Search results for: machine monitoring
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5727

Search results for: machine monitoring

2037 Correlation of Material Mechanical Characteristics Obtained by Means of Standardized and Miniature Test Specimens

Authors: Vaclav Mentl, P. Zlabek, J. Volak

Abstract:

New methods of mechanical testing were developed recently that are based on making use of miniature test specimens (e.g. Small Punch Test). The most important advantage of these method is the nearly non-destructive withdrawal of test material and small size of test specimen what is interesting in cases of remaining lifetime assessment when a sufficient volume of the representative material cannot be withdrawn of the component in question. In opposite, the most important disadvantage of such methods stems from the necessity to correlate test results with the results of standardised test procedures and to build up a database of material data in service. The correlations among the miniature test specimen data and the results of standardised tests are necessary. The paper describes the results of fatigue tests performed on miniature tests specimens in comparison with traditional fatigue tests for several steels applied in power producing industry. Special miniature test specimens fixtures were designed and manufactured for the purposes of fatigue testing at the Zwick/Roell 10HPF5100 testing machine. The miniature test specimens were produced of the traditional test specimens. Seven different steels were fatigue loaded (R = 0.1) at room temperature.

Keywords: mechanical properties, miniature test specimens, correlations, small punch test, micro-tensile test, mini-charpy impact test

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2036 Numerical Analysis of Wire Laser Additive Manufacturing for Low Carbon Steels+

Authors: Juan Manuel Martinez Alvarez, Michele Chiumenti

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This work explores the benefit of the thermo-metallurgical simulation to tackle the Wire Laser Additive Manufacturing (WLAM) of low-carbon steel components. The Finite Element Analysis is calibrated by process monitoring via thermal imaging and thermocouples measurements, to study the complex thermo-metallurgical behavior inherent to the WLAM process of low carbon steel parts.A critical aspect is the analysis of the heterogeneity in the resulting microstructure. This heterogeneity depends on both the thermal history and the residual stresses experienced during the WLAM process. Because of low carbon grades are highly sensitive to quenching, a high-gradient microstructure often arises due to the layer-by-layer metal deposition in WLAM. The different phases have been identified by scanning electron microscope. A clear influence of the heterogeneities on the final mechanical performance has been established by the subsequent mechanical characterization. The thermo-metallurgical analysis has been used to determine the actual thermal history and the corresponding thermal gradients during the printing process. The correlation between the thermos-mechanical evolution, the printing parameters and scanning sequence has been established. Therefore, an enhanced printing strategy, including optimized process window has been used to minimize the microstructure heterogeneity at ArcelorMittal.

Keywords: additive manufacturing, numerical simulation, metallurgy, steel

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2035 Numerical Simulation for a Shallow Braced Excavation of Campus Building

Authors: Sao-Jeng Chao, Wen-Cheng Chen, Wei-Humg Lu

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In order to prevent encountering unpredictable factors, geotechnical engineers always conduct numerical analysis for braced excavation design. Simulation work in advance can predict the response of subsequent excavation and thus will be designed to increase the security coefficient of construction. The parameters that are considered include geological conditions, soil properties, soil distributions, loading types, and the analysis and design methods. National Ilan University is located on the LanYang plain, mainly deposited by clayey soil and loose sand, and thus is vulnerable to external influence displacement. National Ilan University experienced a construction of braced excavation with a complete program of monitoring excavation. This study takes advantage of a one-dimensional finite element method RIDO to simulate the excavation process. The predicted results from numerical simulation analysis are compared with the monitored results of construction to explore the differences between them. Numerical simulation analysis of the excavation process can be used to analyze retaining structures for the purpose of understanding the relationship between the displacement and supporting system. The resulting deformation and stress distribution from the braced excavation cab then be understand in advance. The problems can be prevented prior to the construction process, and thus acquire all the affected important factors during design and construction.

