Search results for: data pipeline

Authors: Jarek Krajewski, David Daxberger, Luzi Beyer

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Finding objective and non-intrusive measurements of emotional and psychopathological states (e.g., post-traumatic stress disorder, PTSD) is an important challenge. Thus, the proposed approach here uses Photoplethysmographic imaging (PPGI) applying facial RGB Cam videos to estimate heart rate levels. A pipeline for the signal processing of the raw image has been proposed containing different preprocessing approaches, e.g., Independent Component Analysis, Non-negative Matrix factorization, and various other artefact correction approaches. Under resting and constant light conditions, we reached a sensitivity of 84% for pulse peak detection. The results indicate that PPGI can be a suitable solution for providing heart rate data derived from these indirectly post-traumatic stress states.

Keywords: heart rate, PTSD, PPGI, stress, preprocessing

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Authors: A. Mohamed, A. El-Hamalawi, M. Frost, A. Connell

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Often design standards do not provide guidance or formulae for the calculation of stresses on buried pipelines caused by external loads. Frequently engineers rely on other methods and published sources of information to calculate such imposed stresses and a variety of methods can be used. This paper reviews three current approaches to soil pipeline interaction modelling to predict stresses on buried pipelines subjected to soil overburden and traffic loading. The traditional approach to use empirical stress formulas to calculate circumferential bending stresses on pipelines. The alternative approaches considered are the use of a finite element package to compute an estimate of circumferential bending stress and a proprietary stress analysis system (SURFLOAD) to estimate the circumferential bending stress. The results from analysis using the methods are presented and compared to experimental results in terms of predicted and measured circumferential stresses. This study shows that the approach used to assess externally generated stress is important and can lead to an over-conservative analysis. Using FE analysis either through SURFLOAD or a general FE package to predict circumferential stress is the most accurate way to undertake stress analysis due to traffic and soil loads. Although conservative, classical empirical methods will continue to be applied to the analysis of buried pipelines, an opportunity exists, therefore, in many circumstances, to use applied numerical techniques, made possible by advances in finite element analysis.

Keywords: buried pipelines, circumferential bending stress, finite element analysis, soil overburden, soil pipeline interaction analysis (SPIA), traffic loadings

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

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Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Karen C. Olufokunbi, Odetunji A. Odejobi

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The discourse of this paper is the examination of the generation, accumulation and growth of e-waste in a developing country. Images and other data about computer e-waste were collected using a digital camera, 290 copies of questionnaire and three structured interviews using Obafemi Awolowo University (OAU), Ile-Ife, Nigeria environment as a case study. The numerical data were analysed using R data analysis and process tool. Automata-based techniques and Petri net modeling tool were used to design and simulate a computational model for the recovery of saleable materials from e-waste. The R analysis showed that at a 95 percent confidence level, the computer equipment that will be disposed by 2020 will be 417 units. Compared to the 800 units in circulation in 2014, 50 percent of personal computer components will become e-waste. This indicates that personal computer components were in high demand due to their low costs and will be disposed more rapidly when replaced by new computer equipment Also, 57 percent of the respondents discarded their computer e-waste by throwing it into the garbage bin or by dumping it. The simulated model using Coloured Petri net modelling tool for the process showed that the e-waste dynamics is a forward sequential process in the form of a pipeline meaning that an e-waste recovery of saleable materials process occurs in identifiable discrete stages indicating that e-waste will continue to accumulate and grow in volume with time.

Keywords: Coloured Petri net, computational modelling, electronic waste, electronic waste process dynamics

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Authors: Lesley Northrop, Justin DeGrazia, Jessica Greenwood

