Search results for: perturbation method

Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: Se-Hwa Park, En-Kyung Han, Jae-Young Lim, Hye-Jung Ahn

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Purpose: The objective of this study is to provide basic data for understanding the substance of inpatient life with CRPS (Complex Regional Pain Syndrome) and developing efficient and effective nursing intervention. Methods: From September 2018 to November, we have interviewed 10 CRPS patients about inpatient experiences. To understand the implication of inpatient life experiences with CRPS and intrinsic structure, we have used the question: 'How about the inpatient experiences with CRPS'. For data analysis, the method suggested by Colaizzi was applied as a phenomenological method. Results: According to the analysis, the study participants' inpatient life process was structured in six categories: (a) breakthrough pain experience (b) the limitation of pain treatment, (c) worsen factors of pain during inpatient period, (d) treat method for pain, (e) positive experience for inpatient period, (f) requirements for medical team, family and people in hospital room. Conclusion: Inpatient with CRPS have experienced the breakthrough pain. They had expected immediate treatment for breakthrough pain, but they experienced severe pain because immediate treatment was not implemented. Pain-worsening factors which patients with CRPS are as follows: personal factors from negative emotions such as insomnia, stress, sensitive character, pain part touch or vibration stimulus on the bed, physical factors from high threshold or rapid speed during fast transfer, conflict with other people, climate factors such as humidity or low temperature, noise, smell, lack of space because of many visitors. Patients actively manage the pain committing into another tasks or diversion. And also, patients passively manage the pain, just suppress, give-up. They think positively about rehabilitation treatment. And they require the understanding and sympathy for other people, and emotional support, immediate intervention for medical team. Based on the results of this study, we suppose the guideline of systematic breakthrough pain management for the relaxation of sudden pain, using notice of informing caution for touch or vibration. And we need to develop non-medicine pain management nursing intervention.

Keywords: breakthrough pain, CRPS, complex regional pain syndrome, inpatient life experiences, phenomenological method

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Authors: Phawin Sangsuvan, Chutimet Srinilta

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This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.

Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques

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Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

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Authors: Hossein Ramezani Ali-Akbari

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This paper presents an innovative method to control the rotational speed of a satellite solar panel during its deployment phase. A brushed DC motor has been utilized in the passive spring driven deployment mechanism to reduce the deployment speed. In order to use the DC motor as a damper, its connector terminals have been connected with an external resistance in a closed circuit. It means that, in this approach, there is no external power supply in the circuit. The working principle of this method is based on the back electromotive force (or back EMF) of the DC motor when an external torque (here the torque produced by the torsional springs) is coupled to the DC motor’s shaft. In fact, the DC motor converts to an electric generator and the current flows into the circuit and then produces the back EMF. Based on Lenz’s law, the generated current produced a torque which acts opposite to the applied external torque, and as a result, the deployment speed of the solar panel decreases. The main advantage of this method is to set an intended damping coefficient to the system via changing the external resistance. To produce the sufficient current, a gearbox has been assembled to the DC motor which magnifies the number of turns experienced by the DC motor. The coupled electro-mechanical equations of the system have been derived and solved, then, the obtained results have been presented. A full-scale prototype of the deployment mechanism has been built and tested. The potential application of brushed DC motors as a rotational speed damper has been successfully demonstrated.

Keywords: back electromotive force, brushed DC motor, rotational speed damper, satellite solar panel deployment mechanism

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Authors: Phornpat Chewasoonthorn, Surat Kwanmuang

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Indoor positioning technologies have been evolved rapidly. They augment the Global Positioning System (GPS) which requires line-of-sight to the sky to track the location of people or objects. This study developed an error correction method for an indoor real-time location system (RTLS) based on an ultra-wideband (UWB) sensor from Decawave. Multiple stationary nodes (anchor) were installed throughout the workspace. The distance between stationary and moving nodes (tag) can be measured using a two-way-ranging (TWR) scheme. The result has shown that the uncorrected ranging error from the sensor system can be as large as 1 m. To reduce ranging error and thus increase positioning accuracy, This study purposes an online correction algorithm using the Kalman filter. The results from experiments have shown that the system can reduce ranging error down to 5 cm.