Keywords: excavation, numerical simulation, RIDO, retaining structure

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2034 Managing the Magnetic Protection of Workers in Magnetic Resonance Imaging

Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

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Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

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2033 Fuzzy Neuro Approach for Integrated Water Management System

Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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2032 Microstructure of Ti – AlN Composite Produced by Selective Laser Melting

Authors: Jaroslaw Mizera, Pawel Wisniewski, Ryszard Sitek

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Selective Laser Melting (SLM) is an advanced additive manufacturing technique used for producing parts made of wide range of materials such as: austenitic steel, titanium, nickel etc. In the our experiment we produced a Ti-AlN composite from a mixture of titanium and aluminum nitride respectively 70% at. and 30% at. using SLM technique. In order to define the size of powder particles, laser diffraction tests were performed on HORIBA LA-950 device. The microstructure and chemical composition of the composite was examined by Scanning Electron Microscopy (SEM). The chemical composition in micro areas of the obtained samples was determined by of EDS. The phase composition was analyzed by X-ray phase analysis (XRD). Microhardness Vickers tests were performed using Zwick/Roell microhardness machine under the load of 0.2kG (HV0.2). Hardness measurements were made along the building (xy) and along the plane of the lateral side of the cuboid (xz). The powder used for manufacturing of the samples had a mean particle size of 41μm. It was homogenous with a spherical shape. The specimens were built chiefly from Ti, TiN and AlN. The dendritic microstructure was porous and fine-grained. Some of the aluminum nitride remained unmelted but no porosity was observed in the interface. The formed material was characterized by high hardness exceeding 700 HV0.2 over the entire cross-section.

Keywords: Selective Laser Melting, Composite, SEM, microhardness

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2031 Operational Software Maturity: An Aerospace Industry Analysis

Authors: Raúl González Muñoz, Essam Shehab, Martin Weinitzke, Chris Fowler, Paul Baguley

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Software applications have become crucial to the aerospace industry, providing a wide range of functionalities and capabilities used during the design, manufacturing and support of aircraft. However, as this criticality increases, so too does the risk for business operations when facing a software failure. Hence, there is a need for new methodologies to be developed to support aerospace companies in effectively managing their software portfolios, avoiding the hazards of business disruption and additional costs. This paper aims to provide a definition of operational software maturity, and how this can be used to assess software operational behaviour, as well as a view on the different aspects that drive software maturity within the aerospace industry. The key research question addressed is, how can operational software maturity monitoring assist the aerospace industry in effectively managing large software portfolios? This question has been addressed by conducting an in depth review of current literature, by working closely with aerospace professionals and by running an industry case study within a major aircraft manufacturer. The results are a software maturity model composed of a set of drivers and a prototype tool used for the testing and validation of the research findings. By utilising these methodologies to assess the operational maturity of software applications in aerospace, benefits in maintenance activities and operations disruption avoidance have been observed, supporting business cases for system improvement.

Keywords: aerospace, software lifecycle, software maintenance, software maturity

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2030 Estimation of Transition and Emission Probabilities

Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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2029 Bacterial Profiling and Development of Molecular Diagnostic Assays for Detection of Bacterial Pathogens Associated with Bovine mastitis

Authors: Aqeela Ashraf, Muhammad Imran, Tahir Yaqub, Muhammad Tayyab, Yung Fu Chang

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For the identification of bovine mastitic pathogen, an economical, rapid and sensitive molecular diagnostic assay is developed by PCR multiplexing of gene and pathogenic species specific DNA sequences. The multiplex PCR assay is developed for detecting nine important bacterial pathogens causing mastitis Worldwide. The bacterial species selected for this study are Streptococcus agalactiae, Streptococcus dysagalactiae, Streptococcus uberis, Staphylococcus aureus, Escherichia coli, Staphylococcus haemolyticus, Staphylococcus chromogenes Mycoplasma bovis and Staphylococcus epidermidis. A single reaction assay was developed and validated by 27 reference strains and further tested on 276 bacterial strains obtained from culturing mastitic milk. The multiplex PCR assay developed here is further evaluated by applying directly on genomic DNA isolated from 200 mastitic milk samples. It is compared with bacterial culturing method and proved to be more sensitive, rapid, economical and can specifically identify 9 bacterial pathogens in a single reaction. It has detected the pathogens in few culture negative mastitic samples. Recognition of disease is the foundation of disease control and prevention. This assay can be very helpful for maintaining the udder health and milk monitoring.