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ASPIRA Labs now offers an en-suit and ready-to-implement technology transfer solution to enable labs and hospitals that lack the resources to build it themselves to offer in-house genetic testing. This unique platform employs a patented Molecular Inversion Probe (MIP) technology that combines the specificity of a hybrid capture protocol with the ease of an amplicon-based protocol and utilizes an advanced bioinformatics analysis pipeline based on machine learning. To demonstrate its efficacy, two independent genetic tests were validated on this technology transfer platform: expanded carrier screening (ECS) and hereditary cancer testing (HC). The analytical performance of ECS and HC was validated separately in a blinded manner for calling three different types of variants: SNVs, short indels (typically, <50 bp), and large indels/CNVs defined as multi-exonic del/dup events. The reference set was constructed using samples from Coriell Institute, an external clinical genetic testing laboratory, Maine Molecular Quality Controls Inc. (MMQCI), SeraCare and GIAB Consortium. Overall, the analytical performance showed a sensitivity and specificity of >99.4% for both ECS and HC in detecting SNVs. For indels, both tests reported specificity of 100%, and ECS demonstrated a sensitivity of 100%, whereas HC exhibited a sensitivity of 96.5%. The bioinformatics pipeline also correctly called all reference CNV events resulting in a sensitivity of 100% for both tests. No additional calls were made in the HC panel, leading to a perfect performance (specificity and F-measure of 100%). In the carrier panel, however, three additional positive calls were made outside the reference set. Two of these calls were confirmed using an orthogonal method and were re-classified as true positives leaving only one false positive. The pipeline also correctly identified all challenging carrier statuses, such as positive cases for spinal muscular atrophy and alpha-thalassemia, resulting in 100% sensitivity. After confirmation of additional positive calls via long-range PCR and MLPA, specificity for such cases was estimated at 99%. These performance metrics demonstrate that this tech-transfer solution can be confidently internalized by clinical labs and hospitals to offer mainstream ECS and HC as part of their test catalog, substantially increasing access to quality germline genetic testing for labs of all sizes and resources levels.

Keywords: clinical genetics, genetic testing, molecular genetics, technology transfer

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Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

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In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: data security, flow cytometry, leukaemia, telematics platform, telemedicine

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Authors: Daehyun Baek, Seungmin Lee, Minju Kim Jangik Park, Hyeong-Soon Moon

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SPM (Single Point Mooring) is one of the mooring buoy facilities installed on a coast near oil and gas terminal which is not able to berth FPSO or large oil tankers under the condition of high draft due to geometrical limitation. Loading and unloading of crude oil and gas through a subsea pipeline can be carried out between the mooring buoy, ships and onshore facilities. SPM is an offshore-standalone system which has to withstand the harsh marine environment with harsh conditions such as high wind, current and so on. Therefore, SPM is required to have high stability, reliability and durability. Also, SPM is comprised to be integrated systems which consist of power management, high pressure valve control, sophisticated hardware/software and a long distance communication system. In order to secure required functions of SPM system, a simulation model for the integrated system of SPM using MATLAB Simulink and State flow tool has been developed. The developed model consists of configuration of hydraulic system for opening and closing of PLEM (Pipeline End Manifold) valves and control system logic. To verify functions of the model, an integrated simulation model for overall systems of SPM was also developed by considering handshaking variables between individual systems. In addition to the dynamic model, a self-diagnostic function to determine failure of the system was configured, which enables the SPM system itself to alert users about the failure once a failure signal comes to arise. Controlling and monitoring the SPM system is able to be done by a HMI system which is capable of managing the SPM system remotely, which was carried out by building a communication environment between the SPM system and the HMI system.

Keywords: HMI system, mooring buoy, simulink simulation model, single point mooring, stateflow

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Authors: Mohammed Lamine Benaouda

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This paper seeks to shed light on the African continent role with the crisis of natural gas supplies to European countries, which resulted from the repercussions of the Russian-Ukrainian war, by examining the case of re-launching the Trans-Saharan Gas Pipeline project Nigeria-Algeria, and clarifying the strategic importance This project is mutually beneficial in the long run. The paper relied on the analytical and statistical method in order to find out the the impact that the project represents on the huge needs of the European gas market on the one hand, and monitoring the various economic gains for Algeria and Nigeria on the other hand, in addition, the comparative approach to assess the possible effects of the success and feasibility of the project economy for all its beneficiaries. The paper founds that the complexity has multiplied in the global energy market in general and the European one in particular, following what the world witnessed from the repercussions of the Russian-Ukrainian war, as well as the extreme importance of the poles of African countries in the arena of the international struggle over resources, which allows them a margin From maneuvering and regional and global influence in various fields. With regard to the research outcoms and the future scope, the researcher believes that the African continent, in light of international competition and conflict, as well as what the world is witnessing in terms of restoring balances of power in the current international system, will play very important roles, especially with its enormous natural and human capabilities, which enable it to Weighting future conflicts over energy and spheres of influence.

Keywords: algeria, nigeria, west africa, ECOWAS, gas supplies, russia, ukrain

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Authors: Hajer Najjar, Riad Bourguiba, Jaouhar Mouine

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Reduced instruction set computer (RISC) processors are widely used because of their multiple advantages. In fact, they are based on a simple instruction set so that they increase the speed of the processor and reduce its energy consumption. In this paper, we will present a basic RISC architecture processor that will be developed later to converge to a new architecture with runtime reconfiguration.

