Search results for: equivalent transformation algorithms

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: Giorgio Bertolazzi, Panayiotis Benos, Michele Tumminello, Claudia Coronnello

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MicroRNAs are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR (Combinatorial miRNA targeting) is a user friendly web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR incorporates miRNA expression in a thermodynamic binding model, and it associates each gene with the probability of being a target of a set of miRNAs. ComiR algorithms were trained with the information regarding binding sites in the 3’UTR region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein; this protein is a component of the microRNA induced silencing complex. In this work, we tested whether including coding region binding sites in the ComiR algorithm improves the performance of the tool in predicting microRNA targets. We focused the analysis on the D. melanogaster species and updated the ComiR underlying database with the currently available releases of mRNA and microRNA sequences. As a result, we find that the ComiR algorithm trained with the information related to the coding regions is more efficient in predicting the microRNA targets, with respect to the algorithm trained with 3’utr information. On the other hand, we show that 3’utr based predictions can be seen as complementary to the coding region based predictions, which suggests that both predictions, from 3'UTR and coding regions, should be considered in a comprehensive analysis. Furthermore, we observed that the lists of targets obtained by analyzing data from one experimental approach only, that is, inhibition or immunoprecipitation of AGO1, are not reliable enough to test the performance of our microRNA target prediction algorithm. Further analysis will be conducted to investigate the effectiveness of the tool with data from other species, provided that validated datasets, as obtained from the comparison of RISC proteins inhibition and immunoprecipitation experiments, will be available for the same samples. Finally, we propose to upgrade the existing ComiR web-tool by including the coding region based trained model, available together with the 3’UTR based one.

Keywords: AGO1, coding region, Drosophila melanogaster, microRNA target prediction

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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

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Authors: Pradeep Peiris, Hasini Lecamwasam

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The fluid, ambiguous, and often elusive existence of caste among the Sinhalese in Sri Lanka has inspired many scholarly endeavours. Originally, Sinhalese caste was organized according to the occupational functions assigned to various groups in society. Hence cultivators came to be known as Goyigama, washers Dobi, drummers Berava, smiths Navandanna and so on. During pre-colonial times the specialized services of various groups were deployed to build water reservoirs, cultivate the land, and/or sustain the Buddhist order by material means. However, as to how and why caste prevails today in Sinhalese society when labour is in ideal terms free to move where it wants, or in other words, occupation is no longer strictly determined or restricted by birth, is a question worth exploring. Hence this paper explores how, and perhaps more interestingly why, when the nexus between traditional occupations and caste status is fast disappearing, caste itself has managed to survive and continues to be salient in politics in Sri Lanka. In answer to this larger question, the paper looks at caste from three perspectives: 1) Buddhism, whose ethical project provides a justification of social stratifications that transcends economic bases 2) Capitalism that has reactivated and reproduced archaic relations in a process of 'accumulation by subordination', not only by reinforcing the marginality of peripheral caste groups, but also by exploiting caste divisions to hinder any realization of class interests and 3) Democracy whose supposed equalizing effect expected through its ‘one man–one vote’ approach has been subverted precisely by itself, whereby the aggregate ultimately comes down to how many such votes each ‘group’ in society has. This study draws from field work carried out in Dedigama (in the District of Kegalle, Central Province) and Kelaniya (in the District of Colombo, Western Province) in Sri Lanka over three years. The choice of field locations was encouraged by the need to capture rural and urban dynamics related to caste since caste is more apparently manifest in rural areas whose material conditions partially warrant its prevalence, whereas in urban areas it exists mostly in the ideological terrain. In building its analysis, the study has employed a combination of objectivist and subjectivist approaches to capture the material and ideological existence of caste and caste politics in Sinhalese society. Therefore, methods such as in-depth interviews, observation, and collection of demographical and interpretive data from secondary sources were used for this study. The paper has been situated in a critical theoretical framework of social inquiry in an attempt to question dominant assumptions regarding such meta-labels as ‘Capitalism’ and ‘Democracy’, and also the supposed emancipatory function of religion (focusing on Buddhism).

Keywords: Buddhism, capitalism, caste, democracy, Sri Lanka

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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Authors: Jillian M. Hagel, Joseph E. Tucker, Peter J. Facchini

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With the aim of establishing a holistic approach for the treatment of central nervous system (CNS) disorders, we are pursuing a drug development program rapidly progressing through discovery and characterization phases. The drug candidates identified in this program are referred to as neuroplastogens owing to their ability to mediate neuroplasticity, which can be beneficial to patients suffering from anxiety, depression, or posttraumatic stress disorder. These and other related neuropsychiatric conditions are associated with the onset of neuronal atrophy, which is defined as a reduction in the number and/or productivity of neurons. The stimulation of neuroplasticity results in an increase in the connectivity between neurons and promotes the restoration of healthy brain function. We have synthesized a substantial catalogue of proprietary indolethylamine derivatives based on the general structures of serotonin (5-hydroxytryptamine) and psychedelic molecules such as N,N-dimethyltryptamine (DMT) and psilocin (4-hydroxy-DMT) that function as neuroplastogens. A primary objective in our screening protocol is the identification of derivatives associated with a significant reduction in hallucination, which will allow administration of the drug at a dose that induces neuroplasticity and triggers other efficacious outcomes in the treatment of targeted CNS disorders but which does not cause a psychedelic response in the patient. Both neuroplasticity and hallucination are associated with engagement of the 5HT2A receptor, requiring drug candidates differentially coupled to these two outcomes at a molecular level. We use novel and proprietary artificial intelligence algorithms to predict the mode of binding to the 5HT2A receptor, which has been shown to correlate with the hallucinogenic response. Hallucination is tested using the mouse head-twitch response model, whereas mouse marble-burying and sucrose preference assays are used to evaluate anxiolytic and anti-depressive potential. Neuroplasticity is assays using dendritic outgrowth assays and cell-based ELISA analysis. Pharmacokinetics and additional receptor-binding analyses also contribute the selection of lead candidates. A summary of the program is presented.

