Search results for: structure prediction

Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Mia Françoise

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This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization.

Keywords: financial stocks, optimized asset allocation, prediction modelling, South Africa

Procedia PDF Downloads 73

Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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The river is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that need to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between the main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of the main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, CES software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel, and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth, velocity distribution

Procedia PDF Downloads 158

Authors: Zohreh Derikvand, Hadis Cheraghi, Azadeh Azadbakht, Vaclav Eigner, Michal Dusek

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Two new one and two dimensional metal organic coordination polymers of Cu(II), [Cu(3-nph)2(H2O)2pz]n (1) and Ag(I), {[Ag(3-nph)pz].H2O}n (2) with pyrazine (pz) and 3- nitrophthalic acid (3-nph) have been synthesized and characterized by elemental analysis, spectral (IR, UV-Vis), thermal (TG/DTG) analysis and single crystal X-ray diffraction. We used these compounds to preparation modified electrode with Au/Pt nanosparticles in order to investigation electrochemistry and electrocatalysis activities. The surface structure and composition of the sensor were characterized by scanning electron microscopy (SEM). The Ag(I) coordination polymer shows a 2D layer structure constructed from dinuclear silver (I) building blocks in which two crystallographically Ag+ ions are connected to each other by a covalent bond. The pyrazine ligands adopt μ2 bridging modes, linking the metal centers into a one and two -dimensional coordination framework in 1 and 2. The two AgI cations are surrounded by pyrazine and 3-nitrophthalate mono anions and indicate distorted tetrahedral geometry. In the crystal structures of Ag(I) complex there are non-classical hydrogen bonding arrangements, C–O•••π and π–π stacking interactions. In Cu(II) coordination polymer, the coordination geometry around Cu(II) atom is a distorted octahedron. Interestingly, the structural analysis illustrates that the strong and weak hydrogen bond accompanied with C–H•••π and C–O•••π stacking interactions assemble the crystal structure of 1 and 2 into fascinating 3D supramolecular architecture.

Keywords: 3-nithrophethalic acid, crystal structure, coordination polymer, electrocatalysis

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Authors: Asmaa M. Marzouk, Abdallah M. Elshaer

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Despite the well-recognized value of shopping as a revenue-generating resource, little effort was made to investigate what is the structure of tourists’ shopping behavior, which in turn, affect their travel experience. The purpose of this paper is to study the structure of tourists’ shopping process to better understand their shopping behavior by investigating factors that influence this activity other than hotels tyranny. This study specifically aims to propose a model incorporating those all variables. This empirical study investigates the shopping experience of international tourists using a questionnaire aimed to examine multinational samples selected from the tourist population visiting a specific destination in Egypt. This study highlights the various stakeholders that make tourists do shop independent of hotels. The results, therefore, demonstrate the relationship between the shopping process entities involved and configure the variables within the model in a way that provides a viable solution for visitors to avoid the tyranny of hotel facilities and amenities on the public markets.

Keywords: hotels’ amenities, shopping process, tourist behavior, tourist satisfaction

Procedia PDF Downloads 115

Authors: Lucie Novakova, Petr Homola, Vaclav Kafka

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Asymmetric incremental sheet forming (AISF) could significantly reduce costs incurred by the fabrication of complex industrial components with a minimal environmental impact. The AISF experiments were carried out on commercially pure titanium (Ti-Gr2), Timetal (15-3-3-3) alloy, and Ti-6Al-4V (Ti-Gr5) alloy. A special testing geometry was used to characterize the titanium alloys properties from the point of view of the forming zone and titanium structure effect. The structure and properties of the materials were assessed by means of metallographic analyses and microhardness measurements.The highest differences in the parameters assessed as a function of the sampling zone were observed in the case of alpha-phase Ti-Gr2at the expense of the most substantial sheet thinning occurrence. A springback causes a smaller stored deformation in Timetal (β alloy) resulting in less pronounced microstructure refinement and microhardness increase. Ti-6Al-4V alloy exhibited early failure due to its poor formability at ambient temperature.

