Search results for: object-based image analysis

Authors: Reji Thankachan, Varsha PS

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Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

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Authors: K. Caban-Piaskowska

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The aim of the article is to show how the role of a designer has changed, from the point of view of human resources management and thanks to the increased importance of design management, and is to present how a rehabilitation product, through technology approach to designing, becomes a universal product. Designing for the disabled is a very undiscovered area on the pattern-designing market, most often because it is associated with devices which support rehabilitation. In consequence, it means that the realizations have a limited group of receivers and are not that attractive for designers. The relation between using modern design in building rehabilitation devices and increasing the efficiency of treatment and physiotherapy. Using modern technology can have marketing significance. Rehabilitation products designed and produced in a modern way makes an impression that experts and professionals are involved in the lives of the user – patient. In order to illustrate the problem presented above i.e. Creating a rehabilitation product as an example of design management, the case study method was used in the research. The analysis of the case was created on the basis of an interview conducted by the author with a designer who took part in meetings with people who use rehabilitation and their physiotherapists, and created universal products in Poland in the years of 2012 to 2017. Usually, engineers and constructors deal with creating products which remind us of old torture devices, however, they are indestructible in construction. Such image of those products for the disabled clearly indicates that it is a wonderful niche for designers and emphasizes the need to make those products more attractive and innovative. Products for the disabled cannot be limited to rehabilitation equipment only e.g. wheelchairs or standing frames. Introducing the idea of universal designing can significantly broaden the circle of pattern-designing receivers – everyday-use items – with the disabled people. Fulfilling these criteria will decide about the advantage on the competitive market. It is possible due to the usage of the design management concept in the functioning of an organization. Using modern technology and materials in the production of equipment, and changing the role of a designer broadening the circle of receivers by designing a wide use process which makes it possible to use the product by people with various needs. What is more, introducing rehabilitation functions in everyday-use items can also become an innovative accent in designing. In the reality of the market, each group of users can and should be treated as a problem and a realization task.

Keywords: design management, innovation, rehabilitation product, universal product

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Authors: Toufik Bensana, Medkour Mihoub, Slimane Mekhilef

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally nonstationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA), and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, rolling element bearing, local mean decomposition, condition monitoring

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis

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Authors: Jakyoung Kim, Sungwook Jang

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The purpose of this study is to examine the research trends of life-long education for people with disabilities using a keyword network analysis. For this purpose, 151 papers were selected from 594 papers retrieved using keywords such as 'people with disabilities' and 'life-long education' in the Korean Education and Research Information Service. The Keyword network analysis was constructed by extracting and coding the keyword used in the title of the selected papers. The frequency of the extracted keywords, the centrality of degree, and betweenness was analyzed by the keyword network. The results of the keyword network analysis are as follows. First, the main keywords that appeared frequently in the study of life-long education for people with disabilities were 'people with disabilities', 'life-long education', 'developmental disabilities', 'current situations', 'development'. The research trends of life-long education for people with disabilities are focused on the current status of the life-long education and the program development. Second, the keyword network analysis and visualization showed that the keywords with high frequency of occurrences also generally have high degree centrality and betweenness centrality. In terms of the keyword network diagram, it was confirmed that research trends of life-long education for people with disabilities are centered on six prominent keywords. Based on these results, it was discussed that life-long education for people with disabilities in the future needs to expand the subjects and the supporting areas of the life-long education, and the research needs to be further expanded into more detailed and specific areas. 

Keywords: life-long education, people with disabilities, research trends, keyword network analysis

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Authors: Minh Dong Le, Viet Dung Nguyen, Do Huu Viet, Nguyen Huu Tu

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In this paper, we present a new method for circumscribed masses detection in mammograms. Our method is evaluated on 23 mammographic images of circumscribed masses and 20 normal mammograms from public Mini-MIAS database. The method is quite sanguine with sensitivity (SE) of 95% with only about 1 false positive per image (FPpI). To achieve above results we carry out a progression following: Firstly, the input images are preprocessed with the aim to enhance key information of circumscribed masses; Next, we calculate and evaluate statistically basic features of abnormal regions on training database; Then, mammograms on testing database are divided into equal blocks which calculated corresponding features. Finally, using priority order of basic features to classify blocks as an abnormal or normal regions.