Keywords: neuroplastogen, non-hallucinogenic, drug development, anxiety, depression, PTSD, indolethylamine derivatives, psychedelic-inspired, 5-HT2A receptor, computational chemistry, head-twitch response behavioural model, neurite outgrowth assay

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Authors: Kanduru Lokesh, Venkitasamy Kesavan

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The unique structural features of spiro-oxindoles with diverse biological activities have made them privileged structures in new drug discovery. The key structural characteristic of these compounds is the spiro ring fused at the C-3 position of the oxindole core with varied heterocyclic motifs. Structural diversification of heterocyclic scaffolds to synthesize new chemical entities as pharmaceuticals and agrochemicals is one of the important goals of synthetic organic chemists. Nitrogen and oxygen containing heterocycles are by far the most widely occurring privileged structures in medicinal chemistry. The structural complexity and distinct three-dimensional arrangement of functional groups of these privileged structures are generally responsible for their specificity against biological targets. Structurally diverse compound libraries have proved to be valuable assets for drug discovery against challenging biological targets. Thus, identifying a new combination of substituents at C-3 position on oxindole moiety is of great importance in drug discovery to improve the efficiency and efficacy of the drugs. The development of suitable methodology for the synthesis of spiro-oxindole compounds has attracted much interest often in response to the significant biological activity displayed by the both natural and synthetic compounds. So creating structural diversity of oxindole scaffolds is need of the decade and formidable challenge. A general way to improve synthetic efficiency and also to access diversified molecules is through the annulation reactions. Annulation reactions allow the formation of complex compounds starting from simple substrates in a single transformation consisting of several steps in an ecologically and economically favorable way. These observations motivated us to develop the annulation reaction protocol to enable the synthesis of a new class of spiro-oxindole motifs which in turn would enable the enhancement of molecular diversity. As part of our enduring interest in the development of novel, efficient synthetic strategies to enable the synthesis of biologically important oxindole fused spirocarbocyclic systems, We have developed an efficient methodology for the construction of highly functionalized spirocarbocyclic oxindoles through [4+2] annulation of phthalides via Hauser annulation. functionalized spirocarbocyclic oxindoles was accomplished for the first time in the literature using Hauser annulation strategy. The reaction between methyleneindolinones and arylsulfonylphthalides catalyzed by cesium carbonate led to the access of new class of biologically important spiro[indoline-3,2'-naphthalene] derivatives in very good yields. The synthetic utility of the annulated product was further demonstrated by fluorination Using NFSI as a fluorinating agent to furnish corresponding fluorinated product.

Keywords: Hauser-Kraus annulation, spiro carbocyclic oxindoles, oxindole-ester, fluoridation

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Authors: Oto J. Okwu, Ornan Henry, Victor A. Otene

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The agricultural sector contributes a great deal to the sustenance of Nigeria’s food security and economy, with an attendant impact on rural development. In spite of the relatively high number of farmers in the country, self-sufficiency in food production is still a challenge. Farmers are faced with myriad problems which hinder their production efficiency, one of which is their access to agricultural inputs required for optimum production. To meet the challenges faced by farmers, the government at the federal level has come up with many agricultural policies, one of which is the Agricultural Transformation Agenda (ATA). The Growth Enhancement Support Scheme (GESS) is one of the critical components of ATA, which is aimed at ensuring the effective distribution of agricultural inputs delivered directly to farmers, and at a regulated cost. After about 8 years of launching this policy, it will be necessary to carry out an assessment of GESS and determine the impact it has made on rural farmers with respect to their access to farm inputs. This study was carried out to assess the Growth Enhancement Support Scheme (GESS) in Adamawa State, Nigeria. Crop farmers who registered under the GESS in Adamawa State, Nigeria, formed the population for the study. Primary data for the study were obtained through a survey, and the use of a structured questionnaire. A sample size of 167 respondents was selected using multi-stage, purposive, and random sampling techniques. The validity and reliability of the research instrument (questionnaire) were obtained through pilot testing and test-retest method, respectively. The objectives of the study were to determine the difference in the level of access to agricultural inputs before and after GESS, determine the difference in cost of agricultural inputs before and after GESS, and to determine the challenges faced by rural farmers in accessing agricultural inputs through GESS. Both descriptive and inferential statistics were used in analyzing the collected data. Specifically, Mann-Whitney, student t-test, and factor analysis were used to test the stated hypotheses. Research findings revealed there was a significant difference in the level of access to farm inputs after the introduction of GESS (Z=14.216). Also, there was a significant difference in the cost of agro-inputs after the introduction of GESS (Pr |T| > |t|= 0.0000). The challenges faced by respondents in accessing agro-inputs through GESS were administrative and technical in nature. Based on the findings of the research, it was recommended that efforts be made by the government to sustain the GESS, as it has significantly improved the level of farmers’ access to agricultural inputs and has reduced the cost of agro-inputs, while administrative challenges faced by the respondents in accessing inputs be addressed by the government, and extension agents assist the farmers to overcome the technical challenges they face in accessing inputs.

Keywords: agricultural policy, agro-inputs, assessment, growth enhancement support scheme, rural farmers

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: C. Román, M. Guevara, P. Salas, D. Duclap, J. Houenou, C. Poupon, J. F. Mangin, P. Guevara

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Diffusion Magnetic Resonance Imaging (dMRI) allows the non-invasive study of human brain white matter. From diffusion data, it is possible to reconstruct fiber trajectories using tractography algorithms. Our previous work consists in an automatic method for the identification of short association bundles of the superficial white matter (SWM), based on a whole brain inter-subject hierarchical clustering applied to a HARDI database. The method finds representative clusters of similar fibers, belonging to a group of subjects, according to a distance measure between fibers, using a non-linear registration (DTI-TK). The algorithm performs an automatic labeling based on the anatomy, defined by a cortex mesh parcelated with FreeSurfer software. The clustering was applied to two independent groups of 37 subjects. The clusters resulting from both groups were compared using a restrictive threshold of mean distance between each pair of bundles from different groups, in order to keep reproducible connections. In the left hemisphere, 48 reproducible bundles were found, while 43 bundles where found in the right hemisphere. An inter-hemispheric bundle correspondence was then applied. The symmetric horizontal reflection of the right bundles was calculated, in order to obtain the position of them in the left hemisphere. Next, the intersection between similar bundles was calculated. The pairs of bundles with a fiber intersection percentage higher than 50% were considered similar. The similar bundles between both hemispheres were fused and symmetrized. We obtained 30 common bundles between hemispheres. An atlas was created with the resulting bundles and used to segment 78 new subjects from another HARDI database, using a distance threshold between 6-8 mm according to the bundle length. Finally, a laterality index was calculated based on the bundle volume. Seven bundles of the atlas presented right laterality (IP_SP_1i, LO_LO_1i, Op_Tr_0i, PoC_PoC_0i, PoC_PreC_2i, PreC_SM_0i, y RoMF_RoMF_0i) and one presented left laterality (IP_SP_2i), there is no tendency of lateralization according to the brain region. Many factors can affect the results, like tractography artifacts, subject registration, and bundle segmentation. Further studies are necessary in order to establish the influence of these factors and evaluate SWM laterality.

