Search results for: rolling stock reliability
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2888

Search results for: rolling stock reliability

1778 Forming Limit Analysis of DP600-800 Steels

Authors: Marcelo Costa Cardoso, Luciano Pessanha Moreira

Abstract:

In this work, the plastic behaviour of cold-rolled zinc coated dual-phase steel sheets DP600 and DP800 grades is firstly investigated with the help of uniaxial, hydraulic bulge and Forming Limit Curve (FLC) tests. The uniaxial tensile tests were performed in three angular orientations with respect to the rolling direction to evaluate the strain-hardening and plastic anisotropy. True stress-strain curves at large strains were determined from hydraulic bulge testing and fitted to a work-hardening equation. The limit strains are defined at both localized necking and fracture conditions according to Nakajima’s hemispherical punch procedure. Also, an elasto-plastic localization model is proposed in order to predict strain and stress based forming limit curves. The investigated dual-phase sheets showed a good formability in the biaxial stretching and drawing FLC regions. For both DP600 and DP800 sheets, the corresponding numerical predictions overestimated and underestimated the experimental limit strains in the biaxial stretching and drawing FLC regions, respectively. This can be attributed to the restricted failure necking condition adopted in the numerical model, which is not suitable to describe the tensile and shear fracture mechanisms in advanced high strength steels under equibiaxial and biaxial stretching conditions.

Keywords: advanced high strength steels, forming limit curve, numerical modelling, sheet metal forming

Procedia PDF Downloads 359
1777 Does Supervisory Board Composition Influence Sustainability Reporting Quality?

Authors: Patrick Velte

Abstract:

Sustainability reporting has become a central element of modern corporate governance practice. This paper is the first to recognize supervisory board independence, sustainable expertise and gender diversity in two European two tier countries and their impact on sustainability reporting quality. For a sample of 188 German and Austrian companies which are listed at the Prime Standard of the Frankfurt and Vienna Stock Exchange for the business years 2012-2013, descriptive findings show that CSR reporting quality is still low in both countries. Furthermore, multiple regressions state that independent and female members in the supervisory board do have a positive impact on CSR reporting quality in Germany and Austria. However, the existence of sustainable experts in the supervisory board both in Germany and Austria shows a positive but insignificant impact. Our findings suggest that the current European corporate governance regulations can be a useful instrument to increase the quality of modern CSR reporting for the stakeholders.

Keywords: sustainability reporting, corporate governance, gender diversity, board independence

Procedia PDF Downloads 383
1776 Using “Eckel” Model to Measure Income Smoothing Practices: The Case of French Companies

Authors: Feddaoui Amina

Abstract:

Income smoothing represents an attempt on the part of the company's management to reduce variations in earnings through the manipulation of the accounting principles. In this study, we aimed to measure income smoothing practices in a sample of 30 French joint stock companies during the period (2007-2009), we used Dummy variables method and “ECKEL” model to measure income smoothing practices and Binomial test accourding to SPSS program, to confirm or refute our hypothesis. This study concluded that there are no significant statistical indicators of income smoothing practices in the sample studied of French companies during the period (2007-2009), so the income series in the same sample studied of is characterized by stability and non-volatility without any intervention of management through accounting manipulation. However, this type of accounting manipulation should be taken into account and efforts should be made by control bodies to apply Eckel model and generalize its use at the global level.

Keywords: income, smoothing, 'Eckel', French companies

Procedia PDF Downloads 142
1775 A Survey on the Blockchain Smart Contract System: Security Strengths and Weaknesses

Authors: Malaw Ndiaye, Karim Konate

Abstract:

Smart contracts are computer protocols that facilitate, verify, and execute the negotiation or execution of a contract, or that render a contractual term unnecessary. Blockchain and smart contracts can be used to facilitate almost any financial transaction. Thanks to these smart contracts, the settlement of dividends and coupons could be automated. Smart contracts have become lucrative and profitable targets for attackers because they can hold a great amount of money. Smart contracts, although widely used in blockchain technology, are far from perfect due to security concerns. Since there are recent studies on smart contract security, none of them systematically study the strengths and weaknesses of smart contract security. Some have focused on an analysis of program-related vulnerabilities by providing a taxonomy of vulnerabilities. Other studies are responsible for listing the series of attacks linked to smart contracts. Although a series of attacks are listed, there is a lack of discussions and proposals on improving security. This survey takes stock of smart contract security from a more comprehensive perspective by correlating the level of vulnerability and systematic review of security levels in smart contracts.