Keywords: mammograms, circumscribed masses, evaluated statistically, priority order of basic features

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Utkan Mutman, Cihan Dirlik

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Kocaeli/TURKEY district in which wastewater held in a chosen field increased property has made piling in order to improve the ground under the aeration basin. In this study, the degree of improvement the ground after bored piling held in the field were investigated. In this context, improving the ground before and after the investigation was carried out and that the solution values obtained by the finite element method analysis using Plaxis program have been made. The diffuses in the aeration basin whose treatment is to aide is influenced with and without geogrid on the ground. On the ground been improved, for the purpose of control of manufactured bored piles, pile continuity, and pile load tests were made. Taking into consideration both the data in the field as well as dynamic loads in the aeration basic, an analysis was made on Plaxis program and compared the data obtained from the analysis result and data obtained in the field.

Keywords: geogrid, bored pile, soil improvement, plaxis

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Authors: Reskino Resky

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This research purposes to create a model to detecting financial statement fraud. This research examines the variable of fraud triangle and auditor industry specialization with financial statement fraud. This research used sample of company which is listed in Indonesian Stock Exchange that have sanctions and cases by Financial Services Authority in 2011-2013. The number of company that were became in this research were 30 fraud company and 30 non-fraud company. The method of determining the sample is by using purposive sampling method with judgement sampling, while the data processing methods used by researcher are mann-whitney u and discriminants analysis. This research have two from five variable that can be process with discriminant analysis. The result shows the financial targets can be detect financial statement fraud, while financial stability can’t be detect financial statement fraud.

Keywords: fraud triangle analysis, financial targets, financial stability, auditor industry specialization, financial statement fraud

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Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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Authors: Tyler Gill, Sophia Daniels

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The paper examines how accessing the spatial-temporal constrains of data will help inform policymakers and law enforcement officials. The authors utilize Chicago crime data from 2006-2016 to demonstrate how the Emerging Hot Spot Tool is an ideal hot spot clustering approach to analyze crime data. Traditional approaches include density maps or creating a spatial weights matrix to include the spatial-temporal constrains. This new approach utilizes a space-time implementation of the Getis-Ord Gi* statistic to visualize the data more quickly to make better decisions. The research will help complement socio-cultural research to find key patterns to help frame future policies and evaluate the implementation of prior strategies. Through this analysis, homicide trends and patterns are found more effectively and recommendations for use by non-traditional users of GIS are offered for real life implementation.

Keywords: crime mapping, emerging hot spot analysis, Getis-Ord Gi*, spatial-temporal analysis

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Authors: Adel Ali Elshaibani

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Risk management indicators augment the reporting infrastructure, particularly for the board and senior management, to identify, monitor, and manage risks. This enhancement facilitates improved decision-making throughout the banking organization. Decision tree analysis is a tool that visually outlines potential outcomes, costs, and consequences of complex decisions. It is particularly beneficial for analyzing quantitative data and making decisions based on numerical values. By calculating the expected value of each outcome, decision tree analysis can help assess the best course of action. In the context of banking, decision tree analysis can assist lenders in evaluating a customer’s creditworthiness, thereby preventing losses. However, applying these tools in developing countries may face several limitations, such as data availability, lack of technological infrastructure and resources, lack of skilled professionals, cultural factors, and cost. Moreover, decision trees can create overly complex models that do not generalize well to new data, known as overfitting. They can also be sensitive to small changes in the data, which can result in different tree structures and can become computationally expensive when dealing with large datasets. In conclusion, while risk management indicators and decision tree analysis are beneficial for decision-making in banks, their effectiveness is contingent upon how they are implemented and utilized by the board of directors, especially in the context of developing countries. It’s important to consider these limitations when planning to implement these tools in developing countries.

Keywords: risk management indicators, decision tree analysis, developing countries, board of directors, bank performance, risk management strategy, banking institutions

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

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Authors: M. Vivodík, Ž. Balážová, Z. Gálová

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The aim of this work was to detect genetic variability among the set of 40 castor genotypes using 8 RAPD markers. Amplification of genomic DNA of 40 genotypes, using RAPD analysis, yielded in 66 fragments, with an average of 8.25 polymorphic fragments per primer. Number of amplified fragments ranged from 3 to 13, with the size of amplicons ranging from 100 to 1200 bp. Values of the polymorphic information content (PIC) value ranged from 0.556 to 0.895 with an average of 0.784 and diversity index (DI) value ranged from 0.621 to 0.896 with an average of 0.798. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared and analyzed genotypes were grouped into two main clusters and only two genotypes could not be distinguished. Knowledge on the genetic diversity of castor can be used for future breeding programs for increased oil production for industrial uses.

