In this study, effects of food processing, food matrix and the addition of excipient foods on the carotenoid bioaccessibility of carrots were determined. Different excipient foods (olive oil, lemon juice and whey curd) and different food matrices (grating, boiling and mashing) were used. Total carotenoid contents of the grated, boiled and mashed carrots were 57.23, 51.11 and 62.10 μg/g respectively. No significant differences among these values indicated that these treatments had no effect on the release of carotenoids from the food matrix. Contrary to, changes in the food matrix, especially mashing caused significant increase in the carotenoid bioaccessibility. Although the carotenoid bioaccessibility was 10.76% in grated carrots, this value was 18.19% in mashed carrots (p<0.05). Addition of olive oil and lemon juice as excipients into the grated carrots caused 1.23 times and 1.67 times increase in the carotenoid content and the carotenoid bioaccessibility respectively. However, addition of the excipient foods in the boiled carrot samples did not influence the release of carotenoid from the food matrix. Whereas, up to 1.9 fold increase in the carotenoid bioaccessibility was determined by the addition of the excipient foods into the boiled carrots. The bioaccessibility increased from 14.20% to 27.12% by the addition of olive oil, lemon juice and whey curd. The highest carotenoid content among mashed carrots was found in the mashed carrots incorporated with olive oil and lemon juice. This combination also caused a significant increase in the carotenoid bioaccessibility from 18.19% to 29.94% (p<0.05). When compared the results related with the effect of the treatments on the carotenoid bioaccessibility, mashed carrots containing olive oil, lemon juice and whey curd had the highest carotenoid bioaccessibility. The increase in the bioaccessibility was approximately 81% when compared to grated and mashed samples containing olive oil, lemon juice and whey curd. In conclusion, these results demonstrated that the food matrix and addition of the excipient foods had a significant effect on the carotenoid content and the carotenoid bioaccessibility.

Keywords: carrot, carotenoids, excipient foods, food matrix

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Authors: Buruk Kitachew Wossenyeleh

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Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

Procedia PDF Downloads 152

Authors: Fang Liu, JiaJia Yao, GuanLin Wu, ZuMaoLi, XueYan Yang, HePeng Zhang, ZhiPeng Sun, JunShuai Xue

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The explosive increasing needs of data processing and information storage strongly drive the advancement of the binary logic system to multiple-valued logic system. Inherent negative differential resistance characteristic, ultra-high-speed switching time, and robust anti-irradiation capability make III-nitride resonant tunneling diode one of the most promising candidates for multi-valued logic devices. Here we report the monolithic integration of GaN resonant tunneling diodes in series to realize multiple negative differential resistance regions, obtaining at least three stable operating states. A multiply-by-three circuit is achieved by this combination, increasing the frequency of the input triangular wave from f0 to 3f0. The resonant tunneling diodes are grown by plasma-assistedmolecular beam epitaxy on free-standing c-plane GaN substrates, comprising double barriers and a single quantum well both at the atomic level. Device with a peak current density of 183kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed, which is the best result reported in nitride-based resonant tunneling diodes. Microwave oscillation event at room temperature was discovered with a fundamental frequency of 0.31GHz and an output power of 5.37μW, verifying the high repeatability and robustness of our device. The switching behavior measurement was successfully carried out, featuring rise and fall times in the order of picoseconds, which can be used in high-speed digital circuits. Limited by the measuring equipment and the layer structure, the switching time can be further improved. In general, this article presents a novel nitride device with multiple negative differential regions driven by the resonant tunneling mechanism, which can be used in high-speed multiple value logic field with reduced circuit complexity, demonstrating a new solution of nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, negative differential resistance, multiple-valued logic system, switching time, peak-to-valley current ratio

Procedia PDF Downloads 100

Authors: Yang Cao

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Analyzing the oral production of Chinese-speaking learners of English as a second language (L2), we can find a large variety of verb inflections – Why does it seem so hard for them to use consistent correct past morphologies in obligatory past contexts? Failed Functional Features Hypothesis (FFFH) attributes the rather non-target-like performance to the absence of [±past] feature in their L1 Chinese, arguing that for post puberty learners, new features in L2 are no more accessible. By contrast, Missing Surface Inflection Hypothesis (MSIH) tends to believe that all features are actually acquirable for late L2 learners, while due to the mapping difficulties from features to forms, it is hard for them to realize the consistent past morphologies on the surface. However, most of the studies are limited to the verb morphologies in finite clauses and few studies have ever attempted to figure out these learners’ performance in non-finite clauses. Additionally, it has been discussed that Chinese learners may be able to tell the finite/infinite distinction (i.e. the [±finite] feature might be selected in Chinese, even though the existence of [±past] is denied). Therefore, adopting a self-paced reading task (SPR), the current study aims to analyze the processing patterns of Chinese-speaking learners of L2 Russian, in order to find out if they are sensitive to misuse of tense morphologies in both finite and non-finite clauses and whether they are sensitive to the finite/infinite distinction presented in Russian. The study targets L2 Russian due to its systematic morphologies in both present and past tenses. A native Russian group, as well as a group of English-speaking learners of Russian, whose L1 has definitely selected both [±finite] and [±past] features, will also be involved. By comparing and contrasting performance of the three language groups, the study is going to further examine and discuss the two theories, FFFH and MSIH. Preliminary hypotheses are: a) Russian native speakers are expected to spend longer time reading the verb forms which violate the grammar; b) it is expected that Chinese participants are, at least, sensitive to the misuse of inflected verbs in non-finite clauses, although no sensitivity to the misuse of infinitives in finite clauses might be found. Therefore, an interaction of finite and grammaticality is expected to be found, which indicate that these learners are able to tell the finite/infinite distinction; and c) having selected [±finite] and [±past], English-speaking learners of Russian are expected to behave target-likely, supporting L1 transfer.