Keywords: multiplex PCR, bacteria, mastitis, milk

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2028 Digital Twin of Real Electrical Distribution System with Real Time Recursive Load Flow Calculation and State Estimation

Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone

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Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.

Keywords: digital twin, distributed energy resources, remote terminal units, supervisory control and data acquisition system, smart recursive load flow

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2027 Adapting Grain Crop Cleaning Equipment for Sesame and Other Emerging Spice Crops

Authors: Ramadas Narayanan, Surya Bhattrai, Vu Hoan

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Threshing and cleaning are crucial post-harvest procedures that are carried out to separate the grain or seed from the harvested plant and eliminate any potential contaminants or foreign debris. After harvesting, threshing and cleaning are necessary for the clean seeds to guarantee high quality and acceptable for consumption or further processing. For mechanised production, threshing can be conducted in a thresher. Afterwards, the seeds are to be cleaned in dedicated seed-cleaning facilities. This research investigates the effectiveness of Kimseed cleaning equipment MK3, designed for grain crops for processing new crops such as sesame, fennel and kalonji. Subsequently, systematic trials were conducted to adapt the equipment to the applications in sesame and spice crops. It was done to develop methods for mechanising harvest and post-harvest operations. For sesame, it is recommended to have t a two-step process in the cleaning machine to remove large and small contaminants. The first step is to remove the large contaminants, and the second is to remove the smaller ones. The optimal parameters for cleaning fennel are a shaker frequency of 6.0 to 6.5 Hz and an airflow of 1.0 to 1.5 m/s. The optimal parameters for cleaning kalonji are a shaker frequency of 5.5Hz to 6.0 Hz and airflow of 1.0 to under 1.5m/s.

Keywords: sustainable mechanisation, sead cleaning process, optimal setting, shaker frequency

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2026 Design of EV Steering Unit Using AI Based on Estimate and Control Model

Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

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2025 Performants: Making the Organization of Concerts Easier

Authors: Ioannis Andrianakis, Panagiotis Panagiotopoulos, Kyriakos Chatzidimitriou, Dimitrios Tampakis, Manolis Falelakis

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Live music, whether performed in organized venues, restaurants, hotels or any other spots, creates value chains that support and develop local economies and tourism development. In this paper, we describe PerformAnts, a platform that increases the mobility of musicians and their accessibility to remotely located venues by rationalizing the cost of live acts. By analyzing the event history and taking into account their potential availability, the platform provides bespoke recommendations to both bands and venues while also facilitating the organization of tours and helping rationalize transportation expenses by realizing an innovative mechanism called “chain booking”. Moreover, the platform provides an environment where complicated tasks such as technical and financial negotiations, concert promotion or copyrights are easily manipulated by users using best practices. The proposed solution provides important benefits to the whole spectrum of small/medium size concert organizers, as the complexity and the cost of the production are rationalized. The environment is also very beneficial for local talent, musicians that are very mobile, venues located away from large urban areas or in touristic destinations, and managers who will be in a position to coordinate a larger number of musicians without extra effort.