Keywords: dendrogram, polymorphism, RAPD technique, Ricinus communis L.

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Authors: H. Mashhady, H. A. Manzoori, M. Doosti, M. Fatollahi

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This study reports a descriptive research in the form of a genre analysis of postgraduates' theses and dissertations at three Iranian universities, including Ferdowsi, Tehran, and Tarbiat Moddares universities. The researchers sought to depict the generic structure of “statement of the problem” section of PhD dissertations and MA theses. Moreover, researchers desired to find any probable variety based on the year the dissertations belonged, to see weather genre-consciousness developed among Iranian postgraduates. To obtain data, “statement of the problem” section of 90 Ph.D. dissertations and MA theses from 2001 to 2013 in Teaching English as a Foreign Language (TEFL) at above-mentioned universities was selected. Frequency counts was employed for the quantitative method of data analysis, while genre analysis was used as the qualitative method. Inter-rater reliability was found to be about 0.93. Results revealed that students in different degrees at each of these universities used various generic structures for writing “statement of the problem”. Moreover, comparison of different time periods (2001-2006, and 2007-2013) revealed that postgraduates in the second time period, regardless of their degree and university, employed more similar generic structures which can be optimistically attributed to a general raise in genre awareness.

Keywords: genre, genre analysis, Ph.D. and MA dissertations, statement of the problem, generic structure

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Authors: Dereje Moges Azbite

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Laboratory analysis of igneous rocks is performed with the help of the main oxide plots. The lithology of the two wells was identified using the main oxides obtained using the XRF method. Twenty-four (24) cutting samples with different degrees of alteration were analyzed to determine and identify the rock types by plotting these well samples on special diagrams and correlating with the regional rocks. The results for the analysis of the main oxides and trace elements of 24 samples are presented. Alteration analysis in the two well samples was conducted for 21 samples from two wells for identifying clay minerals. Bulk sample analysis indicated quartz, illite & micas, calcite, cristobalite, smectite, pyrite, epidote, alunite, chlorite, wairakite, diaspore and kaolin minerals present in both wells. Hydrothermal clay minerals such as illite, chlorite, smectite and kaoline minerals were identified in both wells by X-ray diffraction.

Keywords: auto geothermal field, igneous rocks, major oxides, tracer elements, XRF, XRD, alteration minerals

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Authors: Yi Wang, Greg Hearn, Terry Flew

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In order to understand how cultural innovation occurs, this paper explores the interaction in Shenzhen of China between universities, creative industries, and government in creative economic using the Triple Helix framework. During the past two decades, Triple Helix has been recognized as a new theory of innovation to inform and guide policy-making in national and regional development. Universities and governments around the world, especially in developing countries, have taken actions to strengthen connections with creative industries to develop regional economies. To date research based on the Triple Helix model has focused primarily on Science and Technology collaborations, largely ignoring other fields. Hence, there is an opportunity for work to be done in seeking to better understand how the Triple Helix framework might apply in the field of creative industries and what knowledge might be gleaned from such an undertaking. Since the late 1990s, the concept of ‘creative industries’ has been introduced as policy and academic discourse. The development of creative industries policy by city agencies has improved city wealth creation and economic capital. It claims to generate a ‘new economy’ of enterprise dynamics and activities for urban renewal through the arts and digital media, via knowledge transfer in knowledge-based economies. Creative industries also involve commercial inputs to the creative economy, to dynamically reshape the city into an innovative culture. In particular, this paper will concentrate on creative spaces (incubators, digital tech parks, maker spaces, art hubs) where academic, industry and government interact. China has sought to enhance the brand of their manufacturing industry in cultural policy. It aims to transfer the image of ‘Made in China’ to ‘Created in China’ as well as to give Chinese brands more international competitiveness in a global economy. Shenzhen is a notable example in China as an international knowledge-based city following this path. In 2009, the Shenzhen Municipal Government proposed the city slogan ‘Build a Leading Cultural City”’ to show the ambition of government’s strong will to develop Shenzhen’s cultural capacity and creativity. The vision of Shenzhen is to become a cultural innovation center, a regional cultural center and an international cultural city. However, there has been a lack of attention to the triple helix interactions in the creative industries in China. In particular, there is limited knowledge about how interactions in creative spaces co-location within triple helix networks significantly influence city based innovation. That is, the roles of participating institutions need to be better understood. Thus, this paper discusses the interplay between university, creative industries and government in Shenzhen. Secondary analysis and documentary analysis will be used as methods in an effort to practically ground and illustrate this theoretical framework. Furthermore, this paper explores how are creative spaces being used to implement Triple Helix in creative industries. In particular, the new combination of resources generated from the synthesized consolidation and interactions through the institutions. This study will thus provide an innovative lens to understand the components, relationships and functions that exist within creative spaces by applying Triple Helix framework to the creative industries.