Keywords: features, finite clauses, morphosyntax, non-finite clauses, past morphologies, present morphologies, Second Language Acquisition, self-paced reading task, verb inflections

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Authors: Karan Sharma, Ajay Kumar

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Epileptic seizure is a type of disease due to which electrical charge in the brain flows abruptly resulting in abnormal activity by the subject. One percent of total world population gets epileptic seizure attacks.Due to abrupt flow of charge, EEG (Electroencephalogram) waveforms change. On the display appear a lot of spikes and sharp waves in the EEG signals. Detection of epileptic seizure by using conventional methods is time-consuming. Many methods have been evolved that detect it automatically. The initial part of this paper provides the review of techniques used to detect epileptic seizure automatically. The automatic detection is based on the feature extraction and classification patterns. For better accuracy decomposition of the signal is required before feature extraction. A number of parameters are calculated by the researchers using different techniques e.g. approximate entropy, sample entropy, Fuzzy approximate entropy, intrinsic mode function, cross-correlation etc. to discriminate between a normal signal & an epileptic seizure signal.The main objective of this review paper is to present the variations in the EEG signals at both stages (i) Interictal (recording between the epileptic seizure attacks). (ii) Ictal (recording during the epileptic seizure), using most appropriate methods of analysis to provide better healthcare diagnosis. This research paper then investigates the effects of a noninvasive healing therapy on the subjects by studying the EEG signals using latest signal processing techniques. The study has been conducted with Reiki as a healing technique, beneficial for restoring balance in cases of body mind alterations associated with an epileptic seizure. Reiki is practiced around the world and is recommended for different health services as a treatment approach. Reiki is an energy medicine, specifically a biofield therapy developed in Japan in the early 20th century. It is a system involving the laying on of hands, to stimulate the body’s natural energetic system. Earlier studies have shown an apparent connection between Reiki and the autonomous nervous system. The Reiki sessions are applied by an experienced therapist. EEG signals are measured at baseline, during session and post intervention to bring about effective epileptic seizure control or its elimination altogether.

Keywords: EEG signal, Reiki, time consuming, epileptic seizure

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

Procedia PDF Downloads 130

Authors: Jose A. Alvarez Aldegunde, Adrian Fernandez Sanchez, Matthew D. Menden, Bernardo Vila Rodriguez

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Up to five statistical pre-processings have been carried out considering the pollutant records of the stations present in Cartagena de Indias, Colombia, also taking into account the childhood asthma incidence surveys conducted in hospitals in the city by the Health Ministry of Colombia for this study. These pre-processings have consisted of different techniques such as the determination of the quality of data collection, determination of the quality of the registration network, identification and debugging of errors in data collection, completion of missing data and purified data, as well as the improvement of the time scale of records. The characterization of the quality of the data has been conducted by means of density analysis of the pollutant registration stations using ArcGis Software and through mass balance techniques, making it possible to determine inconsistencies in the records relating the registration data between stations following the linear regression. The results obtained in this process have highlighted the positive quality in the pollutant registration process. Consequently, debugging of errors has allowed us to identify certain data as statistically non-significant in the incidence and series of contamination. This data, together with certain missing records in the series recorded by the measuring stations, have been completed by statistical imputation equations. Following the application of these prior processes, the basic series of incidence data for respiratory disease and pollutant records have allowed the characterization of the influence of pollutants on respiratory diseases such as, for example, childhood asthma. This characterization has been carried out using statistical correlation methods, including visual correlation, simple linear regression correlation and spectral analysis with PAST Software which identifies maximum periodicity cycles and minimums under the formula of the Lomb periodgram. In relation to part of the results obtained, up to eleven maximums and minimums considered contemporary between the incidence records and the particles have been identified taking into account the visual comparison. The spectral analyses that have been performed on the incidence and the PM2.5 have returned a series of similar maximum periods in both registers, which are at a maximum during a period of one year and another every 25 days (0.9 and 0.07 years). The bivariate analysis has managed to characterize the variable "Daily Vehicular Flow" in the ninth position of importance of a total of 55 variables. However, the statistical correlation has not obtained a favorable result, having obtained a low value of the R2 coefficient. The series of analyses conducted has demonstrated the importance of the influence of pollutants such as PM2.5 in the development of childhood asthma in Cartagena. The quantification of the influence of the variables has been able to determine that there is a 56% probability of dependence between PM2.5 and childhood respiratory asthma in Cartagena. Considering this justification, the study could be completed through the application of the BenMap Software, throwing a series of spatial results of interpolated values of the pollutant contamination records that exceeded the established legal limits (represented by homogeneous units up to the neighborhood level) and results of the impact on the exacerbation of pediatric asthma. As a final result, an economic estimate (in Colombian Pesos) of the monthly and individual savings derived from the percentage reduction of the influence of pollutants in relation to visits to the Hospital Emergency Room due to asthma exacerbation in pediatric patients has been granted.

Keywords: Asthma Incidence, BenMap, PM2.5, Statistical Analysis

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Morteza Esfandiari, Shabnam Jabari, Heather MacGrath, David Coleman

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Flood is a severe issue in different places in the world as well as the city of Fredericton, New Brunswick, Canada. The downtown area of Fredericton is close to the Saint John River, which is susceptible to flood around May every year. Recently, the frequency of flooding seems to be increased, especially after the fact that the downtown area and surrounding urban/agricultural lands got flooded in two consecutive years in 2018 and 2019. In order to have an explicit vision of flood span and damage to affected areas, it is necessary to use either flood inundation modelling or satellite data. Due to contingent availability and weather dependency of optical satellites, and limited existing data for the high cost of hydrodynamic models, it is not always feasible to rely on these sources of data to generate quality flood maps after or during the catastrophe. Height Above the Nearest Drainage (HAND), a state-of-the-art topo-hydrological index, normalizes the height of a basin based on the relative elevation along with the stream network and specifies the gravitational or the relative drainage potential of an area. HAND is a relative height difference between the stream network and each cell on a Digital Terrain Model (DTM). The stream layer is provided through a multi-step, time-consuming process which does not always result in an optimal representation of the river centerline depending on the topographic complexity of that region. HAND is used in numerous case studies with quite acceptable and sometimes unexpected results because of natural and human-made features on the surface of the earth. Some of these features might cause a disturbance in the generated model, and consequently, the model might not be able to predict the flow simulation accurately. We propose to include a previously existing stream layer generated by the province of New Brunswick and benefit from culvert maps to improve the water flow simulation and accordingly the accuracy of HAND model. By considering these parameters in our processing, we were able to increase the accuracy of the model from nearly 74% to almost 92%. The improved model can be used for generating highly accurate flood maps, which is necessary for future urban planning and flood damage estimation without any need for satellite imagery or hydrodynamic computations.