Keywords: incremental forming, metallography, hardness, titanium alloys

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Authors: Qinghua Zhang, Yanhe Zhu, Xiang Zhao, Yeqin Yang, Hongwei Jing, Guoan Zhang, Jie Zhao

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This paper presents a wearable reconfigurable supernumerary robotic limb with differential actuated joints, which is lightweight, compact and comfortable for the wearers. Compared to the existing supernumerary robotic limbs which mostly adopted series structure with large movement space but poor carrying capacity, a prototype with the series-parallel configuration to better adapt to different task requirements has been developed in this design. To achieve a compact structure, two kinds of cable-driven mechanical structures based on guide pulleys and differential actuated joints were designed. Moreover, two different tension devices were also designed to ensure the reliability and accuracy of the cable-driven transmission. The proposed device also employed self-designed bearings which greatly simplified the structure and reduced the cost.

Keywords: cable-driven, differential actuated joints, reconfigurable, supernumerary robotic limb

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Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

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Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

Procedia PDF Downloads 118

Authors: Subzar Ahmad Bhat, Saraswati Setia, V. K.Sehgal

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During the past earthquakes, open ground storey buildings have performed poorly due to the soft storey defect. Indian Standard IS 1893:2002 allows analysis of open ground storey buildings without considering infill stiffness but with a multiplication factor 2.5 in compensation for the stiffness discontinuity. Therefore, the aim of this paper is to check the applicability of the multiplication factor of 2.5 and study behaviour of the structure after the application of the multiplication factor. For this purpose, study is performed on models considering infill stiffness using SAP 2000 (Version 14) by linear static analysis and response spectrum analysis. Total seven models are analysed and designed for the range of multiplication factor ranging from 1.25 to 2.5. The value of multiplication factor equal to 2.5 has been found on the higher side, resulting in increased dimension and percentage of reinforcement without significant enhancement beyond a certain multiplication factor. When the building with OGS is designed for values of MF higher than 1.25 considering infill stiffness soft storey effect shifts from ground storey to first storey. For the analysis of the OGS structure best way to analysis the structure is to analyse it as the frame with stiffness and strength of the infill taken into account. The provision of infill walls in the upper storeys enhances the performance of the structure in terms of displacement and storey drift controls.

Keywords: open ground storey, multiplication factor, IS 1893:2002 provisions, static analysis, response spectrum analysis, infill stiffness, equivalent strut

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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Authors: A. Shooshtari, A. R. Masoodi, S. Heyrani Moghaddam

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Free vibration analysis of a gabled frame with elastic support and semi-rigid connections is performed by using a program in OpenSees software. Natural frequencies and mode shape details of frame are obtained for two states, which are semi-rigid connections and elastic supports, separately. The members of this structure are analyzed as a prismatic nonlinear beam-column element in software. The mass of structure is considered as two equal lumped masses at the head of two columns in horizontal and vertical directions. Note that the degree of freedom, allocated to all nodes, is equal to three. Furthermore, the mode shapes of frame are achieved. Conclusively, the effects of connections and supports flexibility on the natural frequencies and mode shapes of structure are investigated.

Keywords: natural frequency, mode shape, gabled frame, semi-rigid connection, elastic support, OpenSees software

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Authors: Chaoyan Huang, Hongxia Zheng

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For deep space exploration and long duration interplanetary manned missions, protection of astronauts from cosmic radiation is an unavoidable problem. However, passive shielding can be little effective for protecting particles which energies are greater than 1GeV/nucleon. In this study, active magnetic protection method is adopted. Taking into account the structure and size of the end-cap, eight shielding magnetic field configurations are designed based on the Hoffman configuration. The shielding effect of shielding magnetic field structure, intensity B and thickness L on H particles with 2GeV energy is compared by test particle simulation. The result shows that the shielding effect is better with the linear type magnetic field structure in the end-cap region. Furthermore, two magnetic field configurations with better shielding effect are investigated through H and He galactic cosmic spectra. And the shielding effect of the linear type configuration adopted in the barrel and end-cap regions is best.

Keywords: galactic cosmic rays, active protection, shielding magnetic field configuration, shielding effect

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Authors: Sima Hassankhali, Ildar Sadeqi

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In the theory of Pareto efficient points, the existence of a bounded base for a cone K of a normed space X is so important. In this article, we study the geometric structure of a nonzero closed convex cone K with a bounded base. For this aim, we study the structure of the polar cone K# of K. Furthermore, we obtain a necessary and sufficient condition for a nonempty closed convex set C so that its recession cone C∞ has a bounded base.

