Search results for: object detection and tracking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5214

Search results for: object detection and tracking

1794 Trip Reduction in Turbo Machinery

Authors: Pranay Mathur, Carlo Michelassi, Simi Karatha, Gilda Pedoto

Abstract:

Industrial plant uptime is top most importance for reliable, profitable & sustainable operation. Trip and failed start has major impact on plant reliability and all plant operators focussed on efforts required to minimise the trips & failed starts. The performance of these CTQs are measured with 2 metrics, MTBT(Mean time between trips) and SR (Starting reliability). These metrics helps to identify top failure modes and identify units need more effort to improve plant reliability. Baker Hughes Trip reduction program structured to reduce these unwanted trip 1. Real time machine operational parameters remotely available and capturing the signature of malfunction including related boundary condition. 2. Real time alerting system based on analytics available remotely. 3. Remote access to trip logs and alarms from control system to identify the cause of events. 4. Continuous support to field engineers by remotely connecting with subject matter expert. 5. Live tracking of key CTQs 6. Benchmark against fleet 7. Break down to the cause of failure to component level 8. Investigate top contributor, identify design and operational root cause 9. Implement corrective and preventive action 10. Assessing effectiveness of implemented solution using reliability growth models. 11. Develop analytics for predictive maintenance With this approach , Baker Hughes team is able to support customer in achieving their Reliability Key performance Indicators for monitored units, huge cost savings for plant operators. This Presentation explains these approach while providing successful case studies, in particular where 12nos. of LNG and Pipeline operators with about 140 gas compressing line-ups has adopted these techniques and significantly reduce the number of trips and improved MTBT

Keywords: reliability, availability, sustainability, digital infrastructure, weibull, effectiveness, automation, trips, fail start

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1793 A Review of HVDC Modular Multilevel Converters Subjected to DC and AC Faults

Authors: Jude Inwumoh, Adam P. R. Taylor, Kosala Gunawardane

Abstract:

Modular multilevel converters (MMC) exhibit a highly scalable and modular characteristic with good voltage/power expansion, fault tolerance capability, low output harmonic content, good redundancy, and a flexible front-end configuration. Fault detection, location, and isolation, as well as maintaining fault ride-through (FRT), are major challenges to MMC reliability and power supply sustainability. Different papers have been reviewed to seek the best MMC configuration with fault capability. DC faults are the most common fault, while the probability that AC fault occurs in a modular multilevel converter (MCC) is low; though, AC faults consequence are severe. This paper reviews several MMC topologies and modulation techniques in tackling faults. These fault control strategies are compared based on cost, complexity, controllability, and power loss. A meshed network of half-bridge (HB) MMC topology was optimal in rendering fault ride through than any other MMC topologies but only when combined with DC circuit breakers (CBS), AC CBS, and fault current limiters (FCL).

Keywords: MMC-HVDC, DC faults, fault current limiters, control scheme

Procedia PDF Downloads 140
1792 Single Cell and Spatial Transcriptomics: A Beginners Viewpoint from the Conceptual Pipeline

Authors: Leo Nnamdi Ozurumba-Dwight

Abstract:

Messenger ribooxynucleic acid (mRNA) molecules are compositional, protein-based. These proteins, encoding mRNA molecules (which collectively connote the transcriptome), when analyzed by RNA sequencing (RNAseq), unveils the nature of gene expression in the RNA. The obtained gene expression provides clues of cellular traits and their dynamics in presentations. These can be studied in relation to function and responses. RNAseq is a practical concept in Genomics as it enables detection and quantitative analysis of mRNA molecules. Single cell and spatial transcriptomics both present varying avenues for expositions in genomic characteristics of single cells and pooled cells in disease conditions such as cancer, auto-immune diseases, hematopoietic based diseases, among others, from investigated biological tissue samples. Single cell transcriptomics helps conduct a direct assessment of each building unit of tissues (the cell) during diagnosis and molecular gene expressional studies. A typical technique to achieve this is through the use of a single-cell RNA sequencer (scRNAseq), which helps in conducting high throughput genomic expressional studies. However, this technique generates expressional gene data for several cells which lack presentations on the cells’ positional coordinates within the tissue. As science is developmental, the use of complimentary pre-established tissue reference maps using molecular and bioinformatics techniques has innovatively sprung-forth and is now used to resolve this set back to produce both levels of data in one shot of scRNAseq analysis. This is an emerging conceptual approach in methodology for integrative and progressively dependable transcriptomics analysis. This can support in-situ fashioned analysis for better understanding of tissue functional organization, unveil new biomarkers for early-stage detection of diseases, biomarkers for therapeutic targets in drug development, and exposit nature of cell-to-cell interactions. Also, these are vital genomic signatures and characterizations of clinical applications. Over the past decades, RNAseq has generated a wide array of information that is igniting bespoke breakthroughs and innovations in Biomedicine. On the other side, spatial transcriptomics is tissue level based and utilized to study biological specimens having heterogeneous features. It exposits the gross identity of investigated mammalian tissues, which can then be used to study cell differentiation, track cell line trajectory patterns and behavior, and regulatory homeostasis in disease states. Also, it requires referenced positional analysis to make up of genomic signatures that will be sassed from the single cells in the tissue sample. Given these two presented approaches to RNA transcriptomics study in varying quantities of cell lines, with avenues for appropriate resolutions, both approaches have made the study of gene expression from mRNA molecules interesting, progressive, developmental, and helping to tackle health challenges head-on.