Keywords: HAND, DTM, rapid floodplain, simplified conceptual models

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Authors: Majid Eslami

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Functionally graded materials (FGMs) exhibit heterogeneous microstructures in which the composition and properties gently change in specified directions. The common type of FGMs consist of a metal in which ceramic particles are distributed with a graded concentration. There are many processing routes for FGMs. An important group of these methods is casting techniques (gravity or centrifugal). However, the main problem of casting molten metal slurry with dispersed ceramic particles is a destructive chemical reaction between these two phases which deteriorates the properties of the materials. In order to overcome this problem, in the present investigation a suspension of 6061 aluminum and alumina powders in a liquid polymer was used as the starting material and subjected to centrifugal force for making FGMs. The size rang of these powders was 45-63 and 106-125 μm. The volume percent of alumina in the Al/Al2O3 powder mixture was in the range of 5 to 20%. PMMA (Plexiglas) in different concentrations (20-50 g/lit) was dissolved in toluene and used as the suspension liquid. The glass mold contaning the suspension of Al/Al2O3 powders in the mentioned liquid was rotated at 1700 rpm for different times (4-40 min) while the arm length was kept constant (10 cm) for all the experiments. After curing the polymer, burning out the binder, cold pressing and sintering , cylindrical samples (φ=22 mm h=20 mm) were produced. The density of samples before and after sintering was quantified by Archimedes method. The results indicated that by using the same sized alumina and aluminum powders particles, FGM sample can be produced by rotation times exceeding 7 min. However, by using coarse alumina and fine alumina powders the sample exhibits step concentration. On the other hand, using fine alumina and coarse alumina results in a relatively uniform concentration of Al2O3 along the sample height. These results are attributed to the effects of size and density of different powders on the centrifugal force induced on the powders during rotation. The PMMA concentration and the vol.% of alumina in the suspension did not have any considerable effect on the distribution of alumina particles in the samples. The hardness profiles along the height of samples were affected by both the alumina vol.% and porosity content. The presence of alumina particles increased the hardness while increased porosity reduced the hardness. Therefore, the hardness values did not show the expected gradient in same sample. The sintering resulted in decreased porosity for all the samples investigated.

Keywords: FGM, powder metallurgy, centrifugal method, polymeric suspension

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Authors: Ugo Galvanetto, Pirto G. Pavan, Mirco Zaccariotto

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The discipline of Computer-integrated surgery (CIS) will provide equipment able to improve the efficiency of healthcare systems and, which is more important, clinical results. Surgeons and machines will cooperate in new ways that will extend surgeons’ ability to train, plan and carry out surgery. Patient specific CIS of the brain requires several steps: 1 - Fast generation of brain models. Based on image recognition of MR images and equipped with artificial intelligence, image recognition techniques should differentiate among all brain tissues and segment them. After that, automatic mesh generation should create the mathematical model of the brain in which the various tissues (white matter, grey matter, cerebrospinal fluid …) are clearly located in the correct positions. 2 – Reliable and fast simulation of the surgical process. Computational mechanics will be the crucial aspect of the entire procedure. New algorithms will be used to simulate the mechanical behaviour of cutting through cerebral tissues. 3 – Real time provision of visual and haptic feedback A sophisticated human-machine interface based on ergonomics and psychology will provide the feedback to the surgeon. The present work will address in particular point 2. Modelling the cutting of soft tissue in a structure as complex as the human brain is an extremely challenging problem in computational mechanics. The finite element method (FEM), that accurately represents complex geometries and accounts for material and geometrical nonlinearities, is the most used computational tool to simulate the mechanical response of soft tissues. However, the main drawback of FEM lies in the mechanics theory on which it is based, classical continuum Mechanics, which assumes matter is a continuum with no discontinuity. FEM must resort to complex tools such as pre-defined cohesive zones, external phase-field variables, and demanding remeshing techniques to include discontinuities. However, all approaches to equip FEM computational methods with the capability to describe material separation, such as interface elements with cohesive zone models, X-FEM, element erosion, phase-field, have some drawbacks that make them unsuitable for surgery simulation. Interface elements require a-priori knowledge of crack paths. The use of XFEM in 3D is cumbersome. Element erosion does not conserve mass. The Phase Field approach adopts a diffusive crack model instead of describing true tissue separation typical of surgical procedures. Modelling discontinuities, so difficult when using computational approaches based on classical continuum Mechanics, is instead easy for novel computational methods based on Peridynamics (PD). PD is a non-local theory of mechanics formulated with no use of spatial derivatives. Its governing equations are valid at points or surfaces of discontinuity, and it is, therefore especially suited to describe crack propagation and fragmentation problems. Moreover, PD does not require any criterium to decide the direction of crack propagation or the conditions for crack branching or coalescence; in the PD-based computational methods, cracks develop spontaneously in the way which is the most convenient from an energy point of view. Therefore, in PD computational methods, crack propagation in 3D is as easy as it is in 2D, with a remarkable advantage with respect to all other computational techniques.

Keywords: computational mechanics, peridynamics, finite element, biomechanics

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Authors: Soon Young Choi, Chan Hwan Kim, Chan Hong Park, Hyung Rae Kim, Myoung Hoon Lee, Hyeon-Yeong Park

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We performed the marine magnetic, bathymetry and seismic survey at the TA22 seamount (in the Lau basin, SW Pacific) for finding the submarine hydrothermal deposits in October 2009. We acquired magnetic and bathymetry data sets by suing Overhouser Proton Magnetometer SeaSPY (Marine Magnetics Co.), Multi-beam Echo Sounder EM120 (Kongsberg Co.). We conducted the data processing to obtain detailed seabed topography, magnetic anomaly, reduction to the pole (RTP) and magnetization. Based on the magnetic properties result, we analyzed submarine geology structure of TA22 seamount with post-processed seismic profile. The detailed bathymetry of the TA22 seamount showed the left and right crest parts that have caldera features in each crest central part. The magnetic anomaly distribution of the TA22 seamount regionally displayed high magnetic anomalies in northern part and the low magnetic anomalies in southern part around the caldera features. The RTP magnetic anomaly distribution of the TA22 seamount presented commonly high magnetic anomalies in the each caldera central part. Also, it represented strong anomalies at the inside of caldera rather than outside flank of the caldera. The magnetization distribution of the TA22 seamount showed the low magnetization zone in the center of each caldera, high magnetization zone in the southern and northern east part. From analyzed the seismic profile map, The TA22 seamount area is showed for the inferred small mounds inside each caldera central part and it assumes to make possibility of sills by the magma in cases of the right caldera. Taking into account all results of this study (bathymetry, magnetic anomaly, RTP, magnetization, seismic profile) with rock samples at the left caldera area in 2009 survey, we suppose the possibility of hydrothermal deposits at mounds in each caldera central part and at outside flank of the caldera representing the low magnetization zone. We expect to have the better results by combined modeling from this study data with the other geological data (ex. detailed gravity, 3D seismic, petrologic study results and etc).