Keywords: processor, RISC, DLX, pipeline, runtime reconfiguration

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Shuaibu Umar Abdul

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This paper examines Nigeria’s foreign policy in the age of global terrorism. It worth saying that the threat of ‘terrorism’ is not peculiar to Western and Middle Eastern countries alone, its tentacles are now spreading all over, Africa inclusive. The issue of domestic terrorism in Nigeria has become pervasive since the return of democratic rule in 1999. This development has never been a witness in any form throughout the year of statehood in Nigeria, the issues of banditry, armed robbery, ritual killing, and criminal activities like kidnapping and pipeline vandalization, the breakdown of law and order, poorly managed infrastructural facilities and corruption remain synonymous to Nigeria. These acts of terrorism no doubt have constituted a challenge that necessitates the paradigm shift in Nigeria’s foreign policy. The study employed the conceptual framework of analysis to lead interrogation; secondary sources were used to generate data while descriptive and content analysis were considered for data presentation and interpretation. In view of the interrogation and discussion on the subject matter, the paper revealed that Nigerian government underrated and underestimated the strength of terrorism within and outside her policy hence, it becomes difficult to address. As a response to the findings and conclusion of the study, the paper recommends among others that Nigeria’s foreign policy has to be rethought, reshaped and remodeled in cognizance to the rising global terrorism for peace, growth and development in the country.

Keywords: foreign policy, globe, Nigeria, rethinking, terrorism

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Shiji Hu, Lei Li, Wanting Zhou, DaoHong Yang

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The data encryption, is the foundation of today’s communication. On this basis, how to improve the speed of data encryption and decryption is always a problem that scholars work for. In this paper, we proposed an elliptic curve crypto processor architecture based on SM2 prime field. In terms of hardware implementation, we optimized the algorithms in different stages of the structure. In finite field modulo operation, we proposed an optimized improvement of Karatsuba-Ofman multiplication algorithm, and shorten the critical path through pipeline structure in the algorithm implementation. Based on SM2 recommended prime field, a fast modular reduction algorithm is used to reduce 512-bit wide data obtained from the multiplication unit. The radix-4 extended Euclidean algorithm was used to realize the conversion between affine coordinate system and Jacobi projective coordinate system. In the parallel scheduling of point operations on elliptic curves, we proposed a three-level parallel structure of point addition and point double based on the Jacobian projective coordinate system. Combined with the scalar multiplication algorithm, we added mutual pre-operation to the point addition and double point operation to improve the efficiency of the scalar point multiplication. The proposed ECC hardware architecture was verified and implemented on Xilinx Virtex-7 and ZYNQ-7 platforms, and each 256-bit scalar multiplication operation took 0.275ms. The performance for handling scalar multiplication is 32 times that of CPU(dual-core ARM Cortex-A9).

Keywords: Elliptic curve cryptosystems, SM2, modular multiplication, point multiplication.

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Authors: Mohsen Hababalahi, Morteza Bastami

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Buried pipeline damage correlations are critical part of loss estimation procedures applied to lifelines for future earthquakes. The vulnerability of buried pipelines against earthquake and liquefaction has been observed during some of previous earthquakes and there are a lot of comprehensive reports about this event. One of the main reasons for impairment of buried pipelines during earthquake is liquefaction. Necessary conditions for this phenomenon are loose sandy soil, saturation of soil layer and earthquake intensity. Because of this fact that pipelines structure are very different from other structures (being long and having light mass) by paying attention to the results of previous earthquakes and compare them with other structures, it is obvious that the danger of liquefaction for buried pipelines is not high risked, unless effective parameters like earthquake intensity and non-dense soil and other factors be high. Recent liquefaction researches for buried pipeline include experimental and theoretical ones as well as damage investigations during actual earthquakes. The damage investigations have revealed that a damage ratio of pipelines (Number/km ) has much larger values in liquefied grounds compared with one in shaking grounds without liquefaction according to damage statistics during past severe earthquakes, and that damages of joints and pipelines connected with manholes were remarkable. The purpose of this research is numerical study of buried pipelines under the effect of liquefaction by case study of the 2013 Dashti (Iran) earthquake. Water supply and electrical distribution systems of this township interrupted during earthquake and water transmission pipelines were damaged severely due to occurrence of liquefaction. The model consists of a polyethylene pipeline with 100 meters length and 0.8 meter diameter which is covered by light sandy soil and the depth of burial is 2.5 meters from surface. Since finite element method is used relatively successfully in order to solve geotechnical problems, we used this method for numerical analysis. For evaluating this case, some information like geotechnical information, classification of earthquakes levels, determining the effective parameters in probability of liquefaction, three dimensional numerical finite element modeling of interaction between soil and pipelines are necessary. The results of this study on buried pipelines indicate that the effect of liquefaction is function of pipe diameter, type of soil, and peak ground acceleration. There is a clear increase in percentage of damage with increasing the liquefaction severity. The results indicate that although in this form of the analysis, the damage is always associated to a certain pipe material, but the nominally defined “failures” include by failures of particular components (joints, connections, fire hydrant details, crossovers, laterals) rather than material failures. At the end, there are some retrofit suggestions in order to decrease the risk of liquefaction on buried pipelines.