Keywords: blockchain, Bitcoin, smart contract, criminal smart contract, security

Procedia PDF Downloads 153
1774 Towards a Simulation Model to Ensure the Availability of Machines in Maintenance Activities

Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

Abstract:

The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: maintenance, complexity, simulation, multi-agent systems, AnyLogic platform

Procedia PDF Downloads 289
1773 A System Dynamic Based DSS for Ecological Urban Management in Alexandria, Egypt

Authors: Mona M. Salem, Khaled S. Al-Hagla, Hany M. Ayad

Abstract:

The concept of urban metabolism has increasingly been employed in a diverse range of disciplines as a mean to analyze and theorize the city. Urban ecology has a particular focus on the implications of applying the metabolism concept to the urban realm. This approach has been developed by a few researchers, though it has rarely if ever been used in policy development for city planning. The aim of this research is to use ecologically informed urban planning interventions to increase the sustainability of urban metabolism; with special focus on land stock as a most important city resource by developing a system dynamic based DSS. This model identifies two critical management strategy variables for the Strategic Urban Plan Alexandria SUP 2032. As a result, this comprehensive and precise quantitative approach is needed to monitor, measure, evaluate and observe dynamic urban changes working as a decision support system (DSS) for policy making.

Keywords: ecology, land resource, LULCC, management, metabolism, model, scenarios, system dynamics, urban development

Procedia PDF Downloads 365
1772 Assessment of the Two-Way Relationship between Capital Structure and Operation Performance of Listed Companies on Vietnam’s Stock

Authors: Uyen Tran Tu

Abstract:

The decision on capital structure is one of the most important and sophisticated decisions in financial management in order to improve firm performance. This article would study the two-way impact between capital structure and firm performance. The study use EVIEWS 6.0 software to determine a two-way relationship between the capital structure and firm performance based on two-stage regression (2SLS - Two-Stage Least Squares). The findings are: capital structure has the opposite effect on the business efficiency and vice versa, factors that effect on business efficiency include Size and Opportunities. Factors effects on the capital structure are size; liquidity. These factors also affect the ratio of capital structure (total debt/ total asset) of companies. In particular, liquidity has the opposite effect; and the size of the business has the same impact. The results of the study are in line with the theory and empirical studies presented, and the results of the study are unchanged for all three years 2015-2017.

Keywords: capital structure, firm performance, factors, two-way relationship

Procedia PDF Downloads 139
1771 Cytology Is a Promising Tool for the Diagnosis of High-Grade Serous Ovarian Carcinoma from Ascites

Authors: Miceska Simona, Škof Erik, Frković Grazio Snježana, Jeričević Anja, Smrkolj Špela, Cvjetićanin Branko, Novaković Srdjan, Grčar Kuzmanov Biljana, Kloboves-Prevodnik Veronika

Abstract:

Objectives: High-grade serous ovarian cancer (HGSOC) is characterized by the dissemination of the tumor cells (TC) in the peritoneal cavity forming malignant ascites at the time of diagnosis or recurrence. Still, cytology itself has been underutilized as a modality for the diagnosis of HGSOC from ascites, and histological examination from the tumor tissue is yet the only validated method used. The objective of this study was to evaluate the reliability of cytology in the diagnosis of HGSOC in relation to the histopathological examination. Methods: The study included 42 patients with histologically confirmed HGSOC, accompanied by malignant ascites. To confirm the malignancy of the TC in the ascites and to define their immunophenotype, immunohistochemical reaction (IHC) of the following antigens: Calretinin, MOC, WT1, PAX8, p53, p16 & Ki-67 was evaluated on ascites cytospins and tissue blocks. For complete cytological determination of HGSOC, BRCA 1/2 gene mutation was determined from ascites, tissue block, and blood. BRCA1/2 mutation from blood was performed to define the type of mutation, somatic vs germline. Results: Among 42 patients, the immunophenotype of HGSOC from ascites was confirmed in 36 cases (86%). For more profound analysis, the patients were divided in 3 groups regarding the number of TC present in the ascites: patients with less than 10% TC, 10% TC, and more than 10% TC. From all included patients, in the group with less than 10% TC, there were 10 cases, and only 5 of them(50%) showed HGSOC phenotype; 12 cases had equally 10% of TC, and 11 cases (92%) showed HGSOC phenotype; 20 cases had more than 10% TC and all of them (100%) confirmed the HGSOC immunophenotype from ascites. Only 33 patients were eligible for further BRCA1/2 analysis. Eleven BRCA1/2 mutations were detected from thetissue block: 6 germline and 5 somatic. In 2 cases with less than 10% TC, BRCA1/2 mutation was not detected; 4 cases had 10% TC, and 2 of them (50%) confirmed the mutation; 4 cases had more than 10% TC, and all showed 100% reliability with the tumor tissue. Conclusions: Cytology is a highly reliable method for determining the immunophenotype of HGSOC and BRCA1/2 mutation if more than 10% of tumor cells are present in the ascites. This may present an additional non-invasive clinical approach for fast and effective diagnose in the future, especially in inoperable conditions or relapses.