Keywords: transcriptomics, RNA sequencing, single cell, spatial, gene expression.

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1791 Trinary Affinity—Mathematic Verification and Application (1): Construction of Formulas for the Composite and Prime Numbers

Authors: Liang Ming Zhong, Yu Zhong, Wen Zhong, Fei Fei Yin

Abstract:

Trinary affinity is a description of existence: every object exists as it is known and spoken of, in a system of 2 differences (denoted dif1, dif₂) and 1 similarity (Sim), equivalently expressed as dif₁ / Sim / dif₂ and kn / 0 / tkn (kn = the known, tkn = the 'to be known', 0 = the zero point of knowing). They are mathematically verified and illustrated in this paper by the arrangement of all integers onto 3 columns, where each number exists as a difference in relation to another number as another difference, and the 2 difs as arbitrated by a third number as the Sim, resulting in a trinary affinity or trinity of 3 numbers, of which one is the known, the other the 'to be known', and the third the zero (0) from which both the kn and tkn are measured and specified. Consequently, any number is horizontally specified either as 3n, or as '3n – 1' or '3n + 1', and vertically as 'Cn + c', so that any number seems to occur at the intersection of its X and Y axes and represented by its X and Y coordinates, as any point on Earth’s surface by its latitude and longitude. Technically, i) primes are viewed and treated as progenitors, and composites as descending from them, forming families of composites, each capable of being measured and specified from its own zero called in this paper the realistic zero (denoted 0r, as contrasted to the mathematic zero, 0m), which corresponds to the constant c, and the nature of which separates the composite and prime numbers, and ii) any number is considered as having a magnitude as well as a position, so that a number is verified as a prime first by referring to its descriptive formula and then by making sure that no composite number can possibly occur on its position, by dividing it with factors provided by the composite number formulas. The paper consists of 3 parts: 1) a brief explanation of the trinary affinity of things, 2) the 8 formulas that represent ALL the primes, and 3) families of composite numbers, each represented by a formula. A composite number family is described as 3n + f₁‧f₂. Since there are an infinitely large number of composite number families, to verify the primality of a great probable prime, we have to have it divided with several or many a f₁ from a range of composite number formulas, a procedure that is as laborious as it is the surest way to verifying a great number’s primality. (So, it is possible to substitute planned division for trial division.)

Keywords: trinary affinity, difference, similarity, realistic zero

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1790 Machine Learning in Agriculture: A Brief Review

Authors: Aishi Kundu, Elhan Raza

Abstract:

"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

Procedia PDF Downloads 105
1789 3D Modeling of Flow and Sediment Transport in Tanks with the Influence of Cavity

Authors: A. Terfous, Y. Liu, A. Ghenaim, P. A. Garambois

Abstract:

With increasing urbanization worldwide, it is crucial to sustainably manage sediment flows in urban networks and especially in stormwater detention basins. One key aspect is to propose optimized designs for detention tanks in order to best reduce flood peak flows and in the meantime settle particles. It is, therefore, necessary to understand complex flows patterns and sediment deposition conditions in stormwater detention basins. The aim of this paper is to study flow structure and particle deposition pattern for a given tank geometry in view to control and maximize sediment deposition. Both numerical simulation and experimental works were done to investigate the flow and sediment distribution in a storm tank with a cavity. As it can be indicated, the settle distribution of the particle in a rectangular tank is mainly determined by the flow patterns and the bed shear stress. The flow patterns in a rectangular tank differ with different geometry, entrance flow rate and the water depth. With the changing of flow patterns, the bed shear stress will change respectively, which also play an influence on the particle settling. The accumulation of the particle in the bed changes the conditions at the bottom, which is ignored in the investigations, however it worth much more attention, the influence of the accumulation of the particle on the sedimentation should be important. The approach presented here is based on the resolution of the Reynolds averaged Navier-Stokes equations to account for turbulent effects and also a passive particle transport model. An analysis of particle deposition conditions is presented in this paper in terms of flow velocities and turbulence patterns. Then sediment deposition zones are presented thanks to the modeling with particle tracking method. It is shown that two recirculation zones seem to significantly influence sediment deposition. Due to the possible overestimation of particle trap efficiency with standard wall functions and stick conditions, further investigations seem required for basal boundary conditions based on turbulent kinetic energy and shear stress. These observations are confirmed by experimental investigations processed in the laboratory.

Keywords: storm sewers, sediment deposition, numerical simulation, experimental investigation

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1788 Detecting Cyberbullying, Spam and Bot Behavior and Fake News in Social Media Accounts Using Machine Learning

Authors: M. D. D. Chathurangi, M. G. K. Nayanathara, K. M. H. M. M. Gunapala, G. M. R. G. Dayananda, Kavinga Yapa Abeywardena, Deemantha Siriwardana

Abstract:

Due to the growing popularity of social media platforms at present, there are various concerns, mostly cyberbullying, spam, bot accounts, and the spread of incorrect information. To develop a risk score calculation system as a thorough method for deciphering and exposing unethical social media profiles, this research explores the most suitable algorithms to our best knowledge in detecting the mentioned concerns. Various multiple models, such as Naïve Bayes, CNN, KNN, Stochastic Gradient Descent, Gradient Boosting Classifier, etc., were examined, and the best results were taken into the development of the risk score system. For cyberbullying, the Logistic Regression algorithm achieved an accuracy of 84.9%, while the spam-detecting MLP model gained 98.02% accuracy. The bot accounts identifying the Random Forest algorithm obtained 91.06% accuracy, and 84% accuracy was acquired for fake news detection using SVM.

Keywords: cyberbullying, spam behavior, bot accounts, fake news, machine learning

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1787 Tax Evasion with Mobility between the Regular and Irregular Sectors

Authors: Xavier Ruiz Del Portal

Abstract:

This paper incorporates mobility between the legal and black economies into a model of tax evasion with endogenous labor supply in which underreporting is possible in one sector but impossible in the other. We have found that the results of the effects along the extensive margin (number of evaders) become more robust and conclusive than those along the intensive margin (hours of illegal work) usually considered by the literature. In particular, it is shown that the following policies reduce the number of evaders: (a) larger and more progressive evasion penalties; (b) higher detection probabilities; (c) an increase in the legal sector wage rate; (d) a decrease in the moonlighting wage rate; (e) higher costs for creating opportunities to evade; (f) lower opportunities to evade, and (g) greater psychological costs of tax evasion. When tax concealment and illegal work also are taken into account, the effects do not vary significantly under the assumptions in Cowell (1985), except for the fact that policies (a) and (b) only hold as regards low- and middle-income groups and policies (e) and (f) as regards high-income groups.

Keywords: income taxation, tax evasion, extensive margin responses, the penalty system

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1786 Grating Scale Thermal Expansion Error Compensation for Large Machine Tools Based on Multiple Temperature Detection

Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

Abstract:

To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

Procedia PDF Downloads 366
1785 Value of Unilateral Spinal Anaesthesia For Hip Fracture Surgery In The Elderly (75 Cases)

Authors: Fedili Benamar, Beloulou Mohamed Lamine, Ouahes Hassane, Ghattas Samir

Abstract:

Background and aims: While in Western countries, unilateral spinal anesthesia has been widely practiced for a long time, it remains little known in the local anesthesia community, and has not been the object of many studies. However, it is a simple, practical and effective technique. Our objective was to evaluate this practice in emergency anesthesia management in frail patients and to compare it with conventional spinal anesthesia. Methods: This is a prospective, observational, comparative study between hypobaric unilateral and conventional spinal anaesthesia for hip fracture surgery carried out in the operating room of the university military hospital of Staoueli. The work was spread over of 12-month period from 2019 to 2020. The parameters analyzed were hemodynamic variations, vasopressor use, block efficiency, postoperative adverse events, and postoperative morphine consumption. Results: -75 cases (mean age 72±14 years) -Group1= 41 patients (54.6%) divided into (ASA1=14.6% ASA2=60.98% ASA3=24.39%) single shoot spinal anaesthesia -Group2= 34 patients (45.3%) divided into (ASA1=2.9%, ASA2=26.4% ASA3=61.7%, ASA4=8.8%) unilateral hypobaric spinal anesthesia. -Hemodynamic variations were more severe in group 1 (51% hypotension) compared to 30% in group 2 RR=1.69 and odds ratio=2.4 -these variations were more marked in the ASA3 subgroup (group 1=70% hypotension versus group 2=30%) with an RR=2.33 and an odds ratio=5.44 -39% of group 1 required vasoactive drugs (15mg +/- 11) versus 32% of group 2 (8mg+/- 6.49) - no difference in the use of morphine in post-op. Conclusions: Within the limits of the population studied, this work demonstrates the clinical value of unilateral spinal anesthesia in ortho-trauma surgery in the frail patient.

Keywords: spinal anaesthesia, vasopressor, morphine, hypobaric unilateral spinal anesthesia, ropivacaine, hip surgery, eldery, hemodynamic

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1784 Ultrasound as an Aid to Predict the Onset of Leaking in Dengue Haemorrhagic Fever: Experience of a Dengue Treatment Facility in South Asia

Authors: Hasn Perera, Is Almeida, Hnk Perera, Mzf Mohammed, Ade Silva, H. Wijesinghe, Ajal Fernando

Abstract:

Introduction: Dengue is a major Public Health burden of two clinical entities, Dengue Fever & Dengue Haemorrhagic Fever (DHF). The vast majority of dengue deaths occur in DHF patients, where the diagnosis hinges on the presence of fluid leakage. Limited Ultrasound Scans (USS) of chest and abdomen are used widely at Centre for Clinical Management of Dengue & Dengue Haemorrhagic Fever (CCMDDHF), as the primary method for detecting fluid leaking in DHF. This study analyses the relationship between haematological and USS findings at the onset of leaking and to further determine the usefulness of ultrasound in diagnosing DHF. Methods: A prospective analysis of 80 serologically confirmed dengue patients initially admitted to a General Medical and Paediatric wards who were subsequently transferred to the CCMDDHF from March to September 2017 were analysed. In addition to repeated blood counts and capillary haematocrits’, serial USS were done to detect the onset fluid leaking by three competent and experienced doctors at CCMDDHF. Results: 80 patients (male: female: 38:42) with a mean age of 20 years (SD ±16.8, range 3-74) were evaluated. Dropping of platelet counts below 100,000 and haematocrit rise towards 20% started 4±1.3 day of fever with a mean platelet value of 69x103(range17-98x103). Gallbladder wall thickening was the commonest (98.7%) USS finding followed by fluid in hepato-renal pouch (95%), pelvic fluid (58.7%), right-sided pleural effusion (35%), bilateral effusions (7.5%). USS evidence of plasma leakage was detected in 11.25 %( n=9) of DHF cases from 1 day before significant haematocrit rise was noted. 35 (43.7%) patients with lowering platelets and haematocrit rise showed no objective evidence of plasma leaking on ultrasound scan. Conclusion: This outbreak underscores the importance of USS as a useful, sensitive and cost-effective tool for early diagnosis of suspected DHF cases, facilitating the tracking of progress of leaking and management of epidemics.

Keywords: dengue, ultrasound, plasma leaking, South Asia

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1783 Nondestructive Testing for Reinforced Concrete Buildings with Active Infrared Thermography

Authors: Huy Q. Tran, Jungwon Huh, Kiseok Kwak, Choonghyun Kang

Abstract:

Infrared thermography (IRT) technique has been proven to be a good method for nondestructive evaluation of concrete material. In the building, a broad range of applications has been used such as subsurface defect inspection, energy loss, and moisture detection. The purpose of this research is to consider the qualitative and quantitative performance of reinforced concrete deteriorations using active infrared thermography technique. An experiment of three different heating regimes was conducted on a concrete slab in the laboratory. The thermal characteristics of the IRT method, i.e., absolute contrast and observation time, are investigated. A linear relationship between the observation time and the real depth was established with a well linear regression R-squared of 0.931. The results showed that the absolute contrast above defective area increases with the rise of the size of delamination and the heating time. In addition, the depth of delamination can be predicted by using the proposal relationship of this study.