Keywords: liquefaction, buried pipelines, lifelines, earthquake, finite element method

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Authors: Andrey V. Timofeev, Dmitry Egorov

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This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: C-OTDR monitoring system, bimodal processing, LPboost, SVM

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Authors: A. Abdul-Ameer

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The equations governing the distance, pressure- volume flow relationships for the pipeline transportation of gaseous mixtures, are considered. A derivation based on differential calculus, for an element of this system model, is addressed. Solutions, yielding the input- output response following pressure changes, are reviewed. The technical problems associated with these analytical results are identified. Procedures resolving these difficulties providing thereby an attractive, simple, analysis route are outlined. Computed responses, validating thereby calculated predictions, are presented.

Keywords: pressure, distance, flow, dissipation, models

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Authors: S. Fahiminiya, J. Nadaf, F. Rauch, L. Jerome-Majewska, J. Majewski

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Background: Sequencing of protein coding regions of human genome (Whole Exome Sequencing; WES), has demonstrated a great success in the identification of causal mutations for several rare genetic disorders in human. Generally, most of WES studies have focused on rare variants in coding exons and splicing-sites where missense substitutions lead to the alternation of protein product. Although focusing on this category of variants has revealed the mystery behind many inherited genetic diseases in recent years, a subset of them remained still inconclusive. Here, we present the result of our WES studies where analyzing only rare variants in coding regions was not conclusive but further investigation revealed the involvement of non-coding variants and copy number variations (CNV) in etiology of the diseases. Methods: Whole exome sequencing was performed using our standard protocols at Genome Quebec Innovation Center, Montreal, Canada. All bioinformatics analyses were done using in-house WES pipeline. Results: To date, we successfully identified several disease causing mutations within gene coding regions (e.g. SCARF2: Van den Ende-Gupta syndrome and SNAP29: 22q11.2 deletion syndrome) by using WES. In addition, we showed that variants in non-coding regions and CNV have also important value and should not be ignored and/or filtered out along the way of bioinformatics analysis on WES data. For instance, in patients with osteogenesis imperfecta type V and in patients with glucocorticoid deficiency, we identified variants in 5'UTR, resulting in the production of longer or truncating non-functional proteins. Furthermore, CNVs were identified as the main cause of the diseases in patients with metaphyseal dysplasia with maxillary hypoplasia and brachydactyly and in patients with osteogenesis imperfecta type VII. Conclusions: Our study highlights the importance of considering non-coding variants and CNVs during interpretation of WES data, as they can be the only cause of disease under investigation.

Keywords: whole exome sequencing data, non-coding variants, copy number variations, rare diseases

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Authors: Deepak Kumar, Debasish Deb, Reena Mamgain

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Radar signal processing requires high number crunching capability. Most often this is achieved using multiprocessor platform. Though multiprocessor platform provides the capability of meeting the real time computational challenges, the architecture of the same along with mapping of the algorithm on the architecture plays a vital role in efficiently using the platform. Towards this, along with standard performance metrics, few additional metrics are defined which helps in evaluating the multiprocessor platform along with the algorithm mapping. A generic multiprocessor architecture can not suit all the processing requirements. Depending on the system requirement and type of algorithms used, the most suitable architecture for the given problem is decided. In the paper, we study different architectures and quantify the different performance metrics which enables comparison of different architectures for their merit. We also carried out case study of different architectures and their efficiency depending on parallelism exploited on algorithm or data or both.