Keywords: cultural policy, creative industries, creative city, triple Helix

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

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Authors: Tarek M. Alguhane, Ayman H. Khalil, Nour M. Fayed, Ayman M. Ismail

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Early, pre-code, reinforced concrete structures present undetermined resistance to earthquakes. This situation is particularly unacceptable in the case of essential structures, such as healthcare structures and pilgrims' houses. Among these, existing old RC building in Madinah is seismically evaluated with and without infill wall and their dynamic characteristics are compared with measured values in the field using ambient vibration measurements (AVM). After, updating the mathematical models for this building with the experimental results, three dimensional pushover analysis (Nonlinear static analysis) was carried out using SAP 2000 software incorporating inelastic material properties for concrete, infill and steel. The purpose of this analysis is to evaluate the expected performance of structural systems by estimating, strength and deformation demands in design, and comparing these demands to available capacities at the performance levels of interest. The results are summarized and discussed.

Keywords: seismic assessment, pushover analysis ambient vibration, modal update

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Authors: Tahir Saleem, Mohammad Usman, Nadeem Khan

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GPS signals are used for navigation and positioning purposes by a diverse set of users. However, this project intends to utilize the reflected GPS L5 signals for location of target in a region of interest by generating an image that highlights the positions of targets in the area of interest. The principle of bi-static radar is used to detect the targets or any movement or changes. The idea is confirmed by the results obtained during MATLAB simulations. A matched filter based technique is employed in the signal processing to improve the system resolution. The simulation is carried out under different conditions with moving receiver and targets. Noise and attenuation is also induced and atmospheric conditions that affect the direct and reflected GPS signals have been simulated to generate a more practical scenario. A realistic GPS L5 signal has been simulated, the simulation results verify that the detection and imaging of targets is possible by employing reflected GPS using L5 signals and matched filter processing technique with acceptable spatial resolution.

Keywords: GPS, L5 Signal, SAR, spatial resolution

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Authors: Amir Alani, Mojtaba Mahmoodian, Anna Romanova, Asaad Faramarzi

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Pipelines are extensively used engineering structures which convey fluid from one place to another. Most of the time, pipelines are placed underground and are encumbered by soil weight and traffic loads. Corrosion of pipe material is the most common form of pipeline deterioration and should be considered in both the strength and serviceability analysis of pipes. The study in this research focuses on concrete pipes in sewage systems (concrete sewers). This research firstly investigates how to involve the effect of corrosion as a time dependent process of deterioration in the structural and failure analysis of this type of pipe. Then three probabilistic time dependent reliability analysis methods including the first passage probability theory, the gamma distributed degradation model and the Monte Carlo simulation technique are discussed and developed. Sensitivity analysis indexes which can be used to identify the most important parameters that affect pipe failure are also discussed. The reliability analysis methods developed in this paper contribute as rational tools for decision makers with regard to the strengthening and rehabilitation of existing pipelines. The results can be used to obtain a cost-effective strategy for the management of the sewer system.

Keywords: reliability analysis, service life prediction, Monte Carlo simulation method, first passage probability theory, gamma distributed degradation model

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Authors: Deniz Karagöz

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This study is attempt to comprehend the relationship between the spatial characteristics of cultural structure, activities and the tourism demand in Turkey. The analysis divided into four parts. The first part consisted of a cultural structure and cultural activity (CSCA) index provided by principal component analysis. The analysis determined four distinct dimensions, namely, cultural activity/structure, accessing culture, consumption, and cultural management. The exploratory spatial data analysis employed to determine the spatial models of cultural structure and cultural activities in 81 provinces in Turkey. Global Moran I indices is used to ascertain the cultural activities and the structural clusters. Finally, the relationship between the cultural activities/cultural structure and tourism demand was analyzed. The raw/original data of the study official databases. The data on the cultural structure and activities gathered from the Turkish Statistical Institute and the data related to the tourism demand was provided by the Republic of Turkey Ministry of Culture and Tourism.