Keywords: cytology, ascites, high-grade serous ovarian cancer, immunophenotype, BRCA1/2

Procedia PDF Downloads 173
1770 The Consumer's Behavior of Bakery Products in Bangkok

Authors: Jiraporn Weenuttranon

Abstract:

The objectives of the consumer behavior of bakery products in Bangkok are to study consumer behavior of the bakery product, to study the essential factors that could possibly affect the consumer behavior and to study recommendations for the development of the bakery products. This research is a survey research. Populations are buyer’s bakery products in Bangkok. The probability sample size is 400. The research uses a questionnaire for self-learning by using information technology. The researcher created a reliability value at 0.71 levels of significance. The data analysis will be done by using the percentage, mean, and standard deviation and testing the hypotheses by using chi-square.

Keywords: consumer, behavior, bakery, standard deviation

Procedia PDF Downloads 458
1769 Effects of Financial and Non-Financial Reports On - Firms Performance

Authors: Vithaya Intaraphimol

Abstract:

This research investigates the effect of financial accounting information and non-financial accounting reports on corporate credibility via strength of board of directors and market environment volatility as moderating effect. Data in this research is collected by questionnaire form non-financial companies listed on the Stock Exchange of Thailand. Multiple regression statistic technique is chosen for analyzing the data. The empirical results find that firms with greater financial accounting information reports and non-financial accounting information reports will gain greater corporate credibility. Therefore, the corporate reporting has the value for the firms. Moreover, the strength of board of directors will positively moderate the financial and non-financial accounting information reports and corporate credibility relationship. Whereas, market environment volatility will negatively moderate the financial and nonfinancial accounting information reports and corporate credibility relationship.

Keywords: corporate credibility, financial and non-financial reports, firms performance, economics

Procedia PDF Downloads 442
1768 Detecting Model Financial Statement Fraud by Auditor Industry Specialization with Fraud Triangle Analysis

Authors: Reskino Resky

Abstract:

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

Procedia PDF Downloads 445
1767 Smart Defect Detection in XLPE Cables Using Convolutional Neural Networks

Authors: Tesfaye Mengistu

Abstract:

Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 89
1766 Optimal Hedging of a Portfolio of European Options in an Extended Binomial Model under Proportional Transaction Costs

Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

Abstract:

Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

Procedia PDF Downloads 239
1765 Fama French Four Factor Model: A Study of Nifty Fifty Companies

Authors: Deeksha Arora

Abstract:

The study aims to explore the applicability of the widely used asset pricing models, namely, Capital Asset Pricing Model (CAPM) and the Fama-French Four Factor Model in the Indian equity market. The study will be based on the companies that form part of the Nifty Fifty Index for a period of five years: 2011 to 2016. The asset pricing model is examined by forming portfolios on the basis of three variables – market capitalization (size effect), book-to-market equity ratio (value effect) and profitability. The study provides a basis to test the presence of the Fama-French Four factor model in Indian stock market. This study may provide a basis for future research in the generalized asset pricing model comprising of multiple risk factors.

Keywords: book to market equity, Fama French four factor model, market capitalization, profitability, size effect, value effect

Procedia PDF Downloads 243
1764 Granger Causal Nexus between Financial Development and Energy Consumption: Evidence from Cross Country Panel Data

Authors: Rudra P. Pradhan

Abstract:

This paper examines the Granger causal nexus between financial development and energy consumption in the group of 35 Financial Action Task Force (FATF) Countries over the period 1988-2012. The study uses two financial development indicators such as private sector credit and stock market capitalization and seven energy consumption indicators such as coal, oil, gas, electricity, hydro-electrical, nuclear and biomass. Using panel cointegration tests, the study finds that financial development and energy consumption are cointegrated, indicating the presence of a long-run relationship between the two. Using a panel vector error correction model (VECM), the study detects both bidirectional and unidirectional causality between financial development and energy consumption. The variation of this causality is due to the use of different proxies for both financial development and energy consumption. The policy implication of this study is that economic policies should recognize the differences in the financial development-energy consumption nexus in order to maintain sustainable development in the selected 35 FATF countries.