Keywords: indoor positioning, ultra-wideband, error correction, Kalman filter

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

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We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

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Authors: Adrian Priceputu, Elena Mihaela Stan

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Our research addresses a critical challenge in renewable energy: improving efficiency and reducing the costs associated with the installation of ground-mounted photovoltaic (PV) panels. The most commonly used foundation solution is metal piles - with various sections adapted to soil conditions and the structural model of the panels. However, direct foundation systems are also sometimes used, especially in brownfield sites. Although metal micropiles are generally the first design option, understanding and predicting their bearing capacity, particularly under varied soil conditions, remains an open research topic. CPT Method and Current Challenges: Metal piles are favored for PV panel foundations due to their adaptability, but existing design methods rely heavily on costly and time-consuming in situ tests. The Cone Penetration Test (CPT) offers a more efficient alternative by providing valuable data on soil strength, stratification, and other key characteristics with reduced resources. During the test, a cone-shaped probe is pushed into the ground at a constant rate. Sensors within the probe measure the resistance of the soil to penetration, divided into cone penetration resistance and shaft friction resistance. Despite some existing CPT-based design approaches for metal piles, these methods are often cumbersome and difficult to apply. They vary significantly due to soil type and foundation method, and traditional approaches like the LCPC method involve complex calculations and extensive empirical data. The method was developed by testing 197 piles on a wide range of ground conditions, but the tested piles were very different from the ones used for PV pile foundations, making the method less accurate and practical for steel micropiles. Project Objectives and Methodology: Our research aims to develop a calculation method for metal micropile foundations using CPT data, simplifying the complex relationships involved. The goal is to estimate the pullout bearing capacity of piles without additional laboratory tests, streamlining the design process. To achieve this, a case study was selected which will serve for the development of an 80ha solar power station. Four testing locations were chosen spread throughout the site. At each location, two types of steel profiles (H160 and C100) were embedded into the ground at various depths (1.5m and 2.0m). The piles were tested for pullout capacity under natural and inundated soil conditions. CPT tests conducted nearby served as calibration points. The results served for the development of a preliminary equation for estimating pullout capacity. Future Work: The next phase involves validating and refining the proposed equation on additional sites by comparing CPT-based forecasts with in situ pullout tests. This validation will enhance the accuracy and reliability of the method, potentially transforming the foundation design process for PV panels.

Keywords: cone penetration test, foundation optimization, solar power stations, steel pile foundations

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Authors: Rema Daher, Theodor Chakhachiro, Daniel Asmar

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In the era of autonomous robot mapping, assessing the goodness of the generated maps is important, and is usually performed by aligning them to ground truth. Map alignment is difficult for two reasons: first, the query maps can be significantly distorted from ground truth, and second, establishing what constitutes ground truth for different settings is challenging. Most map alignment techniques to this date have addressed the first problem, while paying too little importance to the second. In this paper, we propose a benchmark dataset, which consists of synthetically transformed maps with their corresponding displacement fields. Furthermore, we propose a new system for comparison, where the displacement field of any map alignment technique can be computed and compared to the ground truth using statistical measures. The local information in displacement fields renders the evaluation system applicable to any alignment technique, whether it is linear or not. In our experiments, the proposed method was applied to different alignment methods from the literature, allowing for a comparative assessment between them all.

Keywords: assessment methods, benchmark, image deformation, map alignment, robot mapping, robot motion

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Authors: Najme Lari, Shahrokh Ahangarani, Ali Shanaghi

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Sol-gel technology is a promising manufacturing method to produce anti reflective silica thin films for solar energy applications. So to improve the properties of the films, controlling parameter of the sol - gel method is very important. In this study, soaking treatment effect on optical properties of silica anti reflective thin films was investigated. UV-Visible Spectroscopy, Fourier-Transformed Infrared Spectrophotometer and Field Emission Scanning Electron Microscopy was used for the characterization of silica thin films. Results showed that all nanoporous silica layers cause to considerable reduction of light reflections compared with uncoated glasses. With single layer deposition, the amount of reduction depends on the dipping time of coating and has an optimal time. Also, it was found that solar transmittance increased from 91.5% for the bare slide up to 97.5% for the best made sample corresponding to two deposition cycles.