Keywords: dMRI, hierarchical clustering, lateralization index, tractography

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Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Cemil Kutlutürk

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Hindu culture and religious doctrines such as caste, reincarnation, yoga, nirvana have always proved a popular theme for the film industry. The analyzing of these motifs in the movies with a scientific approach enables to individuals either to comprehend the messages and deep meanings of films or to understand others’ religious beliefs systems and daily lives in a properly way. The primary aim of this study is to handle the subtle influence of Hindu doctrines on cinema industry by focusing on James Cameron’s film, Avatar and its relationship with Hindu concept of avatara by referring to original Hindu sacred texts where this doctrine is basically clarified. The Sanskrit word avatara means to come down or to descend. Although an avatara is commonly considered as an appearance of any deity on earth, the term refers the Vishnu’s descending on earth. When the movie avatar and avatara doctrine are compared, various similarities have noteworthy revealed. Firstly in the movie, Jake is chosen by Eywa to protect Pandora from evils. Similarly in the movie, avatar is born when there is a rise of jealousy and unrighteousness. The same concept is found in avatara doctrine. According to this belief whenever righteousness (dharma) wanes and unrighteousness (adharma) increases God incarnates himself as an avatara. In Hindu tradition, the ten avataras of Vishnu are the most popular. This standard list of ten avataras includes the Fish, the Tortoise, the Boar, the Man-Lion (Narasimha), the Dwarf, Parasurama, Rama, Krishna, the Buddha and Kalki. In the movie the avatar has tail, eyes, nose, ear which is similar to Narasimha (half man-half lion) avatara. On the other hand use of bow and arrow by Navis in the film, evokes us Rama avatara whose basic gun is same. Navis fly on a dragon like bird called Ikra and ride a horse-like quadruped animal. The vehicle for transformation of the avatar in the movie is also resemblance with the idea of Garuda, the great mythical bird, which is used by Vishnu in Hindu mythology. In addition, the last avatara, Kalki, will be seen on a white horse according to Puranas. The basic difference is that for Hinduism avatara means descent of a God, yet in the movie, a human being named Jake Sully, is manifested as humanoid of another planet, this is called as avatar. While in the movie the avatar manifests himself in another planet, Pandora, in Hinduism avataras descent on this world. On the other hand, in Hindu scriptures, there are many avataras and they are categorized according to their functions and attributes. These sides of avatara doctrine cannot be also seen clearly in the film. Even though there are some differences between each other, the main hypothesis of this study is that the general character of the movie is similar to avatara doctrine. In the movie instead of emphasizing on a specific avatara, qualities of different Vishnu avataras have been properly used.

Keywords: film industry, Hinduism, incarnation, James Cameron, movie avatar

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Authors: Chen Yao, Wang Ke

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Small towns are the most basic administrative institutions in our country, which are connected with cities and rural areas. Small towns play an important role in promoting local urban and rural economic development, providing the main public services and maintaining social stability in social governance. With the vigorous development of small towns and the transformation of industrial structure, the changes of social structure, spatial structure, and lifestyle are lagging behind, causing that the spatial form and landscape style do not belong to both cities and rural areas, and seriously affecting the quality of people’s life space and environment. The rural economy in Zhejiang Province has started, the society and the population are also developing in relative stability. In September 2016, Zhejiang Province set out the 'Technical Guidelines for Comprehensive Environmental Remediation of Small Towns in Zhejiang Province,' so as to comprehensively implement the small town comprehensive environmental remediation with the main content of strengthening the plan and design leading, regulating environmental sanitation, urban order and town appearance. In November 2016, Huzhou City started the comprehensive environmental improvement of small towns, strived to use three years to significantly improve the 115 small towns, as well as to create a number of high quality, distinctive and beautiful towns with features of 'clean and livable, rational layout, industrial development, poetry and painting style'. This paper takes Meixi Town, Zhangwu Town and Sanchuan Village in Huzhou City as the empirical cases, analyzes the small town public space by applying the relative theory of actor-network and space syntax. This paper also analyzes the spatial composition in actor and social structure elements, as well as explores the relationship of actor’s spatial practice and public open space by combining with actor-network theory. This paper introduces the relevant theories and methods of spatial syntax, carries out research analysis and design planning analysis of small town spaces from the perspective of quantitative analysis. And then, this paper proposes the effective updating strategy for the existing problems in public space. Through the planning and design in the building level, the dissonant factors produced by various spatial combination of factors and between landscape design and urban texture during small town development will be solved, inhabitant quality of life will be promoted, and town development vitality will be increased.

Keywords: small towns, urbanization, public space, updating

Procedia PDF Downloads 204

Authors: Marcela De Oliveira, Marina P. Da Silva, Fernando C. G. Da Rocha, Jorge M. Santos, Jaime S. Cardoso, Paulo N. Lisboa-Filho

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Multiple Sclerosis (MS) is an immune-mediated disease of the central nervous system characterized by neurodegeneration, inflammation, demyelination, and axonal loss. Magnetic resonance imaging (MRI), due to the richness in the information details provided, is the gold standard exam for diagnosis and follow-up of neurodegenerative diseases, such as MS. Brain atrophy, the gradual loss of brain volume, is quite extensive in multiple sclerosis, nearly 0.5-1.35% per year, far off the limits of normal aging. Thus, the brain volume quantification becomes an essential task for future analysis of the occurrence atrophy. The analysis of MRI has become a tedious and complex task for clinicians, who have to manually extract important information. This manual analysis is prone to errors and is time consuming due to various intra- and inter-operator variability. Nowadays, computerized methods for MRI segmentation have been extensively used to assist doctors in quantitative analyzes for disease diagnosis and monitoring. Thus, the purpose of this work was to evaluate the brain volume in MRI of MS patients. We used MRI scans with 30 slices of the five patients diagnosed with multiple sclerosis according to the McDonald criteria. The computational methods for the analysis of images were carried out in two steps: segmentation of the brain and brain volume quantification. The first image processing step was to perform brain extraction by skull stripping from the original image. In the skull stripper for MRI images of the brain, the algorithm registers a grayscale atlas image to the grayscale patient image. The associated brain mask is propagated using the registration transformation. Then this mask is eroded and used for a refined brain extraction based on level-sets (edge of the brain-skull border with dedicated expansion, curvature, and advection terms). In the second step, the brain volume quantification was performed by counting the voxels belonging to the segmentation mask and converted in cc. We observed an average brain volume of 1469.5 cc. We concluded that the automatic method applied in this work can be used for the brain extraction process and brain volume quantification in MRI. The development and use of computer programs can contribute to assist health professionals in the diagnosis and monitoring of patients with neurodegenerative diseases. In future works, we expect to implement more automated methods for the assessment of cerebral atrophy and brain lesions quantification, including machine-learning approaches. Acknowledgements: This work was supported by a grant from Brazilian agency Fundação de Amparo à Pesquisa do Estado de São Paulo (number 2019/16362-5).