Keywords: detailed bathymetry, magnetic anomaly, seamounts, seismic profile, SW Pacific

Procedia PDF Downloads 403

Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

Procedia PDF Downloads 118

Authors: Calvin Ralph, Edward Archer, Alistair McIlhagger

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3D woven textile composites continue to emerge as an advanced material for structural applications and composite manufacture due to their bespoke nature, through thickness reinforcement and near net shape capabilities. When 3D woven preforms are produced, they are in their optimal physical state. As 3D weaving is a dry preforming technology it relies on compression of the preform to achieve the desired composite thickness, fibre volume fraction (Vf) and consolidation. This compression of the preform during manufacture results in changes to its thickness and architecture which can often lead to under-performance or changes of the 3D woven composite. Unlike traditional 2D fabrics, the bespoke nature and variability of 3D woven architectures makes it difficult to know exactly how each 3D preform will behave during processing. Therefore, the focus of this study is to investigate the effect of compression on differing 3D woven architectures in terms of structure, crimp or fibre waviness and thickness as well as analysing the accuracy of available software to predict how 3D woven preforms behave under compression. To achieve this, 3D preforms are modelled and compression simulated in Wisetex with varying architectures of binder style, pick density, thickness and tow size. These architectures have then been woven with samples dry compression tested to determine the compressibility of the preforms under various pressures. Additional preform samples were manufactured using Resin Transfer Moulding (RTM) with varying compressive force. Composite samples were cross sectioned, polished and analysed using microscopy to investigate changes in architecture and crimp. Data from dry fabric compression and composite samples were then compared alongside the Wisetex models to determine accuracy of the prediction and identify architecture parameters that can affect the preform compressibility and stability. Results indicate that binder style/pick density, tow size and thickness have a significant effect on compressibility of 3D woven preforms with lower pick density allowing for greater compression and distortion of the architecture. It was further highlighted that binder style combined with pressure had a significant effect on changes to preform architecture where orthogonal binders experienced highest level of deformation, but highest overall stability, with compression while layer to layer indicated a reduction in fibre crimp of the binder. In general, simulations showed a relative comparison to experimental results; however, deviation is evident due to assumptions present within the modelled results.

Keywords: 3D woven composites, compression, preforms, textile composites

Procedia PDF Downloads 135

Authors: Francisco J. Ortega, Claudia Roman, Moisés García-Morales, Francisco J. Navarro

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Asphaltic bitumen has been largely used in both industrial and civil engineering, mostly in pavement construction and roofing membrane manufacture. However, bitumen as such is greatly susceptible to temperature variations, and dramatically changes its in-service behavior from a viscoelastic liquid, at medium-high temperatures, to a brittle solid at low temperatures. Bitumen modification prevents these problems and imparts improved performance. Isocyanates like polymeric MDI (mixture of 4,4′-diphenylmethane di-isocyanate, 2,4’ and 2,2’ isomers, and higher homologues) have shown to remarkably enhance bitumen properties at the highest in-service temperatures expected. This comes from the reaction between the –NCO pendant groups of the oligomer and the most polar groups of asphaltenes and resins in bitumen. In addition, oxygen diffusion and/or UV radiation may provoke bitumen hardening and ageing. With the purpose of minimizing these effects, nano-layered-silicates (nanoclays) are increasingly being added to bitumen formulations. Montmorillonites, a type of naturally occurring mineral, may produce a nanometer scale dispersion which improves bitumen thermal, mechanical and barrier properties. In order to increase their lipophilicity, these nanoclays are normally treated so that organic cations substitute the inorganic cations located in their intergallery spacing. In the present work, the combined effect of polymeric MDI and the commercial montmorillonite Cloisite® 20A was evaluated. A selected bitumen with penetration within the range 160/220 was modified with 10 wt.% Cloisite® 20A and 2 wt.% polymeric MDI, and the resulting ternary composites were characterized by linear rheology, X-ray diffraction (XRD) and Atomic Force Microscopy (AFM). The rheological tests evidenced a notable solid-like behavior at the highest temperatures studied when bitumen was just loaded with 10 wt.% Cloisite® 20A and high-shear blended for 20 minutes. However, if polymeric MDI was involved, the sequence of addition exerted a decisive control on the linear rheology of the final ternary composites. Hence, in bitumen/Cloisite® 20A/polymeric MDI formulations, the previous solid-like behavior disappeared. By contrast, an inversion in the order of addition (bitumen/polymeric MDI/ Cloisite® 20A) enhanced further the solid-like behavior imparted by the nanoclay. In order to gain a better understanding of the factors that govern the linear rheology of these ternary composites, a morphological and microstructural characterization based on XRD and AFM was conducted. XRD demonstrated the existence of clay stacks intercalated by bitumen molecules to some degree. However, the XRD technique cannot provide detailed information on the extent of nanoclay delamination, unless the entire fraction has effectively been fully delaminated (situation in which no peak is observed). Furthermore, XRD was unable to provide precise knowledge neither about the spatial distribution of the intercalated/exfoliated platelets nor about the presence of other structures at larger length scales. In contrast, AFM proved its power at providing conclusive information on the morphology of the composites at the nanometer scale and at revealing the structural modification that yielded the rheological properties observed. It was concluded that high-shear blending brought about a nanoclay-reinforced network. As for the bitumen/Cloisite® 20A/polymeric MDI formulations, the solid-like behavior was destroyed as a result of the agglomeration of the nanoclay platelets promoted by chemical reactions.

Keywords: Atomic Force Microscopy, bitumen, composite, isocyanate, montmorillonite.