Keywords: machine learning, music industry, creative industries, web applications

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2024 Development of Biodegradable Plastic as Mango Fruit Bag

Authors: Andres M. Tuates Jr., Ofero A. Caparino

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Plastics have achieved a dominant position in agriculture because of their transparency, lightness in weight, impermeability to water and their resistance to microbial attack. However, this generates a higher quantity of wastes that are difficult to dispose of by farmers. To address these problems, the project aim to develop and evaluate the biodegradable film for mango fruit bag during development. The PBS and starch were melt-blended in a twin-screw extruder and then blown into film extrusion machine. The physic-chemical-mechanical properties of biodegradable fruit bag were done following standard methods of test. Field testing of fruit bag was also conducted to evaluate its durability and efficiency field condition. The PHilMech-FiC fruit bag is made of biodegradable material measuring 6 x 8 inches with a thickness of 150 microns. The tensile strength is within the range of LDPE while the elongation is within the range of HDPE. It is projected that after thirty-six (36) weeks, the film will be totally degraded. Results of field testing show that the quality of harvested fruits using PHilMech-FiC biodegradable fruit bag in terms of percent marketable, non-marketable and export, peel color at the ripe stage, flesh color, TSS, oBrix, percent edible portion is comparable with the existing bagging materials such as Chinese brown paper bag and old newspaper.

Keywords: cassava starch, PBS, biodegradable, chemical, mechanical properties

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2023 Convergence and Stability in Federated Learning with Adaptive Differential Privacy Preservation

Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

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2022 Feasibility of Using Musical Intervention to Promote Growth in Preterm Infants in the Neonatal Intensive Care Unit (NICU)

Authors: Yutong An

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Premature babies in the Neonatal Intensive Care Unit (NICU) are usually protected in individual incubators to ensure a constant temperature and humidity. Accompanied by 24-hour monitoring by medical equipment, this provides a considerable degree of protection for the growth of preterm babies. However, preterm babies are still continuously exposed to noise at excessively high decibels (>45dB). Such noise has a highly damaging effect on the growth and development of preterm babies. For example, in the short term, it can lead to sleep deprivation, stress reactions, and difficulty calming emotions, while in the long term, it can trigger endocrine disorders, metabolic disorders, and hearing impairment. Fortunately, musical interventions in the NICU have been shown to provide calmness to newborns. This article integrates existing research on three types of music that are beneficial for preterm infants and their respective advantages and disadvantages. This paper aims to present a possibility, based on existing NICU equipment and experimental data related to musical interventions, to reduce the impact of noise on preterm babies in the NICU through a system design approach that incorporates a personalized adjustable music system in the incubator and an overall music enhancement in the open bay of the NICU.

Keywords: music interventions, neonatal intensive care unit (NICU), premature babies, neonatal nursing

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2021 School Emergency Drills Evaluation through E-PreS Monitoring System

Authors: A. Kourou, A. Ioakeimidou, V. Avramea

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Planning for natural disasters and emergencies is something every school or educational institution must consider, regardless of its size or location. Preparedness is the key to save lives if a disaster strikes. School disaster management mirrors individual and family disaster prevention, and wider community disaster prevention efforts. This paper presents the usage of E-PreS System as a helpful, managerial tool during the school earthquake drill, in order to support schools in developing effective disaster and emergency plans specific to their local needs. The project comes up with a holistic methodology using real-time evaluation involving different categories of actors, districts, steps and metrics. The main outcomes of E-PreS project are the development of E-PreS web platform that host the needed data of school emergency planning; the development of E-PreS System; the implementation of disaster drills using E-PreS System in educational premises and local schools; and the evaluation of E-PreS System. Taking into consideration that every disaster drill aims to test and valid school plan and procedures; clarify and train personnel in roles and responsibilities; improve interagency coordination; identify gaps in resources; improve individual performance; and identify opportunities for improvement, E-PreS Project was submitted and approved by the European Commission (EC).