Keywords: solid cones, recession cones, polar cones, bounded base

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Authors: Murad Ali, Anderson Konan Seny Kan, Khalid A. Maimani

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Based on the theory of organizational design and the theory of knowledge, this study uses complexity theory to explain and better understand the causal impacts of various patterns of organizational structural factors stimulating absorptive capacity (ACAP). Organizational structure can be thought of as heterogeneous configurations where various components are often intertwined. This study argues that impact of the traditional variables which define a firm’s organizational structure (centralization, formalization, complexity and integration) on ACAP is better understood in terms of set-theoretic relations rather than correlations. This study uses a data sample of 347 from a multiple industrial sector in South Korea. The results from PLS-SEM support all the hypothetical relationships among the variables. However, fsQCA results suggest the possible configurations of centralization, formalization, complexity, integration, age, size, industry and revenue factors that contribute to high level of ACAP. The results from fsQCA demonstrate the usefulness of configurational approaches in helping understand equifinality in the field of knowledge management. A recent fsQCA procedure based on a modeling subsample and holdout subsample is use in this study to assess the predictive validity of the model under investigation. The same type predictive analysis is also made through PLS-SEM. These analyses reveal a good relevance of causal solutions leading to high level of ACAP. In overall, the results obtained from combining PLS-SEM and fsQCA are very insightful. In particular, they could help managers to link internal organizational structural with ACAP. In other words, managers may comprehend finely how different components of organizational structure can increase the level of ACAP. The configurational approach may trigger new insights that could help managers prioritize selection criteria and understand the interactions between organizational structure and ACAP. The paper also discusses theoretical and managerial implications arising from these findings.

Keywords: absorptive capacity, organizational structure, PLS-SEM, fsQCA, predictive analysis, modeling subsample, holdout subsample

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Authors: Surajit Bhattacharya, Daniel Veltri, Atit A. Patel, Daniel N. Cox

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miRNAs have emerged as key post-transcriptional regulators of gene expression, however identification of biologically-relevant target genes for this epigenetic regulatory mechanism remains a significant challenge. To address this knowledge gap, we have developed a novel tool in R, Intra-miR-ExploreR, that facilitates integrated discovery of miRNA targets by incorporating target databases and novel target prediction algorithms, using statistical methods including Pearson and Distance Correlation on microarray data, to arrive at high confidence intragenic miRNA target predictions. We have explored the efficacy of this tool using Drosophila melanogaster as a model organism for bioinformatics analyses and functional validation. A number of putative targets were obtained which were also validated using qRT-PCR analysis. Additional features of the tool include downloadable text files containing GO analysis from DAVID and Pubmed links of literature related to gene sets. Moreover, we are constructing interaction maps of intragenic miRNAs, using both micro array and RNA-seq data, focusing on neural tissues to uncover regulatory codes via which these molecules regulate gene expression to direct cellular development.

Keywords: miRNA, miRNA:mRNA target prediction, statistical methods, miRNA:mRNA interaction network

Procedia PDF Downloads 484

Authors: Yongseok Kim, Jeong-Min Lee, Hyunwoo Song, Junghan Yun, Jungin Byun, Jae-Mean Koo, Chang-Sung Seok

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Thermal barrier coating(TBC) is applied for gas turbine components to protect the components from extremely high temperature condition. Since metallic substrate cannot endure such severe condition of gas turbines, delamination of TBC can cause failure of the system. Thus, delamination life of TBC is one of the most important issues for designing the components operating at high temperature condition. Thermal stress caused by thermally grown oxide(TGO) layer is known as one of the major failure mechanisms of TBC. Thermal stress by TGO mainly occurs at the interface between TGO layer and ceramic top coat layer, and it is strongly influenced by the thickness and shape of TGO layer. In this study, Isothermal oxidation is conducted on coin-type TBC specimens prepared by APS(air plasma spray) method. After the isothermal oxidation at various temperature and time condition, the thickness and shape(rumpling shape) of the TGO is investigated, and the test data is processed by numerical analysis. Finally, the test data is arranged into a mathematical prediction model with two variables(temperature and exposure time) which can predict the thickness and rumpling shape of TGO.