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Authors: Jithin S. Kumar, Ramesh Kannan Kandasami

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Geomaterials are generally porous in nature due to the presence of discrete particles and interconnected voids. The porosity present in these geomaterials play a critical role in many engineering applications such as CO2 sequestration, well bore strengthening, enhanced oil and hydrocarbon recovery, hydraulic fracturing, and subsurface waste storage. These applications involves solid-fluid interactions, which govern the changes in the porosity which in turn affect the permeability and stiffness of the medium. Injecting fluid into the geomaterials results in permeation which exhibits small or negligible deformation of the soil skeleton followed by cavity expansion/ fingering/ fracturing (different forms of instabilities) due to the large deformation especially when the flow rate is greater than the ability of the medium to permeate the fluid. The complexity of this problem increases as the geomaterial behaves like a solid and fluid under certain conditions. Thus it is important to understand this multiphysics problem where in addition to the permeation, the elastic-plastic deformation of the soil skeleton plays a vital role during fluid injection. The phenomenon of permeation and cavity expansion in porous medium has been studied independently through extensive experimental and analytical/ numerical models. The analytical models generally use Darcy's/ diffusion equations to capture the fluid flow during permeation while elastic-plastic (Mohr-Coulomb and Modified Cam-Clay) models were used to predict the solid deformations. Hitherto, the research generally focused on modelling cavity expansion without considering the effect of injected fluid coming into the medium. Very few studies have considered the effect of injected fluid on the deformation of soil skeleton. However, the porosity changes during the fluid injection and coupled elastic-plastic deformation are not clearly understood. In this study, the phenomenon of permeation and instabilities such as cavity and finger/ fracture formation will be quantified extensively by performing experiments using a novel experimental setup in addition to utilizing image processing techniques. This experimental study will describe the fluid flow and soil deformation characteristics under different boundary conditions. Further, a well refined coupled semi-analytical model will be developed to capture the physics involved in quantifying the deformation behaviour of geomaterial during fluid injection.

Keywords: solid-fluid interaction, permeation, poroelasticity, plasticity, continuum model

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Authors: Hamza Javar Magnier, Robin Curtis

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There have been rapid advances in the upstream processing of protein therapeutics, which has shifted the bottleneck to downstream purification and formulation. Finding liquid formulations with shelf lives of up to two years is increasingly difficult for some of the newer therapeutics, which have been engineered for activity, but their formulations are often viscous, can phase separate, and have a high propensity for irreversible aggregation1. We explore means to develop improved predictive ability from a better understanding of how protein-protein interactions on formulation conditions (pH, ionic strength, buffer type, presence of excipients) and how these impact upon the initial steps in protein self-association and aggregation. In this work, we study the initial steps in the aggregation pathways using a minimal protein model based on square-well potentials and discontinuous molecular dynamics. The effect of model parameters, including range of interaction, stiffness, chain length, and chain sequence, implies that protein models fold according to various pathways. By reducing the range of interactions, the folding- and collapse- transition come together, and follow a single-step folding pathway from the denatured to the native state2. After parameterizing the model interaction-parameters, we developed an understanding of low-temperature conformational properties and fluctuations, and the correlation to the folding transition of proteins in isolation. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This implies that fluctuations at low-temperature can be correlated to the folding transition at the melting temperature. Because proteins “breath” at low temperatures, defining a native-state as a single structure with conserved contacts and a fixed three-dimensional structure is misleading. Rather, we introduce a new definition of a native-state ensemble based on our understanding of the core conservation, which takes into account the native fluctuations at low temperatures. This approach permits the study of a large range of length and time scales needed to link the molecular interactions to the macroscopically observed behaviour. In addition, these models studied are parameterized by fitting to experimentally observed protein-protein interactions characterized in terms of osmotic second virial coefficients.

Keywords: protein folding, native-ensemble, conformational fluctuation, aggregation

Procedia PDF Downloads 361

Authors: Roberta Facchinetti, Sara Corrizzato, Silvia Cavalieri

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Increasing interconnection between data digitalization and linguistic investigation has given rise to unprecedented potentialities and challenges for corpus linguists, who need to master IT tools for data analysis and text processing, as well as to develop techniques for efficient and reliable annotation in specific mark-up languages that encode documents in a format that is both human and machine-readable. In the present paper, the challenges emerging from the compilation of a linguistic corpus will be taken into consideration, focusing on the English language in particular. To do so, the case study of the InterDiplo corpus will be illustrated. The corpus, currently under development at the University of Verona (Italy), represents a novelty in terms both of the data included and of the tag set used for its annotation. The corpus covers media interviews and debates with diplomats and international operators conversing in English with journalists who do not share the same lingua-cultural background as their interviewees. To date, this appears to be the first tagged corpus of international institutional spoken discourse and will be an important database not only for linguists interested in corpus analysis but also for experts operating in international relations. In the present paper, special attention will be dedicated to the structural mark-up, parts of speech annotation, and tagging of discursive traits, that are the innovational parts of the project being the result of a thorough study to find the best solution to suit the analytical needs of the data. Several aspects will be addressed, with special attention to the tagging of the speakers’ identity, the communicative events, and anthropophagic. Prominence will be given to the annotation of question/answer exchanges to investigate the interlocutors’ choices and how such choices impact communication. Indeed, the automated identification of questions, in relation to the expected answers, is functional to understand how interviewers elicit information as well as how interviewees provide their answers to fulfill their respective communicative aims. A detailed description of the aforementioned elements will be given using the InterDiplo-Covid19 pilot corpus. The data yielded by our preliminary analysis of the data will highlight the viable solutions found in the construction of the corpus in terms of XML conversion, metadata definition, tagging system, and discursive-pragmatic annotation to be included via Oxygen.