Keywords: sol–gel, silica thin films, anti reflective coatings, optical properties, soaking treatment

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Authors: Ossama Abdelmotaal, Olfat Shaker, Tarek Salman, Lamiaa Nabeel, Mostafa Shabayek

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Colorectal Cancer (CRC) is an important worldwide health problem. Colonoscopy is used in detecting CRC suffer from drawbacks where colonoscopy is an invasive method. This study validates easier and less time-consuming techniques to evaluate the usefulness of detecting miRNA-21, miRNA-215 and miRNA-378 in the sera of colorectal cancer patients as new diagnostic tools. This study includes malignant (Colo Rectal Cancer patients, n= 64)) and healthy (n=27) groups. The studied groups were subjected to colonoscopic examination and estimation of miRNA-21, miRNA-215 and miRNA-378 in sera by RT-PCR. miRNA-21 showed the statistically significantly highest median fold change. miRNA-378 showed statistically significantly lower value (Both showed over-expression). miRNA-215 showed the statistically significantly lowest median fold change (It showed down-regulation). Overall the miRNA (21-215 and 378) appear to be promising method of detecting CRC and evaluating its stages.

Keywords: colorectal cancer, miRNA-21, miRNA-215, miRNA-378

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Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

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Authors: See-Yuan Cheng, Kwang-Yhee Chin, Shuhaimi Mansor

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Rear-roof spoiler is commonly used for improving the aerodynamic performance of road vehicles. This study aims to investigate the effect of yaw angle on the effectiveness of strip-type rear-roof spoiler in providing lower drag and lift coefficients of a hatchback model. A computational fluid dynamics (CFD) method was used. The numerically obtained results were compared to the experimental data for validation of the CFD method. At increasing yaw angle, both the drag and lift coefficients of the model were to increase. In addition, the effectiveness of spoiler was deteriorated. These unfavorable effects were due to the formation of longitudinal vortices around the side edges of the model that had caused the surface pressure of the model to drop. Furthermore, there were significant crossflow structures developed behind the model at larger yaw angle, which were associated with the drop in the surface pressure of the rear section of the model and cause the drag coefficient to rise.

Keywords: Ahmed model, aerodynamics, spoiler, yaw angle

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Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: frame, grey wolf optimization algorithm, modal residual force, structural damage detection

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Authors: Mohamed Amine Zenasni, Bahia Meroufel, André Merlin, Said Benfarhi, Stéphane Molina, Béatrice George

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The introduction of nano-fillers into polymers field lead to the creation of the nano composites. This creation is starting up a new revolution into the world of materials. Nano composites are similar to traditional composite of a polymer blend and filler with at least one nano-scopic dimension. In our project, we worked with nano composites of biodegradable polymer: polycaprolactone, combined with nano-clay (Maghnite) and with different nano-organo-clays. These nano composites have been prepared by melt mixture method. The advantage of this polymer is its degradability and bio compatibility. A study of the relationship between development, micro structure and physico chemical properties of nano composites, clays modified with 3-aminopropyltriethoxysilane (APTES) and Hexadecyltriméthy ammonium bromide (CTAB) and untreated clays were made. Melt mixture method is most suitable methods to get a better dispersion named exfoliation.

Keywords: nanocomposite, biodegradable, polycaprolactone, maghnite, melt mixture, APTES, CTAB

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Authors: Rashmi Shahu

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This is a comparative study of the Organizational Role Stress among the private and government sector employees. There was no known similar kind of Organizational Role Stress study in the field area i.e. Nagpur city. Hence, in order to understand the ORS level pertaining to the government and private sector employees in various offices it was taken as the subject for this study. The Method used for this study was the incidental sampling method. The Organizational Role Scale containing 50 statements related to the ten different ORS areas was used for observations. All 60 participants were tested. The results of the study show that there was a significant difference in only one area of ORS i.e. Personal Inadequacy for the participants. The employees from the private sector showed higher Personal Inadequacy than the government employees. Rest of the ORS areas showed no significant difference meaning that the employees were well adjusted in the respective areas.