Keywords: disaster drills, earthquake preparedness, E-PreS System, school emergency plans

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2020 Measuring the Amount of Eroded Soil and Surface Runoff Water in the Field

Authors: Abdulfatah Faraj Aboufayed

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Water erosion is the most important problems of the soil in the Jebel Nefusa area located in north west of Libya, therefore erosion station had been established in the Faculty of Veterinary and rainfed agriculture research Station, University of the Jepel Algherbee in Zentan. The length of the station is 72.6 feet, 6 feet width, and the percentage of it's slope is 3%. The station was established to measure the mount of soil eroded and amount of surface water produced during the seasons 95/96 and 96/97 from each rain storms. The Monitoring shows that there was a difference between the two seasons in the number of rainstorms which made differences in the amount of surface runoff water and the amount of soil eroded between the two seasons. Although the slope is low (3%), the soil texture is sandy and the land ploughed twice during each season surface runoff and soil eroded occurred. The average amount of eroded soil was 3792 grams (gr) per season and the average amount of surface runoff water was 410 litter (L) per season. The amount of surface runoff water would be much greater from Jebel Nefusa upland with steep slopes and collecting of them will save a valuable amount of water which lost as a runoff while this area is in desperate of this water. The regression analysis of variance show strong correlation between rainfall depth and the other two depended variable (the amount of surface runoff water and the amount of eroded soil). It shows also strong correlation between amount of surface runoff water and amount of eroded soil.

Keywords: rain, surface runoff water, soil, water erosion, soil erosion

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2019 Strategies for Student Recruitment in Civil Engineering

Authors: Diogo Ribeiro, Teresa Neto, Ricardo Santos, Maria Portela, Alexandra Trincão

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This article describes a set of innovating student recruitment strategies in a 1st cycle course of Civil Engineering, in particular the Civil Engineering Degree from the School of Engineering - Polytechnic of Porto (ISEP-PP). The strategies described were two-fold, targeting, for one, the increment on the number of admissions for the degree’s first year and two, promoting the re-entry of students who, for whatever reason, interrupted their studies. For the first objective, teacher-student binomials were set, whilst for the second, personalized contacts and assistance were provided. The main initiatives were promoted by the team of degree directors and were upheld with the participation and in consonance with the School’s external relations office. These initiatives were put forward as an attempt to minimize the impact of a national and international crisis on the AEC industry when the sustainability of the course was at risk. The implementation of these strategies was assessed on basis of a statistical analysis of the data collected from official sources and by surveys promoted. The results showed that the re-entry boost of former students, attending classes scattered on the three curricular years, secured registrations on some Curricular Units (UC’s) which more than doubled their numbers. Accompanied by a still incipient but regained interest on Civil Engineering it was possible in the short span of three years to reset the number of new students from less than 10 to the currently maximum allowed of 75, and so invert the tendency of an abrupt decline on the total number of students enrolled on the degree.

Keywords: civil engineering, monitoring, performance indicators, strategies, student recruitment

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2018 Design and Application of NFC-Based Identity and Access Management in Cloud Services

Authors: Shin-Jer Yang, Kai-Tai Yang

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In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: cloud service, multi-tenancy, NFC, IAM, mobile device

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2017 Tensile Force Estimation for Real-Size Pre-Stressed Concrete Girder using Embedded Elasto-Magnetic Sensor

Authors: Junkyeong Kim, Jooyoung Park, Aoqi Zhang, Seunghee Park

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The tensile force of Pre-Stressed Concrete (PSC) girder is the most important factor for evaluating the performance of PSC girder bridges. To measure the tensile force of PSC girder, several NDT methods were studied. However, conventional NDT method cannot be applied to the real-size PSC girder because the PS tendons could not be approached. To measure the tensile force of real-size PSC girder, this study proposed embedded EM sensor based tensile force estimation method. The embedded EM sensor could be installed inside of PSC girder as a sheath joint before the concrete casting. After curing process, the PS tendons were installed, and the tensile force was induced step by step using hydraulic jacking machine. The B-H loop was measured using embedded EM sensor at each tensile force steps and to compare with actual tensile force, the load cell was installed at each end of girder. The magnetization energy loss, that is the closed area of B-H loop, was decreased according to the increase of tensile force with regular pattern. Thus, the tensile force could be estimated by the tracking the change of magnetization energy loss of PS tendons. Through the experimental result, the proposed method can be used to estimate the tensile force of the in-situ real-size PSC girder bridge.