Keywords: spoken corpus, diplomats’ interviews, tagging system, discursive-pragmatic annotation, english linguistics

Procedia PDF Downloads 185

Authors: Tatiani D. Mousoura

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Specific learning disability (SLD) in higher education has been partially explored in Greece so far. Moreover, opinions on professional perspectives for university students with SLD, is scarcely encountered in Greek research. The perceptions of the hidden character of SLD along with the university policy towards it and professional perspectives that result from this policy have been examined in the present research. This study has applied the paradigm of a Greek Tertiary Pedagogical Education Department (Early Childhood Education). Via mixed methods, data have been collected from different groups of people in the Pedagogical Department: students with SLD and without SLD, academic staff and administration staff, all of which offer the opportunity for triangulation of the findings. Qualitative methods include ten interviews with students with SLD and 15 interviews with academic staff and 60 hours of observation of the students with SLD. Quantitative methods include 165 questionnaires completed by third and fourth-year students and five questionnaires completed by the administration staff. Thematic analyses of the interviews’ data and descriptive statistics on the questionnaires’ data have been applied for the processing of the results. The use of medical terms to define and understand SLD was common in the student cohort, regardless of them having an SLD diagnosis. However, this medical model approach is far more dominant in the group of students without SLD who, by majority, hold misconceptions on a definitional level. The academic staff group seems to be leaning towards a social approach concerning SLD. According to them, diagnoses may lead to social exclusion. The Pedagogical Department generally endorses the principles of inclusion and complies with the provision of oral exams for students with SLD. Nevertheless, in practice, there seems to be a lack of regular academic support for these students. When such support does exist, it is only through individual initiatives. With regards to their prospective profession, students with SLD can utilize their personal experience, as well as their empathy; these appear to be unique weapons in their hands –in comparison with other educators− when it comes to teaching students in the future. In the Department of Pedagogy, provision towards SLD results sporadic, however the vision of an inclusive department does exist. Based on their studies and their experience, pedagogy students with SLD claim that they have an experiential internalized advantage for their future career as educators.

Keywords: specific learning disability, SLD, dyslexia, pedagogy department, inclusion, professional role of SLDed educators, higher education, university policy

Procedia PDF Downloads 113

Authors: Takaaki Miyabe, Hideharu Takahashi, Hiroshige Kikura

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The Government of Japan and Tokyo Electric Power Company Holdings, Incorporated (TEPCO) are struggling with the decommissioning of Fukushima Daiichi Nuclear Power Plants, especially fuel debris retrieval. In fuel debris retrieval, amount of fuel debris, location, characteristics, and distribution information are important. Recently, a survey was conducted using a robot with a small camera. Progress report in remote robot and camera research has speculated that fuel debris is present both at the bottom of the Pressure Containment Vessel (PCV) and inside the Reactor Pressure Vessel (RPV). The investigation found a 'tie plate' at the bottom of the containment, this is handles on the fuel rod. As a result, it is assumed that a hole large enough to allow the tie plate to fall is opened at the bottom of the reactor pressure vessel. Therefore, exploring the existence of holes that lead to inside the RCV is also an issue. Investigations of the lower part of the RPV are currently underway, but no investigations have been made inside or above the PCV. Therefore, a survey must be conducted for future fuel debris retrieval. The environment inside of the RPV cannot be imagined due to the effect of the melted fuel. To do this, we need a way to accurately check the internal situation. What we propose here is the adaptation of a technology called 'Structure from Motion' that reconstructs a 3D image from multiple photos taken by a single camera. The plan is to mount a monocular camera on the tip of long-arm robot, reach it to the upper part of the PCV, and to taking video. Now, we are making long-arm robot that has long-arm and used at high level radiation environment. However, the environment above the pressure vessel is not known exactly. Also, fog may be generated by the cooling water of fuel debris, and the radiation level in the environment may be high. Since camera alone cannot provide sufficient sensing in these environments, we will further propose using ultrasonic measurement technology in addition to cameras. Ultrasonic sensor can be resistant to environmental changes such as fog, and environments with high radiation dose. these systems can be used for a long time. The purpose is to develop a system adapted to the inside of the containment vessel by combining a camera and an ultrasound. Therefore, in this research, we performed a basic experiment on 3D image reconstruction using a camera and ultrasound. In this report, we select the good and bad condition of each sensing, and propose the reconstruction and detection method. The results revealed the strengths and weaknesses of each approach.

Keywords: camera, image processing, reconstruction, ultrasound

Procedia PDF Downloads 104

Authors: Siyamak Sarafraz, Reza Esmaeil Pour, Saeed Jamshidi, Asghar Molaei Dehkordi

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Cutting transport is one of the major problems in directional and extended reach oil and gas wells. Lack of sufficient attention to this issue may bring some troubles such as casing running, stuck pipe, excessive torque and drag, hole pack off, bit wear, decreased the rate of penetration (ROP), increased equivalent circulation density (ECD) and logging. Since it is practically impossible to directly observe the behavior of deep wells, a test setup was designed to investigate cutting transport phenomena. This experimental work carried out to scrutiny behavior of the effective variables in cutting transport. The test setup contained a test section with 17 feet long that made of a 3.28 feet long transparent glass pipe with 3 inch diameter, a storage tank with 100 liters capacity, drill pipe rotation which made of stainless steel with 1.25 inches diameter, pump to circulate drilling fluid, valve to adjust flow rate, bit and a camera to record all events which then converted to RGB images via the Image Processing Toolbox. After preparation of test process, each test performed separately, and weights of the output particles were measured and compared with each other. Observation charts were plotted to assess the behavior of viscosity, flow rate and RPM in inclinations of 0°, 30°, 60° and 90°. RPM was explored with other variables such as flow rate and viscosity in different angles. Also, effect of different flow rate was investigated in directional conditions. To access the precise results, captured image were analyzed to find out bed thickening and particles behave in the annulus. The results of this experimental study demonstrate that drill string rotation helps particles to be suspension and reduce the particle deposition cutting movement increased significantly. By raising fluid velocity, laminar flow converted to turbulence flow in the annulus. Increases in flow rate in horizontal section by considering a lower range of viscosity is more effective and improved cuttings transport performance.