Keywords: thermal barrier coating, thermally grown oxide, thermal stress, isothermal oxidation, numerical analysis

Procedia PDF Downloads 325

Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

Procedia PDF Downloads 243

Authors: Rahul S. Raj

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Electro-mechanical impedance technique is a recently developed non-destructive method for structural health monitoring. This system comprises of piezo electric patch, bonded to the structure using an adhesive/epoxy and electrically excited to determine the health of the component. The subjected electric field actuates the PZT patch harmonically and imparts a force on the host structure. The structural response thus produced by the host component is in the form of peaks and valleys which further shows the admittance signatures of the structure for the given excitation frequency. Adhesives have the capability to change the structural signatures, in EMI technique, by transforming conductance and susceptance signatures. The static approximation provide a justifiable result where adhesive bond lines are thin and stiff. The epoxy adhesive bonds limits design flexibility due to poor bond strengths, hence to enhance the performance of the joints, a new technique is developed for joining PZT, i.e. the alloy bonding technique. It is a metallic joining compound which contains many active elements including Titanium, that reacts with the tenacious surface films of the ceramic and composites to create excellent bonds. This alloy-based bonding technique will be used for better strain interaction and rigorous stress transfer between PZT patch and the host structure.

Keywords: EMI technique, conductance, susceptance, admittance, alloy bonding

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Authors: Abdous Noureddine

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The problem of funding in Algeria emerged as a problem you need to study after many Algerians researchers pointed out that the faltering Algerian public economic institution due to the imbalance in the financial structures and lower steering and marketing efficiency, as well as a result of severe expansion of borrowing because of inadequate own resources, and the consequent inability This institution to repay loans and interest payments, in addition to increasing reliance on overdraft so used to finance fixed assets, no doubt that this deterioration requires research and study of the causes and aspects of treatment, which addresses the current study, aside from it.

Keywords: financial structure, financial capital, equity, debt, firm’s value, return, leverage

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Authors: Tomoya Oshiro, Hiroko Ono

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Japan's aging population is increasing due to the decrease in birthrate. It causes various problems like the decrease in the gross domestic product of the country. The reason is why the local government of Japan has been on the way to a sustainable city recently. Then it is essential to get control of an urban structure to make the compact city successful. There are many kinds of paper about the compact city; however, the paper about a compact city of the island-type city is less. The purpose of this study is to clarify difference of urban structure between an island-type and a general city type. The method which has conducted in this research has two steps. First of all, by using evaluation indexes in the handbook, we evaluated the urban structures among each same -population-class cities from 50,000 to 100,000 people. Next, to clear the difference about the urban structure and feature between island-type and general-type cities compare the radar chart which is composed with each evaluation indexes of urban structure. Moreover, in order to clarify the relationship between evaluation indexes and the place of residence by using GIS software to show up population density on the map. As a result of this research, the management of local government and the local economy in evaluation indexes are indicated to be negative point in comparison of island-type cities with general cities. However, evaluation indexes of safety/security and low-carbon/energy are proved to be positive point. The research to find the difference features of the island-type of urban structure proves that the management of local government or the local economy is negative point in these island-type cities. In addition, the public transportation coverage in Miyako Island, Sado Island, and Amakusa Island show low value compare with other islands and average value. Relationship between evaluation indexes of an urban structure and the place of residence prove that the place of residence is related to public transportation coverage. If the place of residence is spread out, the public transportation coverage will be decreased. The results of this research reveal that the finances in island-type cities are negative point compare to general cities. This problem is caused by declining population. In addition, the place of residence is related to the public transportation coverage. Even though, it needs a much money to increase the public transportation coverage. It is possibly to cause other problems furthermore the aspect of finance is influenced by that as well. The conclusion in this research suggests that it is important for creating the compact city in island-type cities that we first need to address solving the problems about the management of local government and the local economy.

Keywords: sustainable city, comparative analysis, geographic information system, urban structure

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Authors: Xiang-Yao Zheng, Jen-Cheng Wang, Joe-Air Jiang

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Improving the line ampacity while using existing power grids is an important issue that electricity dispatchers are now facing. Using the information provided by the dynamic thermal rating (DTR) of transmission lines, an overhead power grid can operate safely. However, dispatchers usually lack real-time DTR information. Thus, this study proposes a long-short-term memory (LSTM)-based method, which is one of the neural network models. The LSTM-based method predicts the DTR of lines using the weather data provided by Central Weather Bureau (CWB) of Taiwan. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed LSTM-based prediction method. A case study that targets the 345 kV power grid of TaiPower in Taiwan is utilized to examine the performance of the proposed method. The simulation results show that the proposed method is useful to provide the information for the smart grid application in the future.