Keywords: tensile force estimation, embedded EM sensor, magnetization energy loss, PSC girder

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2016 Assessment of Water Quality Used for Irrigation: Case Study of Josepdam Irrigation Scheme

Authors: M. A. Adejumobi, J. O. Ojediran

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The aim of irrigation is to recharge the available water in the soil. Quality of irrigation water is essential for the yield and quality of crops produced, maintenance of soil productivity and protection of the environment. The analysis of irrigation water arises as a need to know the impact of irrigation water on the yield of crops, the effect, and the necessary control measures to rectify the effect of this for optimum production and yield of crops. This study was conducted to assess the quality of irrigation water with its performance on crop planted, in Josepdam irrigation scheme Bacita, Nigeria. Field visits were undertaken to identify and locate water supply sources and collect water samples from these sources; X1 Drain, Oshin, River Niger loop and Ndafa. Laboratory experiments were then undertaken to determine the quality of raw water from these sources. The analysis was carried for various parameters namely; physical and chemical analyses after water samples have been taken from four sources. The samples were tested in laboratory. Results showed that the raw water sources shows no salinity tendencies with SAR values less than 1me/l and Ecvaules at Zero while the pH were within the recommended range by FAO, there are increase in potassium and sulphate content contamination in three of the location. From this, it is recommended that there should be proper monitoring of the scheme by conducting analysis of water and soil in the environment, preferable test should be carried out at least one year to cover the impact of seasonal variations and to determine the physical and chemical analysis of the water used for irrigation at the scheme.

Keywords: irrigation, salinity, raw water quality, scheme

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2015 The Quantitative Analysis of Tourism Carrying Capacity with the Approach of Sustainable Development Case Study: Siahsard Fountain

Authors: Masoumeh Tadayoni, Saeed Kamyabi, Alireza Entezari

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Background and goal of the research: In planning and management system, the tourism carrying capacity is used as a holistic approach and supportive instrument. Evaluating the carrying capacity is used in quantitative the resource exploitation in line with sustainable development and as a foundation for identifying the changes in natural ecosystem and for the final evaluation and monitoring the tensions and decays in regressed ecosystem. Therefore, the present research tries to determine the carrying capacity of effective, physical and real range of Siahsard tourism region. Method: In the present research, the quantitative analysis of tourism carrying capacity is studied by used of effective or permissible carrying capacity (EPCC), real carrying capacity (PCC) and physical carrying capacity (RCC) in Siahsard fountain. It is analyzed based on the field survey and various resources were used for collecting information. Findings: The results of the analysis shows that, 3700 people use the Siahsard tourism region every day and 1350500 people use it annually. However, the evaluation of carrying capacity can be annually 1390650 people in this place. It can be an important tourism place along with other places in the region. Results: Siahsard’s tourism region has a little way to reach to its carrying capacity that needs to be analyzed. However, based on the results, some suggestions were offered for sustainable development of this region and as the most logical alternations for tourism management.

Keywords: carrying capacity, evaluation, Siahsard, tourism

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2014 The Potential of Sentiment Analysis to Categorize Social Media Comments Using German Libraries

Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

Procedia PDF Downloads 174
2013 Use of Treated Municipal Wastewater on Artichoke Crop

Authors: G. Disciglio, G. Gatta, A. Libutti, A. Tarantino, L. Frabboni, E. Tarantino

Abstract:

Results of a field study carried out at Trinitapoli (Puglia region, southern Italy) on the irrigation of an artichoke crop with three types of water (secondary-treated wastewater, SW; tertiary-treated wastewater, TW; and freshwater, FW) are reported. Physical, chemical and microbiological analyses were performed on the irrigation water, and on soil and yield samples. The levels of most of the chemical parameters, such as electrical conductivity, total suspended solids, Na+, Ca2+, Mg+2, K+, sodium adsorption ratio, chemical oxygen demand, biological oxygen demand over 5 days, NO3 –N, total N, CO32, HCO3, phenols and chlorides of the applied irrigation water were significantly higher in SW compared to GW and TW. No differences were found for Mg2+, PO4-P, K+ only between SW and TW. Although the chemical parameters of the three irrigation water sources were different, few effects on the soil were observed. Even though monitoring of Escherichia coli showed high SW levels, which were above the limits allowed under Italian law (DM 152/2006), contamination of the soil and the marketable yield were never observed. Moreover, no Salmonella spp. were detected in these irrigation waters; consequently, they were absent in the plants. Finally, the data on the quantitative-qualitative parameters of the artichoke yield with the various treatments show no significant differences between the three irrigation water sources. Therefore, if adequately treated, municipal wastewater can be used for irrigation and represents a sound alternative to conventional water resources.

Keywords: artichoke, soil chemical characteristics, fecal indicators, treated municipal wastewater, water recycling

Procedia PDF Downloads 422
2012 Application of Rapid Eye Imagery in Crop Type Classification Using Vegetation Indices

Authors: Sunita Singh, Rajani Srivastava

Abstract:

For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.

Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices

Procedia PDF Downloads 356
2011 AI-Based Technologies for Improving Patient Safety and Quality of Care

Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

Abstract:

Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

Procedia PDF Downloads 72
2010 Modeling Pan Evaporation Using Intelligent Methods of ANN, LSSVM and Tree Model M5 (Case Study: Shahroud and Mayamey Stations)

Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

Abstract:

The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

Procedia PDF Downloads 71
2009 An Investigation of the Therapeutic Effects of Indian Classical Music (Raga Bhairavi) on Mood and Physiological Parameters of Scholars

Authors: Kalpana Singh, Nikita Katiyar

Abstract:

This research investigates the impact of Raga Bhairavi, a prominent musical scale in Indian classical music, on the mood and basic physiological parameters of research scholars at the University of Lucknow - India. The study focuses on the potential therapeutic effects of listening to Raga Bhairavi during morning hours. A controlled experimental design is employed, utilizing self-reporting tools for mood assessment and monitoring physiological indicators such as heart rate, oxygen saturation levels, body temperature and blood pressure. The hypothesis posits that exposure to Raga Bhairavi will lead to positive mood modulation and a reduction in physiological stress markers among research scholars. Data collection involves pre and post-exposure measurements, providing insights into the immediate and cumulative effects of the musical intervention. The study aims to contribute valuable information to the growing field of music therapy, offering a potential avenue for enhancing the well-being and productivity of individuals engaged in intense cognitive activities. Results may have implications for the integration of music-based interventions in academic and research environments, fostering a conducive atmosphere for intellectual pursuits.

Keywords: bio-musicology, classical music, mood assessment, music therapy, physiology, Raga Bhairavi

Procedia PDF Downloads 48
2008 An Improved Convolution Deep Learning Model for Predicting Trip Mode Scheduling

Authors: Amin Nezarat, Naeime Seifadini

Abstract:

Trip mode selection is a behavioral characteristic of passengers with immense importance for travel demand analysis, transportation planning, and traffic management. Identification of trip mode distribution will allow transportation authorities to adopt appropriate strategies to reduce travel time, traffic and air pollution. The majority of existing trip mode inference models operate based on human selected features and traditional machine learning algorithms. However, human selected features are sensitive to changes in traffic and environmental conditions and susceptible to personal biases, which can make them inefficient. One way to overcome these problems is to use neural networks capable of extracting high-level features from raw input. In this study, the convolutional neural network (CNN) architecture is used to predict the trip mode distribution based on raw GPS trajectory data. The key innovation of this paper is the design of the layout of the input layer of CNN as well as normalization operation, in a way that is not only compatible with the CNN architecture but can also represent the fundamental features of motion including speed, acceleration, jerk, and Bearing rate. The highest prediction accuracy achieved with the proposed configuration for the convolutional neural network with batch normalization is 85.26%.

Keywords: predicting, deep learning, neural network, urban trip

Procedia PDF Downloads 134