Keywords: cultural activities, cultural structure, spatial characteristics, tourism demand, Turkey

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Authors: Seyed Abolhassan Naeini, Azam Kouhpeyma

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Reduction of water level at which a slope is submerged with it is called drawdown. Draw down can took place rapidly or slowly and in both situations, it can affect slope stability. Using coupled analysis (seepage and stability analysis) causes more accurate results. In this study, the stability of homogeneous embankment is investigated numerically. Slope safety factor changes due to changes in three factors of height, slope and drawdown rate have been investigated and compared. It was found that with increasing height and slope, the safety factor decreases, and with increasing the discharge rate, the safety factor increases.

Keywords: drawdown, slope stability, coupled seepage and stability analysis

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Authors: Naik Muhammad, Zahid Ullah, Dong-Ho Choi

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Submerged floating tunnel (SFT) is a new solution for the transportation infrastructure through sea straits, fjords, and inland waters, and can be a good alternative to long span suspension bridges. SFT is a massive cylindrical structure that floats at a certain depth below the water surface and subjected to extreme environmental conditions. The identification of dominant structural response of SFT becomes more important due to intended environmental conditions for the design of SFT. The time domain dynamic problem of SFT moored by vertical and inclined mooring cables/anchors is formulated. The dynamic time history analysis of SFT subjected to hydrodynamic and seismic excitations is performed. The SFT is modeled by finite element 3D beam, and the mooring cables are modeled by truss elements. Based on the dynamic time history analysis the displacements and internal forces of SFT were calculated. The response of SFT is presented for hydrodynamic and seismic excitations. The transverse internal forces of SFT were the maximum compared to vertical direction, for both hydrodynamic and seismic cases; this indicates that the cable system provides very small stiffness in transverse direction as compared to vertical direction of SFT.

Keywords: submerged floating tunnel, hydrodynamic analysis, time history analysis, seismic response

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Authors: S. Madhu, V. V. Subba Rao

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In the implementation of carbon nanotube reinforced polymer matrix composites in structural applications, deflection and stress analysis are important considerations. In the present study, a multi scale analysis of deflection and stress analysis of carbon nanotube (CNT) reinforced polymer composite plates is presented. A micromechanics model based on the Mori-Tanaka method is developed by introducing straight CNTs aligned in one direction. The effect of volume fraction and diameter of CNTs on plate deflection and the stresses are investigated using Classical Laminate Plate Theory (CLPT). The study is primarily conducted with the intention of observing the suitability of CNT reinforced polymer composite plates under static loading for structural applications.

Keywords: carbon nanotube, micromechanics, composite plate, multi-scale analysis, classical laminate plate theory

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Authors: Chadi Azoury, Assad Kallassy, Pierre Rahme

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In this paper, we consider the modal analysis of small frames. Firstly, we construct the 3D model using H8 elements and find the natural frequencies of the frame focusing our attention on the modes in the XY plane. Secondly, we construct the 2D model (plane stress model) using Q4 elements. We concluded that the results of both models are very close to each other’s. Then we formulate the stiffness matrix and the mass matrix of the 3-noded Timoshenko beam that is well suited for thick and short beams like in our case. Finally, we model the corners where the horizontal and vertical bar meet with a special matrix. The results of our new model (3-noded Timoshenko beam for the horizontal and vertical bars and a special element for the corners based on the Q4 elements) are very satisfying when performing the modal analysis.