Keywords: organozational role stress, private sector, government sector, personal inadequacy

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Authors: Anvar Atayev, Karl Steinborn, Aleksander Lovric, Saif Al-Ibadi, Jorg Fliege

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In this paper, we present results obtained from optimising the aerodynamic performance of aerostructures in external ow. The optimisation method used was developed to efficiently handle multi-variable problems with numerous black-box objective functions and constraints. To demonstrate these capabilities, a series of CFD problems were considered; (1) a two-dimensional NACA aerofoil with three variables, (2) a two-dimensional morphing aerofoil with 17 variables, and (3) a three-dimensional morphing aeroplane tail with 33 variables. The objective functions considered were related to combinations of the mean aerodynamic coefficients, as well as their relative variations/oscillations. It was observed that for each CFD problem, an improved objective value was found. Notably, the scale-up in variables for the latter problems did not greatly hinder optimisation performance. This makes the method promising for scaled-up CFD problems, which require considerable computational resources.

Keywords: computational fluid dynamics, optimisation algorithms, aerodynamic design, engineering design

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Authors: Abbas Moradi, Mohsen Safajoy, Reza Yazdanparast

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Analysis of blade-disc dovetail joints is one of the biggest challenges facing designers of aero-engines. To avoid comparatively expensive experimental full-scale tests, numerical methods can be used to simulate loaded disc-blades assembly. Mortar method provides a powerful and flexible tool for solving frictional contact problems. In this study, 2D frictional contact in dovetail has been analysed based on the mortar algorithm. In order to model the friction, the classical law of coulomb and moving friction cone algorithm is applied. The solution is then obtained by solving the resulting set of non-linear equations using an efficient numerical algorithm based on Newton–Raphson Method. The numerical results show that this approach has better convergence rate and accuracy than other proposed numerical methods.

Keywords: computational contact mechanics, dovetail joints, nonlinear FEM, mortar approach

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Authors: Manendra Singh Parihar, Sandip Ghosh Chowdhury

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Austenitic stainless steels are widely used and give a good combination of properties. When this steel is plastically deformed, a phase transformation of the metastable Face Centred Cubic Austenite to the stable Body Centred Cubic (α’) or to the Hexagonal close packed (ԑ) martensite may occur, leading to the enhancement in the mechanical properties like strength. The work was based on variant selection and corresponding texture analysis for the strain induced martensitic transformation during deformation of the parent austenite FCC phase to form the product HCP and the BCC martensite phases separately, obeying their respective orientation relationships. The automated method for reconstruction of the parent phase orientation using the EBSD data of the product phase orientation is done using the MATLAB and TSL-OIM software. The method of triplets was used which involves the formation of a triplet of neighboring product grains having a common variant and linking them using a misorientation-based criterion. This led to the proper reconstruction of the pre-transformation phase orientation data and thus to its microstructure and texture. The computational speed of current method is better compared to the previously used methods of reconstruction. The reconstruction of austenite from ԑ and α’ martensite was carried out for multiple samples and their IPF images, pole figures, inverse pole figures and ODFs were compared. Similar type of results was observed for all samples. The comparison gives the idea for estimating the correct sequence of the transformation i.e. γ → ε → α’ or γ → α’, during deformation of AISI 304 austenitic stainless steel.

Keywords: variant selection, reconstruction, EBSD, austenitic stainless steel, martensitic transformation

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Authors: Mehul Srivastava, Sharma Tushar Ravikant, Mridul Krishn Mishra

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In structural design, the evaluation of safety and probability failure of structure is of significant importance, mainly when the variables are random. On real structures, structural reliability can be evaluated obtaining an implicit limit state function. The structural reliability limit state function is obtained depending upon the statistically independent variables. In the analysis of reliability, we considered the statistically independent random variables to be the load intensity applied and the depth or height of the beam member considered. There are many approaches for structural reliability problems. In this paper Extreme Learning Machine technique and First Order Second Moment Method is used to determine the reliability indices for the same set of variables. The reliability index obtained using ELM is compared with the reliability index obtained using FOSM. Higher the reliability index, more feasible is the method to determine the reliability.