Keywords: brain volume, magnetic resonance imaging, multiple sclerosis, skull stripper

Procedia PDF Downloads 112

Authors: Saeed Nazari, Masoom Nazari, Ali Hejazi, Siamak Sanoobari Ghazi Jahani, Mohammad Dehghani, Javad Vakili

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More than ever, digitization is an imperative for businesses to keep their competitive advantages, foster innovation and reduce paperwork. To design and successfully implement digital transformation initiatives within process safety management system, employees need to be equipped with the right tool, frameworks, and best practices. we developed a unique full stack application so-called SHEQTool which is entirely dynamic based on our extensive expertise, experience, and client feedback to help business processes particularly operations safety management. We use our best knowledge and scientific methodologies published by CCPS and OSHA Guidelines to streamline operations and integrated them into task management within Petrochemical Companies. We digitalize their main process safety management system elements and their sub elements such as hazard identification and risk management, training and communication, inspection and audit, critical changes management, contractor management, permit to work, pre-start-up safety review, incident reporting and investigation, emergency response plan, personal protective equipment, occupational health, and action management in a fully customizable manner with no programming needs for users. We review the feedback from main actors within petrochemical plant which highlights improving their business performance and productivity as well as keep tracking their functions’ key performance indicators (KPIs) because it; 1) saves time, resources, and costs of all paperwork on our businesses (by Digitalization); 2) reduces errors and improve performance within management system by covering most of daily software needs of the organization and reduce complexity and associated costs of numerous tools and their required training (One Tool Approach); 3) focuses on management systems and integrate functions and put them into traceable task management (RASCI and Flowcharting); 4) helps the entire enterprise be resilient to any change of your processes, technologies, assets with minimum costs (through Organizational Resilience); 5) reduces significantly incidents and errors via world class safety management programs and elements (by Simplification); 6) gives the companies a systematic, traceable, risk based, process based, and science based integrated management system (via proper Methodologies); 7) helps business processes complies with ISO 9001, ISO 14001, ISO 45001, ISO 31000, best practices as well as legal regulations by PDCA approach (Compliance).

Keywords: process, safety, digitalization, management, risk, incident, SHEQTool, OSHA, CCPS

Procedia PDF Downloads 23

Authors: Prince Vivek, Vijay K. Bharti, Manishi Mukesh, Ankita Sharma, Om Prakash Chaurasia, Bhuvnesh Kumar

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High performance of endurance in equid requires adaptive changes involving physio-biochemical, and molecular responses in an attempt to regain homeostasis. We hypothesized that the identification of the suitable reference genes might be considered for assessing of endurance related traits in pony at high altitude and may ensure for individuals struggling to potent endurance trait in ponies at high altitude. A total of 12 mares of ponies, Zanskar breed, were divided into three groups, group-A (without load), group-B, (60 Kg) and group-C (80 Kg) on backpack loads were subjected to a load carry protocol, on a steep climb of 4 km uphill, and of gravel, uneven rocky surface track at an altitude of 3292 m to 3500 m (endpoint). Blood was collected before and immediately after the load carry on sodium heparin anticoagulant, and the peripheral blood mononuclear cell was separated for total RNA isolation and thereafter cDNA synthesis. Real time-PCR reactions were carried out to evaluate the mRNAs expression profile of a panel of putative internal control genes (ICGs), related to different functional classes, namely glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β₂ microglobulin (β₂M), β-actin (ACTB), ribosomal protein 18 (RS18), hypoxanthine-guanine phosophoribosyltransferase (HPRT), ubiquitin B (UBB), ribosomal protein L32 (RPL32), transferrin receptor protein (TFRC), succinate dehydrogenase complex subunit A (SDHA) for normalizing the real-time quantitative polymerase chain reaction (qPCR) data of native pony’s. Three different algorithms, geNorm, NormFinder, and BestKeeper software, were used to evaluate the stability of reference genes. The result showed that GAPDH was best stable gene and stability value for the best combination of two genes was observed TFRC and β₂M. In conclusion, the geometric mean of GAPDH, TFRC and β₂M might be used for accurate normalization of transcriptional data for assessing endurance related traits in Zanskar ponies during load carrying.

Keywords: endurance exercise, ubiquitin B (UBB), β₂ microglobulin (β₂M), high altitude, Zanskar ponies, reference gene

Procedia PDF Downloads 112

Authors: Sylwia Krawiec, Joanna Cabaj, Karol Malecha

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Nowadays, progress in the field of the analytical methods is of great interest for reliable biological research and medical diagnostics. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements. Chemical sensors have displaced the conventional analytical methods - sensors combine precision, sensitivity, fast response and the possibility of continuous-monitoring. Biosensor is a chemical sensor, which except of conventer also possess a biologically active material, which is the basis for the detection of specific chemicals in the sample. Each biosensor device mainly consists of two elements: a sensitive element, where is recognition of receptor-analyte, and a transducer element which receives the signal and converts it into a measurable signal. Through these two elements biosensors can be divided in two categories: due to the recognition element (e.g immunosensor) and due to the transducer (e.g optical sensor). Working of optical sensor is based on measurements of quantitative changes of parameters characterizing light radiation. The most often analyzed parameters include: amplitude (intensity), frequency or polarization. Changes in the optical properties one of the compound which reacts with biological material coated on the sensor is analyzed by a direct method, in an indirect method indicators are used, which changes the optical properties due to the transformation of the testing species. The most commonly used dyes in this method are: small molecules with an aromatic ring, like rhodamine, fluorescent proteins, for example green fluorescent protein (GFP), or nanoparticles such as quantum dots (QDs). Quantum dots have, in comparison with organic dyes, much better photoluminescent properties, better bioavailability and chemical inertness. These are semiconductor nanocrystals size of 2-10 nm. This very limited number of atoms and the ‘nano’-size gives QDs these highly fluorescent properties. Rapid and sensitive detection of dopamine is extremely important in modern medicine. Dopamine is very important neurotransmitter, which mainly occurs in the brain and central nervous system of mammals. Dopamine is responsible for the transmission information of moving through the nervous system and plays an important role in processes of learning or memory. Detection of dopamine is significant for diseases associated with the central nervous system such as Parkinson or schizophrenia. In developed optical biosensor for detection of dopamine, are used graphene quantum dots (GQDs). In such sensor dopamine molecules coats the GQD surface - in result occurs quenching of fluorescence due to Resonance Energy Transfer (FRET). Changes in fluorescence correspond to specific concentrations of the neurotransmitter in tested sample, so it is possible to accurately determine the concentration of dopamine in the sample.