Keywords: corner element, high-order Timoshenko beam, Guyan reduction, modal analysis of frames, rigid link, shear locking, and short beams

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Authors: A. B. M. Rezaul Islam, Ernur Karadogan

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Shape memory alloys (SMAs) are known for their shape memory effect and pseudoelasticity behavior. Their thermomechanical behaviors are modeled by numerous researchers using microscopic thermodynamic and macroscopic phenomenological point of view. Tanaka, Liang-Rogers and Ivshin-Pence models are some of the most popular SMA macroscopic phenomenological constitutive models. They describe SMA behavior in terms of stress, strain and temperature. These models involve material parameters and they have associated uncertainty present in them. At different operating temperatures, the uncertainty propagates to the output when the material is subjected to loading followed by unloading. The propagation of uncertainty while utilizing these models in real-life application can result in performance discrepancies or failure at extreme conditions. To resolve this, we used probabilistic approach to perform the sensitivity and uncertainty analysis of Tanaka, Liang-Rogers, and Ivshin-Pence models. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods have been used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. As per the results, it is evident that the models vary due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most significant parameters at several temperatures. This work highlights the sensitivity and uncertainty analysis results and shows comparison of them at different temperatures and loading conditions for all these models. The analysis presented will aid in designing engineering applications by eliminating the probability of model failure due to the uncertainty in the input parameters. Thus, it is recommended to have a proper understanding of sensitive parameters and the uncertainty propagation at several operating temperatures and loading conditions as per Tanaka, Liang-Rogers, and Ivshin-Pence model.

Keywords: constitutive models, FAST sensitivity analysis, sensitivity analysis, sobol, shape memory alloy, uncertainty analysis

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Authors: G. Scremin, I. Y. Suh, S. Doukas

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Spectators follow their favorite sports teams for different reasons. While some attend a sporting event simply for its entertainment value, others do so because of the personal sense of achievement and accomplishment their connection with a sports team creates. Moreover, the level of identity spectators feel toward their favorite sports team falls in a broad continuum. Some are mere spectators. For those spectators, their association to a sports team has little impact on their self-image. Others are die-hard fans who are proud of their association with their team and whose connection with that team is an important reflection of who they are. Several motives for sports consumption can be used to explain the level of spectator support in a variety of sports. Those motives can also be used to explain the variance in the identification, attachment, and loyalty spectators feel toward their favorite sports team. Motives for sports consumption can be used to discriminate the degree of identification spectators have with their favorite sports team. In this study, motives for sports consumption was used to discriminate the level of identity spectators feel toward their sports team. It was hypothesized that spectators with a strong level of team identity would report higher rates of interest in player, interest in sports, and interest in team than spectators with a low level of team identity. And spectators with a low level of team identity would report higher rates for entertainment value, bonding with friends or family, and wholesome environment. Football spectators in the United States and England were surveyed about their motives for football consumption and their level of identification with their favorite football team. To assess if the motives of sports fans differed by level of team identity and allegiance to an American or English football team, a Multivariate Analysis of Variance (MANOVA) under the General Linear Model (GLM) procedure found in SPSS was performed. The independent variables were level of team identity and allegiance to an American or English football team, and the dependent variables were the sport fan motives. A tripartite split (low, moderate, high) was used on a composite measure for team identity. Preliminary results show that effect of team identity is statistically significant (p < .001) for at least nine of the 17 motives for sports consumption assessed in this investigation. These results indicate that the motives of spectators with a strong level of team identity differ significantly from spectators with a low level of team identity. Those differences can be used to discriminate the degree of identification spectators have with their favorite sports team. Sports marketers can use these methods and results to develop identity profiles of spectators and create marketing strategies specifically designed to attract those spectators based on their unique motives for consumption and their level of team identification.

Keywords: fan identification, market segmentation of sports fans, motives for sports consumption, team identity

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Authors: N. Dumitru, S. Dumitru, C. Copilusi, N. Ploscaru

Abstract:

On this research, experimental analyses have been performed in order to determine the oil pump mechanism dynamics and stability from an oil unit mechanical structure. The experimental tests were focused on the vibrations which occur inside of the rod element during functionality of the oil pump unit. The oil pump mechanism dynamic parameters were measured and also determined through numerical computations. Entire research is based on the oil pump unit mechanical system virtual prototyping. For a complete analysis of the mechanism, the frequency dynamic response was identified, mainly for the mechanism driven element, based on two methods: processing and virtual simulations with MSC Adams aid and experimental analysis. In fact, through this research, a complete methodology is presented where numerical simulations of a mechanism with deformed elements are developed on a dynamic mode and these can be correlated with experimental tests.

Keywords: modal dynamic analysis, oil pump, vibrations, flexible elements, frequency response

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Authors: C. J. Rossouw, T. I. van Niekerk

Abstract:

The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

Procedia PDF Downloads 78