Keywords: reliability, reliability index, statistically independent, extreme learning machine

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Authors: Ahmad Odeh

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Researchers are currently more concerned about the calculations of energy at the operational stage, mainly due to its larger environmental impact, but the fact remains, embodied energies represent a substantial contributor unaccounted for in the overall energy computation method. The calculation of materials’ embodied energy during the construction stage is complicated. This is due to the various factors involved. The equipment used, fuel needed, and electricity required for each type of materials varies with location and thus the embodied energy will differ for each project. Moreover, the method used in manufacturing, transporting and putting in place will have significant influence on the materials’ embodied energy. This anomaly has made it difficult to calculate or even bench mark the usage of such energies. This paper presents a model aimed at calculating embodied energies based on such variabilities. It presents a systematic approach that uses an efficient method of calculation to provide a new insight for the selection of construction materials. The model is developed in a BIM environment. The quantification of materials’ energy is determined over the three main stages of their lifecycle: manufacturing, transporting and placing. The model uses three major databases each of which contains set of the construction materials that are most commonly used in building projects. The first dataset holds information about the energy required to manufacture any type of materials, the second includes information about the energy required for transporting the materials while the third stores information about the energy required by machinery to place the materials in their intended locations. Through geospatial data analysis, the model automatically calculates the distances between the suppliers and construction sites and then uses dataset information for energy computations. The computational sum of all the energies is automatically calculated and then the model provides designers with a list of usable equipment along with the associated embodied energies.

Keywords: BIM, lifecycle energy assessment, building automation, energy conservation

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Authors: Inkeri Jääskeläinen

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The purpose of this study is to shed light on what is it like to study in apprenticeship training using Finnish as second language. This study examines the stories and experiences of apprenticeship students learning and studying Finnish as part of their vocational studies. Also, this pilot study examines the effects of learning to pronounce Finnish through body motions and gestures. Many foreign students choose apprenticeships and start vocational training too early, while their language skills in Finnish are still very weak. Both duties at work and school assignments require reasonably good general language skills (B1.1) and, especially at work, language skills are also a safety issue. At work students should be able to simultaneously learn Finnish and do vocational studies in a noisy, demanding, and stressing environment. Learning and understanding new things is very challenging under these circumstances and sometimes students get exhausted and experience a lot of stress - which makes learning even more difficult. Students are different from each other and so are their ways to learn. Thereafter, one of the most important features of apprenticeship training and second language learning is good understanding of adult learners and their needs. Kinaesthetic methods are an effective way to support adult students’ cognitive skills and make learning more relaxing and fun. Empirical findings show that language learning can indeed be supported physical ways, by body motions and gestures. The method used here, named TFFL (Touch and Feel Foreign Languages), was designed to support adult language learning, to correct or prevent language fossilization and to help the student to manage emotions. Finnish is considered as a difficult language to learn, mostly because it is so different from nearly all other languages. Many learners complain that they are lost or confused and there is a need to find a way to simultaneously learn the language and to handle negative emotion which come from Finnish language and the learning process itself. Due to the nature of Finnish language good pronunciation skills are needed just to understand the way the language work. Movements (body movements etc.) are a natural part of many cultures but not Finnish – In Finland students have traditionally been expected to stay still and that is not a natural way for many foreign students. However, kinaesthetic TFFL method proved out to be a useful way to help some L2 students to feel phonemes, rhythm and intonation, to improve their Finnish and, thereby, also to successfully complete their vocational studies.