Keywords: cutting transport, directional drilling, flow rate, hole cleaning, pipe rotation

Procedia PDF Downloads 284

Authors: Kedar Baral

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This study was carried out in Mustang, Kaski, Tanahun, Baitadi, and Jhapa districts of Nepal. The study explored the spatial and temporal pattern of HWC, socio economic factors associated with it, impacts of conflict on life / livelihood of people and survival of wildlife species, and impact of climate change and forest fire onHWC. Study also evaluated people’s attitude towards wildlife conservation and assessed relevant policies and programs. Questionnaire survey was carried out with the 250 respondents, and both socio-demographic and HWC related information werecollected. Secondary information were collected from Divisional Forest Offices and Annapurna Conservation Area Project.HWC events were grouped by season /months/sites (forest type, distances from forest, and settlement), and the coordinates of the events were exported to ArcGIS. Collected data were analyzed using descriptive statistics in Excel and R Program. A total of 1465 events were recorded in 5 districts during 2015 and 2019. Out of that, livestock killing, crop damage, human attack, and cattle shed damage events were 70 %, 12%, 11%, and 7%, respectively. Among 151 human attack cases, 23 people were killed, and 128 were injured. Elephant in Terai, common leopard and monkey in Middle Mountain, and snow leopard in high mountains were found as major problematic animals. Common leopard attacks were found more in the autumn, evening, and on human settlement area. Whereas elephant attacks were found higher in winter, day time, and on farmland. Poor people farmers were found highly victimized, and they were losing 26% of their income due to crop raiding and livestock depredation. On the other hand, people are killing many wildlife in revenge, and this number is increasing every year. Based on the people's perception, climate change is causing increased temperature and forest fire events and decreased water sources within the forest. Due to the scarcity of food and water within forests, wildlife are compelled to dwell at human settlement area, hence HWC events are increasing. Nevertheless, more than half of the respondents were found positive about conserving entire wildlife species. Forests outside PAs are under the community forestry (CF) system, which restored the forest, improved the habitat, and increased the wildlife.However, CF policies and programs were found to be more focused on forest management with least priority on wildlife conservation and HWC mitigation. Compensation / relief scheme of government for wildlife damage was found some how effective to manage HWC, but the lengthy process, being applicable to the damage of few wildlife species and highly increasing events made it necessary to revisit. Based on these facts, the study suggest to carry out awareness generation activities to the poor farmers, linking the property of people with the insurance scheme, conducting habitat management activities within CF, promoting the unpalatable crops, improvement of shed house of livestock, simplifying compensation scheme and establishing a fund at the district level and incorporating the wildlife conservation and HWCmitigation programs in CF. Finally, the study suggests to carry out rigorous researches to understand the impacts of current forest management practices on forest, biodiversity, wildlife, and HWC.

Keywords: community forest, conflict mitigation, wildlife conservation, climate change

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Authors: Ankush, Harshit Sosan Lakra, Rachita Kuthial

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Climate change poses significant challenges to vulnerable communities, particularly indigenous populations in ecologically sensitive regions. Jharkhand, located in the heart of India, is home to several indigenous communities, including the Particularly Vulnerable Tribal Groups (PVTGs). The Indigenous architecture of the region functions as a significant reservoir of climate adaptation wisdom. It explores the architectural analysis encompassing the construction materials, construction techniques, design principles, climate responsiveness, cultural relevance, adaptation, integration with the environment and traditional wisdom that has evolved through generations, rooted in cultural and socioeconomic traditions, and has allowed these communities to thrive in a variety of climatic zones, including hot and dry, humid, and hilly terrains to withstand the test of time. Despite their historical resilience to adverse climatic conditions, PVTG tribal communities face new and amplified challenges due to the accelerating pace of climate change. There is a significant research void that exists in assimilating their traditional practices and local wisdom into contemporary climate resilience initiatives. Most of the studies place emphasis on technologically advanced solutions, often ignoring the invaluable Indigenous Local knowledge that can complement and enhance these efforts. This research gap highlights the need to bridge the disconnect between indigenous knowledge and contemporary climate adaptation strategies. The study aims to explore and leverage indigenous knowledge of vernacular architecture as a strategic tool for enhancing climatic resilience among PVTGs of the region. The first objective is to understand the traditional wisdom of vernacular architecture by analyzing and documenting distinct architectural practices and cultural significance of PVTG communities, emphasizing construction techniques, materials and spatial planning. The second objective is to develop culturally sensitive climatic resilience strategies based on findings of vernacular architecture by employing a multidisciplinary research approach that encompasses ethnographic fieldwork climate data assessment considering multiple variables such as temperature variations, precipitation patterns, extreme weather events and climate change reports. This will be a tailor-made solution integrating indigenous knowledge with modern technology and sustainable practices. With the involvement of indigenous communities in the process, the research aims to ensure that the developed strategies are practical, culturally appropriate, and accepted. To foster long-term resilience against the global issue of climate change, we can bridge the gap between present needs and future aspirations with Traditional wisdom, offering sustainable solutions that will empower PVTG communities. Moreover, the study emphasizes the significance of preserving and reviving traditional Architectural wisdom for enhancing climatic resilience. It also highlights the need for cooperative endeavors of communities, stakeholders, policymakers, and researchers to encourage integrating traditional Knowledge into Modern sustainable design methods. Through these efforts, this research will contribute not only to the well-being of PVTG communities but also to the broader global effort to build a more resilient and sustainable future. Also, the Indigenous communities like PVTG in the state of Jharkhand can achieve climatic resilience while respecting and safeguarding the cultural heritage and peculiar characteristics of its native population.

Keywords: vernacular architecture, climate change, resilience, PVTGs, Jharkhand, indigenous people, India

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Authors: Nabiyeva Jamala

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We divide water into drinking, mineral, industrial, technical and thermal-energetic types according to its use and purpose. Drinking water must comply with sanitary requirements and norms according to organoleptic devices and physical and chemical properties. Mineral water - must comply with the norms due to some components having therapeutic properties. Industrial water must fulfill its normative requirements by being used in the industrial field. Technical water should be suitable for use in the field of agriculture, household, and irrigation, and the normative requirements should be met. Heat-energy water is used in the national economy, and it consists of thermal and energy water. Water is a filter-accumulator of all types of pollutants entering the environment. This is explained by the fact that it has the property of dissolving compounds of mineral and gaseous water and regular water circulation. Environmentally clean, pure, non-toxic water is vital for the normal life activity of humans, animals and other living beings. Chemical pollutants enter water basins mainly with wastewater from non-ferrous and ferrous metallurgy, oil, gas, chemical, stone, coal, pulp and paper and forest materials processing industries and make them unusable. Wastewater from the chemical, electric power, woodworking and machine-building industries plays a huge role in the pollution of water sources. Chlorine compounds, phenols, and chloride-containing substances have a strong lethal-toxic effect on organisms when mixed with water. Heavy metals - lead, cadmium, mercury, nickel, copper, selenium, chromium, tin, etc. water mixed with ingredients cause poisoning in humans, animals and other living beings. Thus, the mixing of selenium with water causes liver diseases in people, the mixing of mercury with the nervous system, and the mixing of cadmium with kidney diseases. Pollution of the World's ocean waters and other water basins with oil and oil products is one of the most dangerous environmental problems facing humanity today. So, mixing even the smallest amount of oil and its products in drinking water gives it a bad, unpleasant smell. Mixing one ton of oil with water creates a special layer that covers the water surface in an area of 2.6 km2. As a result, the flood of light, photosynthesis and oxygen supply of water is getting weak and there is a great danger to the lives of living beings.