Keywords: biosensor, dopamine, fluorescence, quantum dots

Procedia PDF Downloads 341

Authors: Merab Khokhobaia

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The research of Georgian tourism policy challenges is important, as the tourism can play an increasing role for the economic growth and improvement of standard of living of the country even with scanty resources, at the expense of improved creative approaches. It is also important to make correct decisions at macroeconomic level, which will be accordingly reflected in the successful functioning of the travel companies and finally, in the improvement of economic indicators of the country. In order to correctly orient sectoral policy, it is important to precisely determine its role in the economy. Development of travel industry has been considered as one of the priorities in Georgia; the country has unique cultural heritage and traditions, as well as plenty of natural resources, which are a significant precondition for the development of tourism. Despite the factors mentioned above, the existing resources are not completely utilized and exploited. This work represents a study of subjective, as well as objective reasons of ineffective functioning of the sector. During the years of transformation experienced by Georgia, the role of travel industry in economic development of the country represented the subject of continual discussions. Such assessments were often biased and they did not rest on specific calculations. This topic became especially popular on the ground of market economy, because reliable statistical data have a particular significance in the designing of tourism policy. In order to deeply study the aforementioned issue, this paper analyzes monetary, as well as non-monetary indicators. The research widely included the tourism indicators system; we analyzed the flaws in reporting of the results of tourism sector in Georgia. Existing defects are identified and recommendations for their improvement are offered. For stable development tourism, similarly to other economic sectors, needs a well-designed policy from the perspective of national, as well as local, regional development. The tourism policy must be drawn up in order to efficiently achieve our goals, which were established in short-term and long-term dynamics on the national or regional scale of specific country. The article focuses on the role and responsibility of the state institutes in planning and implementation of the tourism policy. The government has various tools and levers, which may positively influence the processes. These levers are especially important in terms of international, as well as internal tourism development. Within the framework of this research, the regulatory documents, which are in force in relation to this industry, were also analyzed. The main attention is turned to their modernization and necessity of their compliance with European standards. It is a current issue to direct the efforts of state policy on support of business by implementing infrastructural projects, as well as by development of human resources, which may be possible by supporting the relevant higher and vocational studying-educational programs.

Keywords: regional development, tourism industry, tourism policy, transition

Procedia PDF Downloads 241

Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

Procedia PDF Downloads 117

Authors: U. Demir

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18th century which is the period of 'change' in the Ottoman Empire, affects the architecture as well, where the Classical period is left behind, architecture is differentiated in the form language. This change is especially noticeable in monumental buildings and thus manifested itself in the mosques. But, is it possible to talk about the structural context of the 'change' which has been occurred in decoration? The aim of this study is to investigate the changes and classical relations of the 18th century mosques through plan schedules and structure systems. This study focuses on the monumental mosques constructed during the reign of the three sultans who ruled in the second half of the century (Mustafa the 3rd 1757-1774, Abdülhamid the 1st 1774-1789 and Selim the 3rd). According to their construction years these are 'Ayazma, Laleli, Zeyneb Sultan, Fatih, Beylerbeyi, Şebsefa Kadın, Eyüb Sultan, Mihrişah Valide Sultan and Üsküdar-Selimiye' mosques. As a plan scheme, four mosques have a square or close to a rectangular square scheme, while the others have a rectangle scheme and showing the longitudinal development of the mihrab axis. This situation is widespread throughout the period. In addition to the longitudinal development plan, which is the general characteristic of the 18th century mosques, the use of the classical plan schemes continued in the same direction. Spatialization of the mihrab area was applied to the five mosques while other mosques were applied as niches on the wall surface. This situation is widespread in the period of the second half of the century. In the classical period, the lodges may be located at the back of the mosques interior, not interfering with the main worship area. In the period, the lodges were withdrawn from the main worship area. They are separated from the main interior with their own structural and covering systems. The plans seem to be formed as a result of the addition of lodge parts to the northern part of the Classical period mosques. The 18th century mosques are the constructions where the change of the architectural language and style can be observed easily. This change and the break from the classical period manifest themselves quickly in the structural elements, wall surface decorations, pencil work designs, small scale decor elements, motifs. The speed and intensity of change in the decor does not occur the same as in structural context. The mosque construction rules from the traditional and classical era still continues in the century. While some mosque structures have a plan which is inherited from the classical successor, some of were constructed with the same classical period rules. Nonetheless, the location and transformation of the lodges, which are affecting the interior design, are noteworthy. They provide a significant transition on the way to the new language of the mosque design that will be experienced in the next century. It is intended to draw attention to the structural evolution of the 18th century Ottoman architecture through the royal mosques within the scope of this conference.

Keywords: mosque structure, Ottoman architecture, structural evolution, 18th century architecture