Keywords: energy consumption, financial development, FATF countries, Panel VECM

Procedia PDF Downloads 253
1763 Deep Learning for SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 56
1762 Lipopolysaccharide Induced Avian Innate Immune Expression in Heterophils

Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

Abstract:

Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed, with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

Procedia PDF Downloads 596
1761 Legal Disputes of Disclosure and Transparency under Kuwaiti Capital Market Authority Law

Authors: Mohammad A. R. S. Almutairi

Abstract:

This study will provide the introduction that constitutes the problem cornerstone of legal disputes of disclosure and transparency under Kuwaiti Capital market authority Law No. 7 of 2010. It also will discuss the reasons for the emergence of corporate governance and its purposes in the Capital Market Authority Law in Kuwait. In addition, it will show the legal disputes resulting from the unclear concept of disclosure and interest and will discuss the main reasons in support of the possible solution. In addition, this study will argue why the Capital Market Authority Law in Kuwait needs a clear concept and a straight structure of disclosure under section 100. This study will demonstrate why a clear disclosure is led to a better application of the law. This study will demonstrate the fairness in applying the law regarding the punishment against individual, companies and securities market. Furthermore, it will discuss added confidence between investors and the stock market with a clear concept under section 100. Finally, it will summarize arises problem and possible solution.

Keywords: corporate governors, disclosure, transparency, fairness

Procedia PDF Downloads 124
1760 The Popular Imagination through the Poem of “Ras B’Nadam”

Authors: Hirreche Baghdad Mohamed

Abstract:

One of the main texts in popular culture in Algeria is a symbolic and imaginary tale, through which the author was able to derive from the world and popular cultural stock and symbolic capital elements that enabled him to create a synthesis between a number of imaginary and real events. Thanks to the level of spirituality that the author was experiencing, he was able to go deep in order to redraw the boundaries of human life in view of its existence and status (life experiences, its end, and its fate). It is a text that is consistent with religious values and has a philosophical depth. This poem can be shared in official and unofficial meetings, during feasts, and during popular celebrations, such as circumcision ceremonies, marriage, and condolences. It has also the ability to draw attention and appeal to the listener and let him travel into the imaginary world. It is the text related to the story of "Ras b’nadem", or "the head of a man", or rather, a "human skull", for which only a few academic studies have been devoted, and there are two copies of it, one attributed to Lakhdar Ibn Khalouf as a matter of suspicion, while the other is attributed to Qadour Ibn Ashour Al-Zarhouni.

Keywords: ras B’Nadam, ras al mahna, lakhdar ibn khalouf, qadour ibn ashour, sufism, melhoun poetry, resistance poetry

Procedia PDF Downloads 170
1759 Deep Learning Based Polarimetric SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 71
1758 A Coupling Study of Public Service Facilities and Land Price Based on Big Data Perspective in Wuxi City

Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

Abstract:

Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

Procedia PDF Downloads 187
1757 The Effects of the Corporate Governance on the Level of Internet Financial Reporting: Evidence from Turkish Companies

Authors: Raif Parlakkaya, Umran Kahraman, Huseyin Cetin

Abstract:

Internet financial reporting and corporate governance issues are in the focus of academic and professional studies due to their attributed importance by stakeholders of corporations. Major aim of this study is to reveal the relationship between internet financial reporting which is held as dependent variable and some indicators of corporate governance such as the ratio of managerial ownership, blockholder ownership, number of independent members in the board of directors, frequency of meetings by audit committee and education level of audit committee members which are held as independent variables. Main purpose is to reveal the effect of corporate governance on the voluntary efforts of Internet Financial reporting. The scope of the research is limited to the Turkish Corporations listed in Borsa Istanbul (Istanbul Stock Exchange) and findings which are generated by means of SPSS software are revealed in results section and interpreted in conclusions.