Keywords: Finnish, fossilization, interference, kinaesthetic method

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Authors: Khen Cohen, Daniel Yankelevich, David Mendlovic, Dan Raviv

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We present a 3D stereo system for high-resolution sensing in both the spatial and the temporal domains by combining a frame-based camera and an event-based camera. We establish a method to merge both devices into one unite system and introduce a calibration process, followed by a correspondence technique and interpolation algorithm for 3D reconstruction. We further provide quantitative analysis about our system in terms of depth resolution and additional parameter analysis. We show experimentally how our system performs temporal super-resolution up to effectively 1ms and can detect fast-moving objects and human micro-movements that can be used for micro-expression analysis. We also demonstrate how our method can extract colored events for an event-based camera without any degradation in the spatial resolution, compared to a colored filter array.

Keywords: DVS-CIS stereo vision, micro-movements, temporal super-resolution, 3D reconstruction

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Authors: Mesfin Nigussie Ibido

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The study is designed to explore the effects of land certification in securing women’s land rights of two rural villages in Robe district at Arsi Zone of Oromia regional state. The land is very critical assets for human life survival and the backbone for rural women livelihood. Equal access and control power to the land have given a chance for rural women to participate in different economic activities and improve their bargaining ability for decision making on their rights. Unfortunately, women were discriminated and marginalized from access and control of land for centuries through customary practices. However, in many countries, legal reform is used as a powerful tool for eliminating discriminatory provisions in property rights. Among other equity and efficiency concerns, the land certification program in Ethiopia attempts to address gender bias concerns of the current land-tenure system. The existed rural land policy was recognizing a women land rights and benefited by strengthened wives awareness of their land rights and contribute to the strong involvement of wives in decision making. However, harmful practices and policy implementation problems still against women do not fully exercise a provision of land rights in a different area of the country. Thus, this study is carried out to examine the effect of land certification in securing women’s land rights by eliminating the discriminatory nature of cultural abuses of study areas. Probability and non-probability sampling types were used, and the sample size was determined by using the sampling distribution of the proportion method. Systematic random sampling method was applied by taking the nth element of the sample frame. Both quantitative and qualitative research methods were applied, and survey respondents of 192 households were conducted and administering questionnaires in the quantitative method. The qualitative method was applied by interviews with focus group discussions with rural women, case stories, Village, and relevant district offices. Triangulation method was applied in data collection, data presentation and in the analysis of findings. Study finding revealed that the existence of land certification is affected by rural women positively by advancing their land rights, but still, some women are challenged by unsolved problems in the study areas. The study forwards recommendation on the existed problems or gaps to ensure women’s equal access to and control over land in the study areas.

Keywords: decision making, effects, land certification, land right, tenure security

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Authors: M. A. García, J. Vinolas, A. Hernando

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Steel is nowadays one of the most important structural materials because of its outstanding mechanical properties. Therefore, in order to look for a sustainable economic model and to optimize the use of extensive resources, new methods to monitor and prevent failure of steel-based facilities are required. The classical mechanical tests, as for instance building tasting, are invasive and destructive. Moreover, for facilities where the steel element is embedded, (as reinforced concrete) these techniques are directly non applicable. Hence, non-invasive monitoring techniques to prevent failure, without altering the structural properties of the elements are required. Among them, electromagnetic methods are particularly suitable for non-invasive inspection of the mechanical state of steel-based elements. The magnetoelastic coupling effects induce a modification of the electromagnetic properties of an element upon applied stress. Since most steels are ferromagnetic because of their large Fe content, it is possible to inspect their structure and state in a non-invasive way. We present here a distinct electromagnetic method for contactless evaluation of internal stress in steel-based elements. In particular, this method relies on measuring the magnetic induction between two coils with the steel specimen in between them. We found that the alteration of electromagnetic properties of the steel specimen induced by applied stress-induced changes in the induction allowed us to detect stress well below half of the elastic limit of the material. Hence, it represents an outstanding non-invasive method to prevent failure in steel-based facilities. We here describe the theoretical model, present experimental results to validate it and finally we show a practical application for detection of stress and inhomogeneities in train railways.