Procedia PDF Downloads 174

Authors: Tatiana V. Melnikova, Lyudmila P. Polyakova, Alla A. Oudalova

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As a result of environmental pollution, the production of agriculture and foodstuffs inevitably contain residual amounts of Persistent Organic Pollutants (POP). The special attention must be given to organic pollutants, including various organochlorinated pesticides (OCP). Among priorities, OCP is DDT (and its metabolite DDE), alfa-HCH, gamma-HCH (lindane). The control of these substances spends proceeding from requirements of sanitary norms and rules. During too time often is lost sight of that the primary product can pass technological processing (in particular irradiation treatment) as a result of which transformation of physicochemical forms of initial polluting substances is possible. The goal of the present work was to study the OCP radiation degradation at a various gamma-radiation dosimetric characteristics. The problems posed for goal achievement: to evaluate the content of the priority of OCPs in food; study the character the degradation of OCP in model solutions (with micro concentrations commensurate with the real content of their agricultural and food products) depending upon dosimetric characteristics of gamma-radiation. Qualitative and quantitative analysis of OCP in food and model solutions by gas chromatograph Varian 3400 (Varian, Inc. (USA)); chromatography-mass spectrometer Varian Saturn 4D (Varian, Inc. (USA)) was carried out. The solutions of DDT, DDE, alpha- and gamma- isomer HCH (0.01, 0.1, 1 ppm) were irradiated on "Issledovatel" (60Co) and "Luch - 1" (60Co) installations at a dose 10 kGy with a variation of dose rate from 0.0083 up to 2.33 kGy/sec. It was established experimentally that OCP residual concentration in individual samples of food products (fish, milk, cereal crops, meat, butter) are evaluated as 10-1-10-4 mg/kg, the value of which depends on the factor-sensations territory and natural migration processes. The results were used in the preparation of model solutions OCP. The dependence of a degradation extent of OCP from a dose rate gamma-irradiation has complex nature. According to our data at a dose 10 kGy, the degradation extent of OCP at first increase passes through a maximum (over the range 0.23 – 0.43 Gy/sec), and then decrease with the magnification of a dose rate. The character of the dependence of a degradation extent of OCP from a dose rate is kept for various OCP, in polar and nonpolar solvents and does not vary at the change of concentration of the initial substance. Also in work conditions of the maximal radiochemical yield of OCP which were observed at having been certain: influence of gamma radiation with a dose 10 kGy, in a range of doses rate 0.23 – 0.43 Gy/sec; concentration initial OCP 1 ppm; use of solvent - 2-propanol after preliminary removal of oxygen. Based on, that at studying model solutions of OCP has been established that the degradation extent of pesticides and qualitative structure of OCP radiolysis products depend on a dose rate, has been decided to continue researches radiochemical transformations OCP into foodstuffs at various of doses rate.

Keywords: degradation extent, dosimetric characteristics, gamma-radiation, organochlorinated pesticides, persistent organic pollutants

Procedia PDF Downloads 226

Authors: Hoda Rahmani, Gary Weckman

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The body of research examining the integration of drones into various industries is expanding rapidly. Despite progress made in addressing the cybersecurity concerns for commercial drones, knowledge deficits remain in determining potential occupational hazards and risks of drone use to employees’ well-being and health in the workplace. This creates difficulty in identifying key approaches to risk mitigation strategies and thus reflects the need for raising awareness among employers, safety professionals, and policymakers about workplace drone-related accidents. The purpose of this study is to investigate the prevalence of and possible risk factors for drone-related mishaps by comparing the application of drones in construction with manufacturing industries. The chief reason for considering these specific sectors is to ascertain whether there exists any significant difference between indoor and outdoor flights since most construction sites use drones outside and vice versa. Therefore, the current research seeks to examine the causes and patterns of workplace drone-related mishaps and suggest possible ergonomic interventions through data collection. Potential ergonomic practices to mitigate hazards associated with flying drones could include providing operators with professional pieces of training, conducting a risk analysis, and promoting the use of personal protective equipment. For the purpose of data analysis, two data mining techniques, the random forest and association rule mining algorithms, will be performed to find meaningful associations and trends in data as well as influential features that have an impact on the occurrence of drone-related accidents in construction and manufacturing sectors. In addition, Spearman’s correlation and chi-square tests will be used to measure the possible correlation between different variables. Indeed, by recognizing risks and hazards, occupational safety stakeholders will be able to pursue data-driven and evidence-based policy change with the aim of reducing drone mishaps, increasing productivity, creating a safer work environment, and extending human performance in safe and fulfilling ways. This research study was supported by the National Institute for Occupational Safety and Health through the Pilot Research Project Training Program of the University of Cincinnati Education and Research Center Grant #T42OH008432.

Keywords: commercial drones, ergonomic interventions, occupational safety, pattern recognition

Procedia PDF Downloads 181

Authors: Norhalim Yunus, Mohamad Husaini Dahalan, Nor Halina Ghazali

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Building technology start-ups from ground zero into world-class companies in form and substance present a rare opportunity for government-affiliated institutions in Malaysia. The challenge of building such start-ups becomes tougher when their core businesses involve commercialization of unproven technologies for the mass market. These simple truths, while difficult to execute, will go a long way in getting a business off the ground and flying high. Malaysian Technology Development Corporation (MTDC), a company founded to facilitate the commercial exploitation of R&D findings from research institutions and universities, and eventually help translate these findings of applications in the marketplace, is an excellent case in point. The purpose of this paper is to examine MTDC as an institution as it explores the concept of ‘it takes a village to raise a child’ in an effort to create and nurture start-ups into established world class Malaysian technology companies. With MTDC at the centre of Malaysia's innovative start-ups, the analysis seeks to specifically answer two questions: How has the concept been applied in MTDC? and what can we learn from this successful case? A key aim is to elucidate how MTDC's journey as a private limited company can help leverage reforms and achieve transformation, a process that might be suitable for other small, open, third world and developing countries. This paper employs a single case study, designed to acquire an in-depth understanding of how MTDC has developed and grown technology start-ups to world-class technology companies. The case study methodology is employed as the focus is on a contemporary phenomenon within a real business context. It also explains the causal links in real-life situations where a single survey or experiment is unable to unearth. The findings show that MTDC maximises the concept of it needs a village to raise a child in totality, as MTDC itself assumes the role of the innovator to 'raise' start-up companies into world-class stature. As the innovator, MTDC creates shared value and leadership, introduces innovative programmes ahead of the curve, mobilises talents for optimum results and aggregates knowledge for personnel advancement. The success of the company's effort is attributed largely to leadership, visionary, adaptability, commitment to innovate, partnership and networking, and entrepreneurial drive. The findings of this paper are however limited by the single case study of MTDC. Future research is required to study more cases of success or/and failure where the concept of it takes a village to raise a child have been explored and applied.