Keywords: audit committee, corporate governance, internet financial reporting, managerial ownership

Procedia PDF Downloads 504
1756 Influence of Gender Inequality on Pre – Primary School Children’s Literacy Skills Development in Ojo Local Government Area, Lagos State

Authors: Morenikeji Aliu Balaji

Abstract:

Gender inequality is seen as persistent discrimination of one group of people based gender, and it manifests itself differently according to race, culture, politics, country and economic situation. Multiple explanations have been offered for gender differences in literacy skill development. Three prominent explanations that precipitated the gender differences are; biological, where the assumption is that differential brain structures and hemispheric activation patterns cause the sexes to be hardwired differently for reading, with girls developing the cognitive skills associated with reading before boys. Secondly, schooling favour girls and ‘girly’ behaviour, and that boys are, as a result, lagging behind on several behavioural, social and academic measures and thirdly, cultural influences, where literacy is defined as a feminine characteristic – propagated by an overrepresentation of female teachers – and that modern culture steers boys towards activities such as sport and computers. Therefore the study investigated the influence of gender inequality on pre – primary school children literacy skills development in Ojo Local Government Area, Lagos State. Descriptive survey research design was adopted for the study. 100 pre-primary school teachers were involved in the study. A self-designed instrument was used for data collection titled ‘Influence of Gender Inequality on Literacy Skill Development in Children Questionnaire (IGILSDCQ)’. The instrument was validated and tested for reliability. The reliability index for IGILSDCQ (α = 0.79). Five research questions were answered using descriptive (frequency count, simple percentage, mean and standard deviation). The findings showed that that gender inequality to some extent influence children phonemic awareness (WA=1.76), the extent to which gender inequality influence children awareness of print is high (WA=2.8), gender inequality to some extent influence children vocabulary development (WA = 2.4), the extent to which gender inequality influence children speaking skill development is high (WA = 2.5) and lastly, the extent to which gender inequality influence children comprehension ability is high (WA = 2.5). It was recommended among others that effort by the school administrators is necessary in the provision of reading materials and literacy skill development packages that are both male-oriented and female-oriented.

Keywords: pre-primart, literacy, awareness, phonemic, gender

Procedia PDF Downloads 14
1755 Analysis of Financial Time Series by Using Ornstein-Uhlenbeck Type Models

Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

Abstract:

In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

Procedia PDF Downloads 225
1754 Predicting Financial Distress in South Africa

Authors: Nikki Berrange, Gizelle Willows

Abstract:

Business rescue has become increasingly popular since its inclusion in the Companies Act of South Africa in May 2011. The Alternate Exchange (AltX) of the Johannesburg Stock Exchange has experienced a marked increase in the number of companies entering business rescue. This study sampled twenty companies listed on the AltX to determine whether Altman’s Z-score model for emerging markets (ZEM) or Taffler’s Z-score model is a more accurate model in predicting financial distress for small to medium size companies in South Africa. The study was performed over three different time horizons; one, two and three years prior to the event of financial distress, in order to determine how many companies each model predicted would be unlikely to succeed as well as the predictive ability and accuracy of the respective models. The study found that Taffler’s Z-score model had a greater ability at predicting financial distress from all three-time horizons.

Keywords: Altman’s ZEM-score, Altman’s Z-score, AltX, business rescue, Taffler’s Z-score

Procedia PDF Downloads 343
1753 Co-Pyrolysis of Olive Pomace with Plastic Wastes and Characterization of Pyrolysis Products

Authors: Merve Sogancioglu, Esra Yel, Ferda Tartar, Nihan Canan Iskender

Abstract:

Waste polyethylene (PE) is classified as waste low density polyethylene (LDPE) and waste high density polyethylene (HDPE) according to their densities. Pyrolysis of plastic waste may have an important role in dealing with the enormous amounts of plastic waste produced all over the world, by decreasing their negative impact on the environment. This waste may be converted into economically valuable hydrocarbons, which can be used both as fuels and as feed stock in the petrochemical industry. End product yields and properties depend on the plastic waste composition. Pyrolytic biochar is one of the most important products of waste plastics pyrolysis. In this study, HDPE and LDPE plastic wastes were co-pyrolyzed together with waste olive pomace. Pyrolysis runs were performed at temperature 700°C with heating rates of 5°C/min. Higher pyrolysis oil and gas yields were observed by the using waste olive pomace. The biochar yields of HDPE- olive pomace and LDPEolive pomace were 6.37% and 7.26% respectively for 50% olive pomace doses. The calorific value of HDPE-olive pomace and LDPE-olive pomace of pyrolysis oil were 8350 and 8495 kCal.