Keywords: radar signal processing, multiprocessor architecture, efficiency, load imbalance, buffer requirement, pipeline, parallel, hybrid, cluster of processors (COPs)

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Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

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Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

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Authors: Juan Alfredo Guevara Carrio, Swamy Toolahalli Thipperudra, Riddhi Naik Dharmeshbhai, Sergio Graniero Echeverrigaray, Jose Vitorio Emiliano, Antonio Helio Castro

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In order to advance the hydrogen economy, several industrial sectors can potentially benefit from the trillions of stimulus spending for post-coronavirus. Blending hydrogen into natural gas pipeline networks has been proposed as a means of delivering it during the early market development phase, using separation and purification technologies downstream to extract the pure H₂ close to the point of end-use. This first step has been mentioned around the world as an opportunity to use existing infrastructures for immediate decarbonisation pathways. Among current technologies used to extract hydrogen from mixtures in pipelines or liquid carriers, membrane separation can achieve the highest selectivity. The most efficient approach for the separation of H₂ from other substances by membranes is offered from the research of 2D layered materials due to their exceptional physical and chemical properties. Graphene-based membranes, with their distribution of pore sizes in nanometers and angstrom range, have shown fundamental and economic advantages over other materials. Their combination with the structure of ceramic and geopolymeric materials enabled the synthesis of nanocomposites and the fabrication of membranes with long-term stability and robustness in a relevant range of physical and chemical conditions. Versatile separation modules have been developed for hydrogen separation, which adaptability allows their integration in industrial prototypes for applications in heavy transport, steel, and cement production, as well as small installations at end-user stations of pipeline networks. The developed membranes and prototypes are a practical contribution to the technological challenge of supply pure H₂ for the mentioned industries as well as hydrogen energy-based fuel cells.

Keywords: graphene nano-composite membranes, hydrogen separation and purification, separation modules, indsutrial prototype

Procedia PDF Downloads 127

Authors: Mohand Kessal, Rachid Boucetta, Mourad Tikobaini, Mohammed Zamoum

Abstract:

Leakage problem of two-component fluids flow is modeled for a transient one-dimensional homogeneous bubbly flow and developed by taking into account the effect of a leak located at the middle point of the pipeline. The corresponding three conservation equations are numerically resolved by an improved characteristic method. The obtained results are explained and commented in terms of physical impact on the flow parameters.

Keywords: fluid transients, pipelines leaks, method of characteristics, leakage problem

Procedia PDF Downloads 445

Authors: Yi-Lin Chen, Sheng-Jou Hung, Tsunglin Liu

Abstract:

Adaptive immune system recognizes a wide range of antigens via expressing a large number of structurally distinct T cell and B cell receptor genes. The distinct receptor genes arise from complex rearrangements called V(D)J recombination, and constitute the immune repertoire. A common method of profiling immune repertoire is via amplifying recombined receptor genes using multiple primers and high-throughput sequencing. This multiplex-PCR approach is efficient; however, the resulting repertoire can be distorted because of primer bias. To eliminate primer bias, 5’ RACE is an alternative amplification approach. However, the application of RACE approach is limited by its low efficiency (i.e., the majority of data are non-regular receptor sequences, e.g., containing intronic segments) and lack of the convenient tool for analysis. We propose a computational tool that can correctly identify non-regular receptor sequences in RACE data via aligning receptor sequences against the whole gene instead of only the exon regions as done in all other tools. Using our tool, the remaining regular data allow for an accurate profiling of immune repertoire. In addition, a RACE approach is improved to yield a higher fraction of regular T-cell receptor sequences. Finally, we quantify the degree of primer bias of a multiplex-PCR approach via comparing it to the RACE approach. The results reveal significant differences in frequency of VJ combination by the two approaches. Together, we provide a new experimental and computation pipeline for an unbiased profiling of immune repertoire. As immune repertoire profiling has many applications, e.g., tracing bacterial and viral infection, detection of T cell lymphoma and minimal residual disease, monitoring cancer immunotherapy, etc., our work should benefit scientists who are interested in the applications.

Keywords: immune repertoire, T-cell receptor, 5' RACE, high-throughput sequencing, sequence alignment

Procedia PDF Downloads 159

Authors: Moh’d Anwer Al-Shboul

Abstract:

The year 2011 was a challenging year for Jordanian economy, which felt a variety of effects from the Arab Spring which took place in neighboring countries. Since February, 5th 2012, the Arab Gas Supply Pipeline, which carries natural gas from Egypt through the Sinai Peninsula and to Jordan and Israel, has been attacked more than 39 times. Jordan imported about 80 percent of its necessity of natural gas (about 250 million cubic feet of natural gas per day) from Egypt to generate particularly electricity, with the reminder of being produced locally. Jordan has utilized multiple alternatives to address the interruption of available natural gas supply from Egypt. The Jordanian distributed power plants now rely on the use of heavy fuel oil and diesel for electricity generation, in this case, it costs Jordan about four times than natural gas. The substitution of Egyptian natural gas supplies by fuel oil and diesel, coupled with the 32 percent rise in global fuel prices, has increased Jordan’s energy import bill by over 50 percent in 2011, reaching more than 16 percent of the 2011 GDP. The increase in the cost of electricity generation pushed the Jordanian economy to borrow from multiple internal and external resource channels, thus increasing the public debt. The Jordanian government’s short-term solution to the reduced natural gas supply from Egypt was alternatively purchasing the necessary quantities from some Gulf countries such as Qatar and/or Saudi Arabia, which can be imported with two possible methods. The first method is to rent a ship equipped with a liquefied natural gas (LNG) terminal, which is currently operating. The second method requires equipping the Aqaba port with an LNG terminal, which also currently is operating. In the long-term, a viable solution to depending on importing expensive and often unreliable natural gas supplies from surrounding countries is to depend more heavily on renewable supply energy, including solar, wind, and water energy.

Keywords: energy supply resources, Arab spring, liquefied natural gas, pipeline, Jordan

Procedia PDF Downloads 110

Authors: Dohwan Kim, Dongchoon Ryou, Pyungjong Yoo

Abstract:

In public water facilities, drinking water distribution systems have played an important role along with water purification systems. The water distribution network is one of the most expensive components of water supply infrastructure systems. To improve the reliability for the drinking rate of tap water, advanced water treatment processes such as granular activated carbon and membrane filtration were used by water service providers in Korea. But, distrust of the people for tap water are still. Therefore, accurate diagnosis and condition assessment for water pipelines are required to supply the clean water. The internal corrosion of water pipe has increased as time passed. Also, the cross-sectional areas in pipe are reduced by the rust, deposits and tubercles. It is the water supply ability decreases as the increase of hydraulic pump capacity is required to supply an amount of water, such as the initial condition. If not, the poor area of water supply will be occurred by the decrease of water pressure. In order to solve these problems, water managers and engineers should be always checked for the current status of the water pipe, such as water leakage and damage of pipe. If problems occur, it should be able to respond rapidly and make an accurate estimate. In Korea, replacement and rehabilitation of aging drinking water pipes are carried out based on the circumstances of simply buried years. So, water distribution system management may not consider the entire water pipeline network. The long-term design and upgrading of a water distribution network should address economic, social, environmental, health, hydraulic, and other technical issues. This is a multi-objective problem with a high level of complexity. In this study, the thickness of the old water pipes, corrosion levels of the inner and outer surface for water pipes, basic data research (i.e. pipe types, buried years, accident record, embedded environment, etc.), specific resistance of soil, ultimate tensile strength and elongation of metal pipes, samples characteristics, and chemical composition analysis were performed about aging drinking water pipes. Samples of water pipes used in this study were cement mortar lining ductile cast iron pipe (CML-DCIP, diameter 100mm) and epoxy lining steel pipe (diameter 65 and 50mm). Buried years of CML-DCIP and epoxy lining steel pipe were respectively 32 and 23 years. The area of embedded environment was marine reclamation zone since 1940’s. The result of this study was that CML-DCIP needed replacement and epoxy lining steel pipe was still useful.

Keywords: drinking water distribution system, water supply, replacement, rehabilitation, water pipe

Procedia PDF Downloads 232

Authors: Faisal Kalota

Abstract:

Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

Procedia PDF Downloads 382

Authors: B. Medjadji, L. Aminallah, B. Serier, M. Benlebna

Abstract:

In this study, the finite element method in 3-D is used to calculate the integral J in the semi-elliptical crack in a pipe subjected to internal pressure. The stress-strain curve of the pipe has been determined experimentally. The J-integral was calculated in two fronts crack (Ф = 0 and Ф = π/2). The effect of the configuration of the crack on the J integral is analysed. The results show that an external longitudinal crack in a pipe is the most dangerous. It also shows that the increase in the applied pressure causes a remarkable increase of the integral J. The effect of the depth of the crack becomes important when the ratio between the depth of the crack and the thickness of the pipe (a / t) tends to 1.

Keywords: J integral, pipeline, crack, MEF

Procedia PDF Downloads 378

Authors: Sandeep Sharma, Sarabjit Singh

Abstract:

As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

Procedia PDF Downloads 511