Keywords: start-ups, technology transfer, commercialization, technology incubator

Procedia PDF Downloads 123

Authors: P. Naderi, M. N. Ouarzazi, S. C. Hirata, H. Ben Hamed, H. Beji

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The stability of mixed convection in a Newtonian fluid medium heated from below and cooled from above, also known as the Poiseuille-Rayleigh-Bénard problem, has been extensively investigated in the past decades. To our knowledge, mixed convection in porous media has received much less attention in the published literature. The present paper extends the mixed convection problem in porous media for the case of a viscoelastic fluid flow owing to its numerous environmental and industrial applications such as the extrusion of polymer fluids, solidification of liquid crystals, suspension solutions and petroleum activities. Without a superimposed through-flow, the natural convection problem of a viscoelastic fluid in a saturated porous medium has already been treated. The effects of the viscoelastic properties of the fluid on the linear and nonlinear dynamics of the thermoconvective instabilities have also been treated in this work. Consequently, the elasticity of the fluid can lead either to a Hopf bifurcation, giving rise to oscillatory structures in the strongly elastic regime, or to a stationary bifurcation in the weakly elastic regime. The objective of this work is to examine the influence of the main horizontal flow on the linear and characteristics of these two types of instabilities. Under the Boussinesq approximation and Darcy's law extended to a viscoelastic fluid, a temporal stability approach shows that the conditions for the appearance of longitudinal rolls are identical to those found in the absence of through-flow. For the general three-dimensional (3D) perturbations, a Squire transformation allows the deduction of the complex frequencies associated with the 3D problem using those obtained by solving the two-dimensional one. The numerical resolution of the eigenvalue problem concludes that the through-flow has a destabilizing effect and selects a convective configuration organized in purely transversal rolls which oscillate in time and propagate in the direction of the main flow. In addition, by using the mathematical formalism of absolute and convective instabilities, we study the nature of unstable three-dimensional disturbances. It is shown that for a non-vanishing through-flow, general three-dimensional instabilities are convectively unstable which means that in the absence of a continuous noise source these instabilities are drifted outside the porous medium, and no long-term pattern is observed. In contrast, purely transversal rolls may exhibit a transition to absolute instability regime and therefore affect the porous medium everywhere including in the absence of a noise source. The absolute instability threshold, the frequency and the wave number associated with purely transversal rolls are determined as a function of the Péclet number and the viscoelastic parameters. Results are discussed and compared to those obtained from laboratory experiments in the case of Newtonian fluids.

Keywords: instability, mixed convection, porous media, and viscoelastic fluid

Procedia PDF Downloads 314

Authors: Anna Stepien

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The paper presents the results of research on modifications of sand-lime bricks, especially using glass additives (glass fiber and glass sand) and other additives (e.g.:basalt&barite aggregate, lithium silicate and microsilica) as well. The main goal of this paper is to answer the question ‘How to use glass additives in the sand-lime mass and get a better bricks?’ The article contains information on modification of sand-lime bricks using glass fiber, glass sand, microsilica (different structure of silica). It also presents the results of the conducted compression tests, which were focused on compressive strength, water absorption, bulk density, and their microstructure. The Scanning Electron Microscope, spectrum EDS, X-ray diffractometry and DTA analysis helped to define the microstructural changes of modified products. The interpretation of the products structure revealed the existence of diversified phases i.e.the C-S-H and tobermorite. CaO-SiO2-H2O system is the object of intensive research due to its meaning in chemistry and technologies of mineral binding materials. Because the blocks are the autoclaving materials, the temperature of hydrothermal treatment of the products is around 200°C, the pressure - 1,6-1,8 MPa and the time - up to 8hours (it means: 1h heating + 6h autoclaving + 1h cooling). The microstructure of the products consists mostly of hydrated calcium silicates with a different level of structural arrangement. The X-ray diffraction indicated that the type of used sand is an important factor in the manufacturing of sand-lime elements. Quartz sand of a high hardness is also a substrate hardly reacting with other possible modifiers, which may cause deterioration of certain physical and mechanical properties. TG and DTA curves show the changes in the weight loss of the sand-lime bricks specimen against time as well as the endo- and exothermic reactions that took place. The endothermic effect with the maximum at T=573°C is related to isomorphic transformation of quartz. This effect is not accompanied by a change of the specimen weight. The next endothermic effect with the maximum at T=730-760°C is related to the decomposition of the calcium carbonates. The bulk density of the brick it is 1,73kg/dm3, the presence of xonotlite in the microstructure and significant weight loss during DTA and TG tests (around 0,6% after 70 minutes) have been noticed. Silicate elements were assessed on the basis of their compressive property. Orthogonal compositional plan type 3k (with k=2), i.e.full two-factor experiment was applied in order to carry out the experiments both, in the compression strength test and bulk density test. Some modification (e.g.products with barite and basalt aggregate) have improved the compressive strength around 41.3 MPa and water absorption due to capillary raising have been limited to 12%. The next modification was adding glass fiber to sand-lime mass, then glass sand. The results show that the compressive strength was higher than in the case of traditional bricks, while modified bricks were lighter.

Keywords: bricks, fiber, glass, microstructure

Procedia PDF Downloads 329

Authors: Binyam Teferi

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Numerical and theoretical analysis of mixed convection flow of magneto- hydrodynamics micropolar fluid with stretching capillary in the presence of thermal radiation, chemical reaction, viscous dissipation, and heat generation/ absorption have been studied. The non-linear partial differential equations of momentum, angular velocity, energy, and concentration are converted into ordinary differential equations using similarity transformations which can be solved numerically. The dimensionless governing equations are solved by using Runge Kutta fourth and fifth order along with the shooting method. The effect of physical parameters viz., micropolar parameter, unsteadiness parameter, thermal buoyancy parameter, concentration buoyancy parameter, Hartmann number, spin gradient viscosity parameter, microinertial density parameter, thermal radiation parameter, Prandtl number, Eckert number, heat generation or absorption parameter, Schmidt number and chemical reaction parameter on flow variables viz., the velocity of the micropolar fluid, microrotation, temperature, and concentration has been analyzed and discussed graphically. MATLAB code is used to analyze numerical and theoretical facts. From the simulation study, it can be concluded that an increment of micropolar parameter, Hartmann number, unsteadiness parameter, thermal and concentration buoyancy parameter results in decrement of velocity flow of micropolar fluid; microrotation of micropolar fluid decreases with an increment of micropolar parameter, unsteadiness parameter, microinertial density parameter, and spin gradient viscosity parameter; temperature profile of micropolar fluid decreases with an increment of thermal radiation parameter, Prandtl number, micropolar parameter, unsteadiness parameter, heat absorption, and viscous dissipation parameter; concentration of micropolar fluid decreases as unsteadiness parameter, Schmidt number and chemical reaction parameter increases. Furthermore, computational values of local skin friction coefficient, local wall coupled coefficient, local Nusselt number, and local Sherwood number for different values of parameters have been investigated. In this paper, the following important results are obtained; An increment of micropolar parameter and Hartmann number results in a decrement of velocity flow of micropolar fluid. Microrotation decreases with an increment of the microinertial density parameter. Temperature decreases with an increasing value of the thermal radiation parameter and viscous dissipation parameter. Concentration decreases as the values of Schmidt number and chemical reaction parameter increases. The coefficient of local skin friction is enhanced with an increase in values of both the unsteadiness parameter and micropolar parameter. Increasing values of unsteadiness parameter and micropolar parameter results in an increment of the local couple stress. An increment of values of unsteadiness parameter and thermal radiation parameter results in an increment of the rate of heat transfer. As the values of Schmidt number and unsteadiness parameter increases, Sherwood number decreases.