Keywords: chemical pollutants, wastewater, SSAM, polyacrylamide

Procedia PDF Downloads 73

Authors: Ina Nasto, Denada Sota, Kerol Sacaj, Brunilda Veshaj, Hajdar Kicaj

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Rocky shores are often used as models to describe the dynamics of biodiversity around the world, making them one of the most studied marine habitats and their communities. The variability in the number of species and the abundance of hard-bottom benthic animal communities on the coast of Triporti, north of the Bay of Vlora, Albania is described in relation to environmental variables using multivariate analysis. The purpose of this study is to monitor the species composition, quantitative characteristics, and seasonal variations of the benthic macroinvertebrate populations of the shallow rocky shores of the Triportit-Vlora area, as well as the assessment of the ecological condition of these populations. The rocky coast of Triport, with a length of 7 km, was divided into three sampling stations, with three transects each of 50m. The monitoring of benthic macroinvertebrates in these areas was carried out in two seasons, spring and summer (June and August 2021). In each station and sampling season, estimates of the total and average density for each species, the presence constant, and the assessment of biodiversity were calculated using the Shannon–Wiener and the Simpson index. The species composition, the quantitative characteristics of the populations, and the indicators mentioned above were analyzed in a comparative way, both between the seasons within one station and between the three stations with each other. Statistical processing of the data was carried out to analyze the changes between the seasons and between the sampling stations for the species composition, population density, as well as correlation between them. A total of 105 benthic macroinvertebrate taxa were found, dominated by Molluscs, Annelids, and Arthropods. The small density of species and the low degree of stability of the macrozoobenthic community are indicators of the poor ecological condition and environmental impact in the studied areas. Algal cover, the diversity of coastal microhabitats, and the degree of coastal exposure to waves play an important role in the characteristics of macrozoobenthos populations in the studied areas. Also, the rocky shores are of special interest because, in the infralittoral of these areas, there are dense kelp forests with Gongolaria barbata, Ericaria crinita as well as fragmented areas with Posidonia oceanica that reach the coast, priority habitats of special conservation importance in the Mediterranean.

Keywords: Macrozoobenthic communities, Shannon–Wiener, Triporti, Vlore, rocky shore

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Authors: Cathal Merz, Gareth O’Donnell

Abstract:

Coil reinforced thin-walled (CRTW) tubes are used in medicine to treat problems affecting blood vessels within the body through minimally invasive procedures. The CRTW tube considered in this research makes up part of such a device and is inserted into the patient via their femoral or brachial arteries and manually navigated to the site in need of treatment. This procedure replaces the requirement to perform open surgery but is limited by reduction of blood vessel lumen diameter and increase in tortuosity of blood vessels deep in the brain. In order to maximize the capability of these procedures, CRTW tube devices are being manufactured with decreasing wall thicknesses in order to deliver treatment deeper into the body and to allow passage of other devices through its inner diameter. This introduces significant stresses to the device materials which have resulted in an observed increase in the breaking of the proximal segment of the device into two separate pieces after it has failed by buckling. As there is currently no international standard for measuring the mechanical properties of these CRTW tube devices, it is difficult to accurately analyze this problem. The aim of the current work is to address this discrepancy in the biomedical device industry by developing a measurement system that can be used to quantify the effect of process and design changes on CRTW tube performance, aiding in the development of better performing, next generation devices. Using materials testing frames, micro-computed tomography (micro-CT) imaging, experiment planning, analysis of variance (ANOVA), T-tests and regression analysis, test methods have been developed for assessing the impact of process and design changes on the device. The major findings of this study have been an insight into the suitability of buckle and three-point bend tests for the measurement of the effect of varying processing factors on the device’s performance, and guidelines for interpreting the output data from the test methods. The findings of this study are of significant interest with respect to verifying and validating key process and design changes associated with the device structure and material condition. Test method integrity evaluation is explored throughout.

Keywords: neurovascular catheter, coil reinforced tube, buckling, three-point bend, tensile

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Authors: Mohamed Abdelkareem

Abstract:

Remote sensing data contributed on predicting the prospective areas of water resources. Integration of microwave and multispectral data along with climatic, hydrologic, and geological data has been used here. In this article, Sentinel-2, Landsat-8 Operational Land Imager (OLI), Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), and Advanced Land Observing Satellite (ALOS) Phased Array Type L‐band Synthetic Aperture Radar (PALSAR) data were utilized to identify the geological, hydrologic and structural features of Wadi Asyuti which represents a defunct tributary of the Nile basin, in the eastern Sahara. The image transformation of Sentinel-2 and Landsat-8 data allowed characterizing the different varieties of rock units. Integration of microwave remotely-sensed data and GIS techniques provided information on physical characteristics of catchments and rainfall zones that are of a crucial role for mapping groundwater prospective zones. A fused Landsat-8 OLI and ALOS/PALSAR data improved the structural elements that difficult to reveal using optical data. Lineament extraction and interpretation indicated that the area is clearly shaped by the NE-SW graben that is cut by NW-SE trend. Such structures allowed the accumulation of thick sediments in the downstream area. Processing of recent OLI data acquired on March 15, 2014, verified the flood potential maps and offered the opportunity to extract the extent of the flooding zone of the recent flash flood event (March 9, 2014), as well as revealed infiltration characteristics. Several layers including geology, slope, topography, drainage density, lineament density, soil characteristics, rainfall, and morphometric characteristics were combined after assigning a weight for each using a GIS-based knowledge-driven approach. The results revealed that the predicted groundwater potential zones (GPZs) can be arranged into six distinctive groups, depending on their probability for groundwater, namely very low, low, moderate, high very, high, and excellent. Field and well data validated the delineated zones.

Keywords: GIS, remote sensing, groundwater, Egypt

Procedia PDF Downloads 98