Keywords: electricity dispatch, line ampacity prediction, dynamic thermal rating, long-short-term memory neural network, smart grid

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Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

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Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

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Authors: Hui-Chuan Lu

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In a perfect secret-sharing scheme, a dealer distributes a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of the participants in any unqualified subset is statistically independent of the secret. The access structure of the scheme refers to the collection of all qualified subsets. In a graph-based access structures, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing a given access structure is the ratio of the average length of the shares given to the participants to the length of the secret. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing an access structure is called the optimal average information ratio of that access structure. We study the optimal average information ratio of the access structures based on bipartite graphs. Based on some previous results, we give a bound on the optimal average information ratio for all bipartite graphs of girth at least six. This bound is the best possible for some classes of bipartite graphs using our approach.

Keywords: secret-sharing scheme, average information ratio, star covering, deduction, core cluster

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Authors: Taehyun Kim, Hyunjoo Park, Taehyun Kim

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Since the rapid economic development, Korea has recently entered a period of low growth due to population decline and aging. Due to the urbanization around the metropolitan area and the hollowing of local cities, the ecological capacity of a city is decreasing while ecological footprints are increasing, requiring a compact space plan for maintaining urban functions. The purpose of this study is to analyze the relationship between urban spatial structure and residents' ecological footprints for sustainable spatial planning. To do this, we try to analyze the relationship between intra-urban spatial structure, such as net/gross density and service accessibility, and resident ecological footprints of food, housing, transportation, goods and services through survey and structural equation modeling. The results of the study will be useful in establishing an implementation plan for sustainable development goals (SDGs), especially for sustainable cities and communities (SDG 11) and responsible consumption and production (SDG 12) in the future.

Keywords: ecological footprint, structural equation modeling, survey, sustainability, urban spatial structure

Procedia PDF Downloads 249

Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

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The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

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Authors: Mevlüt Burak Dalmış, Kemal Yaman

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In this study, flutter characteristics of cantilever rectangular plate structure under incompressible flow regime are investigated by comparing the results of commercial flutter analysis program ZAERO^© with wind tunnel tests conducted in Ankara Wind Tunnel (ART). A rectangular polycarbonate (PC) plate, 5x125x1000 mm in dimensions, is used for both numerical and experimental investigations. Analysis and test results are very compatible with each other. A comparison between two different solution methods (g and k-method) of ZAERO^© is also done. It is seen that, k-method gives closer result than the other one. However, g-method results are on conservative side and it is better to use conservative results namely g-method results. Even if the modal analysis results are used for the flutter analysis for this simple structure, a modal test should be conducted in order to validate the modal analysis results to have accurate flutter analysis results for more complicated structures.

Keywords: flutter, plate, subsonic flow, wind tunnel

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Authors: Sara Muhammad Elqudah, Vigh László Gergely

Abstract:

Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.

Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance

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Authors: Guanhao Tong, Li Li, Ben David

Abstract:

This study aims to provide an explanatory account of how the leisure tourist experience emerges from tourists and their surroundings through a critical realist lens. This was achieved by applying Archer’s realist social theory as the underlying theoretical ground to unpack the interplays between the external (tourism system or structure) and the internal (tourists or agency). This theory argues that social phenomena can be analyzed in three domains - structure, agency, and culture (SAC), and along three phases – structure conditioning, sociocultural interactions, and structure elaboration. From the realist perspective, the world is an open system; events and discourses are irreducible to present individuals and collectivities. Therefore, identifying the processes or mechanisms is key to help researchers understand how social reality is brought about. Based on the contextual nature of the tourist experience, the research focuses on Chinese tourists (from mainland China) to London as a destination and British culture conveyed through the concept of the destination image. This study uses an intensive approach based on Archer’s M/M approach to discover the mechanisms/processes of the emergence of the tourist experience. Individual interviews were conducted to reveal the underlying causes of lived experiences of the tourists. Secondary data was also collected to understand how British destinations are portrayed to Chinese tourists.

Keywords: Chinese tourists, destination image, M/M approach, realist social theory, social mechanisms, tourist experience

Procedia PDF Downloads 57