Keywords: thermal radiation, chemical reaction, viscous dissipation, heat absorption/ generation, similarity transformation

Procedia PDF Downloads 94

Authors: Evans V. Mauda, Stefan H. Foord, Thinandavha C. Munyai

Abstract:

The greatest threat to biodiversity is a loss of habitat through landscape fragmentation and attrition. Land use changes are therefore among the most immediate drivers of species diversity. Urbanization and agriculture are the main drivers of habitat loss and transformation in the Savanna biomes of South Africa. Agricultural expansion and the intensification in particular, take place at the expense of biodiversity and will probably be the primary driver of biodiversity loss in this century. Arthropods show measurable behavioural responses to changing land mosaics at the smallest scale and heterogeneous environments are therefore predicted to support more complex and diverse biological assemblages. Ants are premier soil turners, channelers of energy and dominate insect fauna, while spiders are a mega-diverse group that can regulate other invertebrate populations. This study aims to quantify the response of these two taxa in a rural-urban mosaic of a rapidly developing communal area. The study took place in and around two villages in the north-eastern corner of South Africa. Two replicates for each of the dominant land use categories, viz. urban settlements, dryland cultivation and cattle rangelands, were set out in each of the villages and sampled during the dry and wet seasons for a total of 2 villages × 3 land use categories × 2 seasons = 24 assemblages. Local scale variables measured included vertical and horizontal habitat structure as well as structural and chemical composition of the soil. Ant richness was not affected by land use but local scale variables such as vertical vegetation structure (+) and leaf litter cover (+), although vegetation complexity at lower levels was negatively associated with ant richness. However, ant richness was largely shaped by regional and temporal processes invoking the importance of dispersal and historical processes. Spider species richness was mostly affected by land use and local conditions highlighting their landscape elements. Spider richness did not vary much between villages and across seasons and seems to be less dependent on context or history. There was a considerable amount of variation in spider richness that was not explained and this could be related to factors which were not measured in this study such as temperature and competition. For both ant and spider assemblages the constrained ordination explained 18 % of variation in these taxa. Three environmental variables (leaf litter cover, active carbon and rock cover) were important in explaining ant assemblage structure, while two (sand and leaf litter cover) were important for spider assemblage structure. This study highlights the importance of disturbance (land use activities) and leaf litter with the associated effects on ant and spider assemblages across the study area.

Keywords: ants, assemblages, biosphere, diversity, land use, spiders, urbanization

Procedia PDF Downloads 249

Authors: Cátia Gonçalves, Teresa Nunes, Inês Pina, Ana Vicente, C. Alves, Felix Charvet, Daniel Neves, A. Matos

Abstract:

The production of charcoal relies on rudimentary technologies using traditional brick kilns. Charcoal is produced under pyrolysis conditions: breaking down the chemical structure of biomass under high temperature in the absence of air. The amount of the pyrolysis products (charcoal, pyroligneous extract, and flue gas) depends on various parameters, including temperature, time, pressure, kiln design, and wood characteristics like the moisture content. This activity is recognized for its inefficiency and high pollution levels, but it is poorly characterized. This activity is widely distributed and is a vital economic activity in certain regions of Portugal, playing a relevant role in the management of woody residues. The location of the units establishes the biomass used for charcoal production. The Portalegre district, in the Alto Alentejo region (Portugal), is a good example, essentially with rural characteristics, with a predominant farming, agricultural, and forestry profile, and with a significant charcoal production activity. In this district, a recent inventory identifies almost 50 charcoal production units, equivalent to more than 450 kilns, of which 80% appear to be in operation. A field campaign was designed with the objective of determining the composition of the emissions released during a charcoal production cycle. A total of 30 samples of particulate matter and 20 gas samples in Tedlar bags were collected. Particulate and gas samplings were performed in parallel, 2 in the morning and 2 in the afternoon, alternating the inlet heads (PM₁₀ and PM₂.₅), in the particulate sampler. The gas and particulate samples were collected in the plume as close as the emission chimney point. The biomass (dry basis) used in the carbonization process was a mixture of cork oak (77 wt.%), holm oak (7 wt.%), stumps (11 wt.%), and charred wood (5 wt.%) from previous carbonization processes. A cylindrical batch kiln (80 m³) with 4.5 m diameter and 5 m of height was used in this study. The composition of the gases was determined by gas chromatography, while the particulate samples (PM₁₀, PM₂.₅) were subjected to different analytical techniques (thermo-optical transmission technique, ion chromatography, HPAE-PAD, and GC-MS after solvent extraction) after prior gravimetric determination, to study their organic and inorganic constituents. The charcoal production cycle presents widely varying operating conditions, which will be reflected in the composition of gases and particles produced and emitted throughout the process. The concentration of PM₁₀ and PM₂.₅ in the plume was calculated, ranging between 0.003 and 0.293 g m⁻³, and 0.004 and 0.292 g m⁻³, respectively. Total carbon, inorganic ions, and sugars account, in average, for PM10 and PM₂.₅, 65 % and 56 %, 2.8 % and 2.3 %, 1.27 %, and 1.21 %, respectively. The organic fraction studied until now includes more than 30 aliphatic compounds and 20 PAHs. The emission factors of particulate matter to produce charcoal in the traditional kiln were 33 g/kg (wooddb) and 27 g/kg (wooddb) for PM₁₀ and PM₂.₅, respectively. With the data obtained in this study, it is possible to fill the lack of information about the environmental impact of the traditional charcoal production in Portugal. Acknowledgment: Authors thanks to FCT – Portuguese Science Foundation, I.P. and to Ministry of Science, Technology and Higher Education of Portugal for financial support within the scope of the project CHARCLEAN (PCIF/GVB/0179/2017) and CESAM (UIDP/50017/2020 + UIDB/50017/2020).

Keywords: brick kilns, charcoal, emission factors, PAHs, total carbon

Procedia PDF Downloads 110