Keywords: biochar, co-pyrolysis, waste plastic, waste olive pomace

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1752 A Semi-supervised Classification Approach for Trend Following Investment Strategy

Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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1751 Equipment Design for Lunar Lander Landing-Impact Test

Authors: Xiaohuan Li, Wangmin Yi, Xinghui Wu

Abstract:

In order to verify the performance of lunar lander structure, landing-impact test is urgently needed. Moreover, the test equipment is necessary for the test. The functions and the key points of the equipment is presented to satisfy the requirements of the test,and the design scheme is proposed. The composition, the major function and the critical parts’ design of the equipment are introduced. By the load test of releasing device and single-beam hoist, and the compatibility test of landing-impact testing system, the rationality and reliability of the equipment is proved.

Keywords: landing-impact test, lunar lander, releasing device, test equipment

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1750 Evaluation of Toxicity of Cerium Oxide on Zebrafish Developmental Stages

Authors: Roberta Pecoraro, Elena Maria Scalisi

Abstract:

Engineered Nanoparticles (ENPs) and Nanomaterials (ENMs) concern an active research area and a sector in full expansion. They have physical-chemical characteristics and small size that improve their performance compared to common materials. Due to the increase in their production and their subsequent release into the environment, new strategies are emerging to assess risk of nanomaterials. NPs can be released into the environment through aquatic systems by human activities and exert toxicity on living organisms. We evaluated the potential toxic effect of cerium oxide (CeO2) nanoparticles because it’s used in different fields due to its peculiar properties. In order to assess nanoparticles toxicity, Fish Embryo Toxicity (FET) test was performed. Powders of CeO2 NPs supplied by the CNR-IMM of Catania are indicated as CeO2 type 1 (as-prepared) and CeO2 type 2 (modified), while CeO2 type 3 (commercial) is supplied by Sigma-Aldrich. Starting from a stock solution (0.001g/10 ml dilution water) of each type of CeO2 NPs, the other concentration solutions were obtained adding 1 ml of the stock solution to 9 ml of dilution water, leading to three different solutions of concentration (10-4, 10-5, 10-6 g/ml). All the solutions have been sonicated to avoid natural tendency of NPs to aggregate and sediment. FET test was performed according to the OECD guidelines for testing chemicals using our internal protocol procedure. A number of eight selected fertilized eggs were placed in each becher filled with 5 ml of each concentration of the three types of CeO2 NPs; control samples were incubated only with dilution water. Replication was performed for each concentration. During the exposure period, we observed four endpoints (embryo coagulation, lack of formation of somites, failure to lift the yolk bag, no heartbeat) by a stereomicroscope every 24 hours. Immunohistochemical analysis on treated larvae was performed to evaluate the expression of metallothioneins (MTs), Heat Shock Proteins 70 (HSP70) and 7-ethoxyresorufin-O-diethylase (EROD). Our results have not shown evident alterations on embryonic development because all embryos completed the development and the hatching of the eggs, started around the 48th hour after exposure, took place within the last observation at 72 hours. A good reactivity, both in the embryos and in the newly hatched larvae, was found. The presence of heartbeat has also been observed in embryos with reduced mobility confirming their viability. A higher expression of EROD biomarker was observed in the larvae exposed to the three types of CeO2, showing a clear difference with the control. A weak positivity was found for MTs biomarker in treated larvae as well as in the control. HSP70 are expressed homogeneously in all the type of nanoparticles tested but not too much greater than control. Our results are in agreement with other studies in the literature, in which the exposure of Danio rerio larvae to other metal oxide nanoparticles does not show adverse effects on survival and hatching time. Further studies are necessary to clarify the role of these NPs and also to solve conflicting opinions.

Keywords: Danio rerio, endpoints, fish embryo toxicity test, metallic nanoparticles

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1749 Board Characteristics, Audit Committee Characteristics, and the Level of Bahraini Corporate Compliance with Mandatory IFRS Disclosure Requirements

Authors: Omar Juhmani

Abstract:

This paper examines the relation between internal corporate governance and the level of corporate compliance with mandatory IFRS disclosure requirements. The internal corporate governance is measured by board and audit committee characteristics. Using data from Bahrain Stock Exchange, the results show that board independence is positively and significantly associated with level of compliance with IFRS disclosure requirements. This suggests that internal corporate governance mechanisms are effective in the financial reporting practices by increasing the level of compliance with IFRS disclosures. Also, the results of the regression analyses indicate that two of the control variables; company size and audit firm size are significantly positively associated with the level of corporate compliance with mandatory IFRS disclosure requirements in Bahrain.

Keywords: Bahrain, board and audit committee characteristics, compliance, disclosure, IFRS

Procedia PDF Downloads 406