Keywords: magnetoelastic, magnetic induction, mechanical stress, steel

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

Abstract:

Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Ana-Katarina Nikich

Abstract:

Background: The kinesiotaping method is often used in physiotherapy and rehabilitation. The purpose of this study was to evaluate the effectiveness of taping in the rehabilitation process of patients. Materials and methods: The study involved 90 male and female patients (the average age was 40-50 years) with various conditions requiring rehabilitation, such as injuries of the musculoskeletal system, sports injuries and other ailments. All patients were divided into two groups: experimental (n=40) and control (n=50). Both groups received 20 days of standard rehabilitation. In the experimental group, kinesiotaping methods were used, taking into account the individual characteristics of each patient. The control group performed regular exercises and physical therapy, but without using kinesiotape. During the study, physical parameters were monitored, interviews were conducted and the conditions of patients from both groups were compared. Results and discussion: The use of the kinesiotaping method in the rehabilitation process led to a significant improvement in physical parameters and pain reduction in patients. Significant improvement (p <0.005) was observed in all evaluated parameters among the patients of the experimental group. The control group also showed sufficient improvement (p <0.005), but the percentage of the experimental group was higher. As a result of the observation, the patients of the experimental group showed faster and more complete rehabilitation compared to the control group. The use of the kinesiotaping method allows to reduce the load on the damaged areas, improve blood circulation and lymphatic drainage, as well as increase stability and coordination of movements. Conclusions: Kinesiotaping as one of the modern therapeutic methods has shown its effectiveness in the rehabilitation process, contributing to the optimal recovery of patients with various conditions requiring rehabilitation. The use of tapes should be included in a comprehensive rehabilitation program to achieve the best results and reduce recovery time.

Keywords: kinesiotaping, rehabilitation, therapy, pain

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Authors: Amirreza Kosari, Hossein Maghsoudi, Malahat Givar

Abstract:

In this study, the three-dimensional optimal path planning of a flying robot for Terrain Following / Terrain Avoidance (TF/TA) purposes using Direct Collocation has been investigated. To this purpose, firstly, the appropriate equations of motion representing the flying robot translational movement have been described. The three-dimensional optimal path planning of the flying vehicle in terrain following/terrain avoidance maneuver is formulated as an optimal control problem. The terrain profile, as the main allowable height constraint has been modeled using Fractal Generation Method. The resulting optimal control problem is discretized by applying Direct Collocation numerical technique, and then transformed into a Nonlinear Programming Problem (NLP). The efficacy of the proposed method is demonstrated by extensive simulations, and in particular, it is verified that this approach could produce a solution satisfying almost all performance and environmental constraints encountering a low-level flying maneuver

Keywords: path planning, terrain following, optimal control, nonlinear programming

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Authors: Jing Ma, Guotong Qin

Abstract:

We reported electro-confinement desalination (ECMD), a desalination method combining electric field effects and confinement effects using nanoporous carbon membranes as electrode. A carbon membrane with average pore size of 8.3 nm was prepared by organic sol-gel method. The precursor of support was prepared by curing porous phenol resin tube. Resorcinol-formaldehyde sol was coated on porous tubular resin support. The membrane was obtained by carbonisation of coated support. A well-combined top layer with the thickness of 35 μm was supported by macroporous support. Measurements of molecular weight cut-off using polyethylene glycol showed the average pore size of 8.3 nm. High salt rejection can be achieved because the water molecules need not overcome high energy barriers in confined space, while huge inherent dehydration energy was required for hydrated ions to enter the nanochannels. Additionally, carbon membrane with additional electric field can be used as an integrated membrane electrode combining the effects of confinement and electric potential gradient. Such membrane electrode can repel co-ions and attract counter-ions using pressure as the driving force for mass transport. When the carbon membrane was set as cathode, the rejection of SO₄²⁻ was 94.89%, while the removal of Na⁺ was less than 20%. We set carbon membrane as anode chamber to treat the effluent water from the cathode chamber. The rejection of SO₄²⁻ and Na⁺ reached to 100% and 88.86%, respectively. ECMD will be a promising energy efficient method for salt rejection.

Keywords: nanoporous carbon membrane, confined effect, electric field, desalination, membrane reactor

Procedia PDF Downloads 125

Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

Procedia PDF Downloads 395