Keywords: concrete building, infrared thermography, nondestructive evaluation, subsurface delamination

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1782 Emotional Analysis for Text Search Queries on Internet

Authors: Gemma García López

Abstract:

The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

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1781 Formalizing a Procedure for Generating Uncertain Resource Availability Assumptions Based on Real Time Logistic Data Capturing with Auto-ID Systems for Reactive Scheduling

Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

Abstract:

As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

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1780 Research on the Renewal and Utilization of Space under the Bridge in Chongqing Based on Spatial Potential Evaluation

Authors: Xvelian Qin

Abstract:

Urban "organic renewal" based on the development of existing resources in high-density urban areas has become the mainstream of urban development in the new era. As an important stock resource of public space in high-density urban areas, promoting its value remodeling is an effective way to alleviate the shortage of public space resources. However, due to the lack of evaluation links in the process of underpass space renewal, a large number of underpass space resources have been left idle, facing the problems of low space conversion efficiency, lack of accuracy in development decision-making, and low adaptability of functional positioning to citizens' needs. Therefore, it is of great practical significance to construct the evaluation system of under-bridge space renewal potential and explore the renewal mode. In this paper, some of the under-bridge spaces in the main urban area of Chongqing are selected as the research object. Through the questionnaire interviews with the users of the built excellent space under the bridge, three types of six levels and twenty-two potential evaluation indexes of "objective demand factor, construction feasibility factor and construction suitability factor" are selected, including six levels of land resources, infrastructure, accessibility, safety, space quality and ecological environment. The analytical hierarchy process and expert scoring method are used to determine the index weight, construct the potential evaluation system of the space under the bridge in high-density urban areas of Chongqing, and explore the direction of renewal and utilization of its suitability. To provide feasible theoretical basis and scientific decision support for the use of under bridge space in the future.

Keywords: high density urban area, potential evaluation, space under bridge, updated using

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1779 On-Line Data-Driven Multivariate Statistical Prediction Approach to Production Monitoring

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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1778 Charging-Vacuum Helium Mass Spectrometer Leak Detection Technology in the Application of Space Products Leak Testing and Error Control

Authors: Jijun Shi, Lichen Sun, Jianchao Zhao, Lizhi Sun, Enjun Liu, Chongwu Guo

Abstract:

Because of the consistency of pressure direction, more short cycle, and high sensitivity, Charging-Vacuum helium mass spectrometer leak testing technology is the most popular leak testing technology for the seal testing of the spacecraft parts, especially the small and medium size ones. Usually, auxiliary pump was used, and the minimum detectable leak rate could reach 5E-9Pa•m3/s, even better on certain occasions. Relative error is more important when evaluating the results. How to choose the reference leak, the background level of helium, and record formats would affect the leak rate tested. In the linearity range of leak testing system, it would reduce 10% relative error if the reference leak with larger leak rate was used, and the relative error would reduce obviously if the background of helium was low efficiently, the record format of decimal was used, and the more stable data were recorded.

Keywords: leak testing, spacecraft parts, relative error, error control

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1777 Dynamic Process Monitoring of an Ammonia Synthesis Fixed-Bed Reactor

Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

Abstract:

This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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1776 Brachypodium: A Model Genus to Study Grass Genome Organisation at the Cytomolecular Level

Authors: R. Hasterok, A. Betekhtin, N. Borowska, A. Braszewska-Zalewska, E. Breda, K. Chwialkowska, R. Gorkiewicz, D. Idziak, J. Kwasniewska, M. Kwasniewski, D. Siwinska, A. Wiszynska, E. Wolny

Abstract:

In contrast to animals, the organisation of plant genomes at the cytomolecular level is still relatively poorly studied and understood. However, the Brachypodium genus in general and B. distachyon in particular represent exceptionally good model systems for such study. This is due not only to their highly desirable ‘model’ biological features, such as small nuclear genome, low chromosome number and complex phylogenetic relations, but also to the rapidly and continuously growing repertoire of experimental tools, such as large collections of accessions, WGS information, large insert (BAC) libraries of genomic DNA, etc. Advanced cytomolecular techniques, such as fluorescence in situ hybridisation (FISH) with evermore sophisticated probes, empowered by cutting-edge microscope and digital image acquisition and processing systems, offer unprecedented insight into chromatin organisation at various phases of the cell cycle. A good example is chromosome painting which uses pools of chromosome-specific BAC clones, and enables the tracking of individual chromosomes not only during cell division but also during interphase. This presentation outlines the present status of molecular cytogenetic analyses of plant genome structure, dynamics and evolution using B. distachyon and some of its relatives. The current projects focus on important scientific questions, such as: What mechanisms shape the karyotypes? Is the distribution of individual chromosomes within an interphase nucleus determined? Are there hot spots of structural rearrangement in Brachypodium chromosomes? Which epigenetic processes play a crucial role in B. distachyon embryo development and selective silencing of rRNA genes in Brachypodium allopolyploids? The authors acknowledge financial support from the Polish National Science Centre (grants no. 2012/04/A/NZ3/00572 and 2011/01/B/NZ3/00177)

Keywords: Brachypodium, B. distachyon, chromosome, FISH, molecular cytogenetics, nucleus, plant genome organisation

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1775 Early Detection of Major Earthquakes Using Broadband Accelerometers

Authors: Umberto Cerasani, Luca Cerasani

Abstract:

Methods for earthquakes forecasting have been intensively investigated in the last decades, but there is still no universal solution agreed by seismologists. Rock failure is most often preceded by a tiny elastic movement in the failure area and by the appearance of micro-cracks. These micro-cracks could be detected at the soil surface and represent useful earth-quakes precursors. The aim of this study was to verify whether tiny raw acceleration signals (in the 10⁻¹ to 10⁻⁴ cm/s² range) prior to the arrival of main primary-waves could be exploitable and related to earthquakes magnitude. Mathematical tools such as Fast Fourier Transform (FFT), moving average and wavelets have been applied on raw acceleration data available on the ITACA web site, and the study focused on one of the most unpredictable earth-quakes, i.e., the August 24th, 2016 at 01H36 one that occurred in the central Italy area. It appeared that these tiny acceleration signals preceding main P-waves have different patterns both on frequency and time domains for high magnitude earthquakes compared to lower ones.

Keywords: earthquake, accelerometer, earthquake forecasting, seism

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1774 Performance Evaluation of Cement Mortar with Crushed Stone Dust as Fine Aggregates

Authors: Pradeep Kumar

Abstract:

The present work is based on application of cement mortar with natural sand and discontinuous steel fiber through which bending behavior of skinny beam was evaluated. This research is to study the effects of combining reinforcing steel meshes (continuous steel reinforcement) with discontinuous fibers as reinforcement in skinny walled Portland cement based cement mortar with crushed stone dust as a fine aggregate. The term ‘skinny’ means thickness of the beams is less than 25 mm. The main idea behind this combination is to satisfy the ultimate strength limit state through the steel mesh reinforcement (as a main reinforcement) and to control the cracking under service loads through fiber (Recron 3s) reinforcement (as secondary reinforcement). The main object of this study is to carry out the bending behavior of mortar reinforced thin beam with only one layer of steel mesh (with various transfer wire spacing) and with a recron 3s (Reliance) fifers. The wide experimental program with bending tests is undertaken. The following variables are investigated: (a) the reference mesh size - 25.4 x 25.4 mm and 50.8 x 50.8 mm; (b) the transverse wire spacing - 25.4 mm, 50.8 mm, and no transverse wires; (c) the type of fibers – Reliance (Recron 3s, 6mm length); and (d) the fiber volume fraction – 0.1% and 0.25%. Some of the main conclusions are: (a) the use of recron 3s fibers leads to a little better overall performance than that with no fiber; (b) an increase in equivalent stress is observed when 0.1% RF,0.25% R Fibers are used; (c) when 25.4 x 50.8 size steel mesh is used, no noticeable change in behavior is observed in comparison to specimens without fibers; and (d) for no fibers 0.1% and o.1% RF the transverse wire spacing has some little effect on the equivalent stress for RF fibers, the transverse wire has no influence but the equivalent stress are increased.

Keywords: cement mortar, crushed stone dust, fibre, steel mesh

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1773 Hyper Tuned RBF SVM: Approach for the Prediction of the Breast Cancer

Authors: Surita Maini, Sanjay Dhanka

Abstract:

Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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1772 A Memetic Algorithm Approach to Clustering in Mobile Wireless Sensor Networks

Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

Abstract:

Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

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1771 Extraction of Polystyrene from Styrofoam Waste: Synthesis of Novel Chelating Resin for the Enrichment and Speciation of Cr(III)/Cr(vi) Ions in Industrial Effluents

Authors: Ali N. Siyal, Saima Q. Memon, Latif Elçi, Aydan Elçi

Abstract:

Polystyrene (PS) was extracted from Styrofoam (expanded polystyrene foam) waste, so called white pollutant. The PS was functionalized with N, N- Bis(2-aminobenzylidene)benzene-1,2-diamine (ABA) ligand through an azo spacer. The resin was characterized by FT-IR spectroscopy and elemental analysis. The PS-N=N-ABA resin was used for the enrichment and speciation of Cr(III)/Cr(VI) ions and total Cr determination in aqueous samples by Flame Atomic Absorption Spectrometry (FAAS). The separation of Cr(III)/Cr(VI) ions was achieved at pH 2. The recovery of Cr(VI) ions was achieved ≥ 95.0% at optimum parameters: pH 2; resin amount 300 mg; flow rates 2.0 mL min-1 of solution and 2.0 mL min-1 of eluent (2.0 mol L-1 HNO3). Total Cr was determined by oxidation of Cr(III) to Cr(VI) ions using H2O2. The limit of detection (LOD) and quantification (LOQ) of Cr(VI) were found to be 0.40 and 1.20 μg L-1, respectively with preconcentration factor of 250. Total saturation and breakthrough capacitates of the resin for Cr(IV) ions were found to be 0.181 and 0.531 mmol g-1, respectively. The proposed method was successfully applied for the preconcentration/speciation of Cr(III)/Cr(VI) ions and determination of total Cr in industrial effluents.

Keywords: styrofoam waste, polymeric resin, preconcentration, speciation, Cr(III)/Cr(VI) ions, FAAS

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1770 Rapid Detection of MBL Genes by SYBR Green Based Real-Time PCR

Authors: Taru Singh, Shukla Das, V. G. Ramachandran

Abstract:

Objectives: To develop SYBR green based real-time PCR assay to detect carbapenemases (NDM, IMP) genes in E. coli. Methods: A total of 40 E. coli from stool samples were tested. Six were previously characterized as resistant to carbapenems and documented by PCR. The remaining 34 isolates previously tested susceptible to carbapenems and were negative for these genes. Bacterial RNA was extracted using manual method. The real-time PCR was performed using the Light Cycler III 480 instrument (Roche) and specific primers for each carbapenemase target were used. Results: Each one of the two carbapenemase gene tested presented a different melting curve after PCR amplification. The melting temperature (Tm) analysis of the amplicons identified was as follows: blaIMP type (Tm 82.18°C), blaNDM-1 (Tm 78.8°C). No amplification was detected among the negative samples. The results showed 100% concordance with the genotypes previously identified. Conclusions: The new assay was able to detect the presence of two different carbapenemase gene type by real-time PCR.

Keywords: resistance, b-lactamases, E. coli, real-time PCR

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1769 Water Leakage Detection System of Pipe Line using Radial Basis Function Neural Network

Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

Abstract:

Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

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1768 Frequency Distribution and Assertive Object Theory: An Exploration of the Late Bronze Age Italian Ceramic Landscape

Authors: Sara Fioretti

Abstract:

In the 2nd millennium BCE, maritime networks became essential to the Mediterranean lifestyle, creating an interconnected world. This phenomenon of interconnected cultures has often been misinterpreted as an “effect” of the Mycenaean “influence” without considering the complexity and role of regional and cross-cultural exchanges. This paper explores the socio-economic relationships, in both cross-cultural and potentially inter-regional settings, present within the archaeological repertoire of the southern Italian Late Bronze Age (LBA 1600 -1140 BCE). The emergence of economic relations within the connectivity of the regional settlements is explored through ceramic contexts found in the case studies Punta di Zambrone, Broglio di Trebisacce, and Nuraghe Antigori. This work-in-progress research is situated in the shifting theoretical views of the last ten years that discuss the Late Bronze Age’s connectivity through Social Networks, Entanglement, and Assertive Objects combined with a comparative statistical study of ceramic frequency distribution. Applying these theoretical frameworks with a quantitative approach demonstrates the specific regional economic relationships that shaped the cultural interactions of the Late Bronze Age. Through this intersection of theory and statistical analysis, the case studies establish a small percentage of pottery as imported, whilst assertive productions have a relatively higher quantity. Overall, the majority still adheres to regional Italian traditions. Therefore, we can dissect the rhizomatic relationships cultivated by the Italian coasts and Mycenaeans and their roles within their networks through the intersection of theoretical and statistical analysis. This research offers a new perspective on the connectivity of the Late Bronze Age relational structures.

Keywords: late bronze age, mediterranean archaeology, exchanges and trade, frequency distribution of ceramic assemblages

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1767 Linking the Built Environment, Activities and Well-Being: Examining the Stories among Older Adults during Ageing-in-Place

Authors: Wenquan Gan, Peiyu Zhao, Xinyu Zhao

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Under the background of the rapid development of China’s ageing population, ageing-in-place has become a primary strategy to cope with this problem promoted by the Chinese government. However, most older adults currently living in old residential communities are insufficient to support their ageing-in-place. Therefore, exploring how to retrofit existing communities towards ageing-friendly standards to support older adults is essential for healthy ageing. To better cope with this issue, this study aims to shed light on the inter-relationship among the built environment, daily activities, and well-being of older adults in urban China. Using mixed research methods including GPS tracking, structured observation, and in-depth interview to examine: (a) what specific places or facilities are most commonly used by the elderly in the ageing-in-place process; (b) what specific built environment characteristics attract older adults in these frequently used places; (c) how has the use of these spaces impacted the well-being of older adults. Specifically, structured observation and GPS are used to record and map the older residents’ behaviour and movement in Suzhou, China, a city with a highly aged population and suitable as a research case. Subsequently, a follow-up interview is conducted to explore what impact of activities and the built environment on their well-being. Results showed that for the elderly with good functional ability, the facilities promoted by the Chinese government to support ageing-in-place, such as community nursing homes for the aged, day-care centre, and activity centres for the aged, are rarely used by older adults. Additionally, older adults have their preferred activities and built environment characteristics that contribute to their well-being. Our findings indicate that a complex interrelationship between the built environment and activities can influence the well-being of the elderly. Further investigations are needed to understand how to support healthy ageing-in-place, especially in addition to providing permanent elder-ly-care facilities, but to attend to the design interventions that can enhance these particularly built environment characteristics to facilitate a healthy lifestyle in later life.

Keywords: older adults, built environment, spatial behavior, community activity, healthy ageing

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1766 High Fidelity Interactive Video Segmentation Using Tensor Decomposition, Boundary Loss, Convolutional Tessellations, and Context-Aware Skip Connections

Authors: Anthony D. Rhodes, Manan Goel

Abstract:

We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

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1765 Obsession Unveiled: A Freud’s Psychoanalytical Analysis of Protagonist Fixations in Nabokov’s Lolita and Pamuk’s The Museum of Innocence

Authors: Kamilya Khamitova

Abstract:

This study analyzes the overarching theme of obsession as portrayed through the two protagonists, Humbert Humbert and Kemal, in Vladimir Nabokov's Lolita and Orhan Pamuk's The Museum of Innocence through the lens of Freudian psychoanalytical theory of “transference.” Their obsessions are channeled into various forms of artistic expression following the loss of their beloved Lolita and Füsun. Employing psychoanalytical literary criticism, firmly grounded in the classical era of psychoanalysis, as pioneered by Sigmund Freud, this research explores the characters' psyches, revealing the concealed desires, conflicts, and symbolic manifestations within their relentless obsessions. The aim of this study is to unravel the psychological complexities of obsession, shedding light on the motivations and behaviors of Humbert and Kemal within the context of their respective narratives. Methodologically, this research employs close textual analysis of the novels, dissecting the protagonists' thoughts, actions, and artistic expressions. Through the lens of Freud's fundamental concept of “transference,” this analysis uncovers the protagonists' mechanisms of projecting their desires onto unattainable objects of desire—Lolita and Füsun. Humbert's pursuit of Lolita mirrors his unresolved emotional traumas and attempts to recapture the lost object of his childhood. In contrast, Kemal's fixation on Füsun is a desperate desire to fill an existential void, address a sense of inadequacy, and construct a semblance of immortality through the meticulous preservation of his memories with her. By adopting a psychoanalytic lens, this research provides a richer understanding of the characters, themes, and symbolism inherent in their artistic expressions of devotion.

Keywords: artistic expression, psychoanalysis of obsession, Sigmund Freud, transference

Procedia PDF Downloads 162