Search results for: rolling stock reliability

Authors: Kanhaiya Singh

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Indian corporate sector has been raising resources through various international financial instruments important among them are Global depository receipts (GDRs) and American Depository Receipts (ADRs). The purpose of raising resources through such instruments is multifold such as lower cost of capital, increased visibility of the company, liberal tax environment, increased trading liquidity etc. One of the significant reason is also the value addition of the company in terms of market capitalization. Obviously, the stocks of such companies are cross listed, one in India and other at the International stock exchange. The sensitivity and movements of stock prices on one stock exchange as compared to other may have an impact on the price movement of the particular scrip. If there is any relationship exists is an issue of study. Having this in view this study is an attempt to identify the extent of impact of price movement of the scrip on one stock exchange on account of change in the prices on the counter stock exchange. Also there is an attempt to find out the difference between pre and post cross listed domestic firm. The study also analyses the impact of exchange rate movements on stock prices.

Keywords: ADR, GDR, cross listing, liquidity, exchange rate

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Authors: Quang Dong Dang

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This paper examines the possible effects of stock market developments by channels on income and wealth inequality. We use the Bayesian Multilevel Model with the explanatory variables of the market’s channels, such as accessibility, efficiency, and market health in six selected countries: the US, UK, Japan, Vietnam, Thailand, and Malaysia. We found that generally, the improvements in the stock market alleviate income inequality. However, stock market expansions in higher-income countries are likely to trigger income inequality. We also found that while enhancing the quality of channels of the stock market has counter-effects on wealth equality distributions, open accessibilities help reduce wealth inequality distributions within the scope of the study. In addition, the inverted U-shaped hypothesis seems not to be valid in six selected countries between the period from 2006 to 2020.

Keywords: Bayesian multilevel model, income inequality, inverted u-shaped hypothesis, stock market development, wealth inequality

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Authors: Tarah Bouaricha

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The impact of worst natural disasters is analysed in terms of insured losses which happened between 2010 and 2014 on S&P insurance index. Event study analysis is used to test whether natural disasters impact insurance index stock market price. There is no negative impact on insurance stock market price around the disasters event. To analyse the reaction of insurance stock market, normal returns (NR), abnormal returns (AR), cumulative abnormal returns (CAR), cumulative average abnormal returns (CAAR) and a parametric test on AR and on CAR are used.

Keywords: study event, natural disasters, insurance, reinsurance, stock market

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Authors: Irfan Ullah Munir, Shen Yue, Muhammad Shahzad Ijaz, Saad Hussain, Syeda Yumna Zaidi

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Financial literacy is fundamental to every decision-making process and has received attention from researchers, regulatory bodies and policy makers in the recent past. This study is an attempt to evaluate financial literacy in an emerging economy, particularly Pakistan, and its influence on people's stock market participation. Data of this study was collected through a structured questionnaire from a sample of 300 respondents. EFA is used to check the convergent and discriminant validity. Data is analyzed using Hayes (2013) approach. A set of demographic control variables that have passed the mean difference test is used. We demonstrate that participants with financial literacy tend to invest more in the stock market. We also find that association among financial literacy and participation in stock market gets moderated by gender.

Keywords: Financial literacy, Stock market participation, Gender, PSX

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Authors: Philemon Rakoto

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This paper tests the improvement of financial reporting quality when firms award stock options to their executives. The originality of this study is that we introduce the moderating effect of business ethics in the model. The sample is made up of 116 Canadian high-technology firms with available data for the fiscal year ending in 2012. We define the quality of financial reporting as the value relevance of accounting information as developed by Ohlson. Our results show that executive stock option award alone does not improve the quality of financial reporting. Rather, the quality improves when a firm awards stock options to its executives and investors perceive that the level of business ethics in that firm is high.

Keywords: business ethics, Canada, high-tech firms, stock options, value relevance

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Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

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The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

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Authors: Ji Su Kim, Bo Ram Choi, Ju Yeon Cho, Hyukjin Lee

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Epidermal growth factor receptor (EGFR) 19 deletion mutation gene is over-expressed in carcinoma patient. EGFR 19 deletion mutation is known as typical biomarker of non-small cell lung cancer (NSCLC), which one section in the coding exon 19 of EGFR is deleted. Therefore, there have been many attempts over the years to detect EGFR 19 deletion mutation for replacing conventional diagnostic method such as PCR and tissue biopsy. We developed a simple and facile detection platform based on Rolling Circle Amplification (RCA), which provides highly amplified products in isothermal amplification of the ligated DNA template. Limit of detection (~50 nM) and a faster detection time (~30 min) could be achieved by introducing RCA.

Keywords: EGFR19, cancer, diagnosis, rolling circle amplification (RCA), hydrogel

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Authors: N. Kazantseva, P. Krakhmalev, I. Yadroitsev, A. Fefelov, N. Vinogradova, I. Ezhov, T. Kurennykh

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Martensitic texture-phase transition in Selective Laser Melting (SLM) Ti-6Al-4V (ELI) alloys was found. Electron Backscatter Diffraction (EBSD) analysis showed the initial cubic beta < 100 > (001) BCC texture. Such kind of texture is observed in BCC metals with flat rolling texture when axis is in the direction of rolling and the texture plane coincides with the plane of rolling. It was found that the texture of the parent BCC beta-phase determined the texture of low-temperature HCP alpha-phase limited the choice of its orientation variants. The {10-12} < -1011 > twinning system in titanium alloys after SLM was determined. Analysis of the oxygen contamination in SLM alloys was done. Comparison of the obtained results with the conventional titanium alloys is also provided.

Keywords: additive technology, texture, twins, Ti-6Al-4V, oxygen content

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Authors: Shraddha Jain Sharma, Ratnalata Gupta

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Predicting stock movements in the financial market is both difficult and rewarding. Analysts and academics are increasingly using advanced approaches such as machine learning techniques to anticipate stock price patterns, thanks to the expanding capacity of computing and the recent advent of graphics processing units and tensor processing units. Stock market prediction is a type of time series prediction that is incredibly difficult to do since stock prices are influenced by a variety of financial, socioeconomic, and political factors. Furthermore, even minor mistakes in stock market price forecasts can result in significant losses for companies that employ the findings of stock market price prediction for financial analysis and investment. Soft computing techniques are increasingly being employed for stock market prediction due to their better accuracy than traditional statistical methodologies. The proposed research looks at the need for soft computing techniques in stock market prediction, the numerous soft computing approaches that are important to the field, past work in the area with their prominent features, and the significant problems or issue domain that the area involves. For constructing a predictive model, the major focus is on neural networks and fuzzy logic. The stock market is extremely unpredictable, and it is unquestionably tough to correctly predict based on certain characteristics. This study provides a complete overview of the numerous strategies investigated for high accuracy prediction, with a focus on the most important characteristics.

Keywords: stock market prediction, artificial intelligence, artificial neural networks, fuzzy logic, accuracy, deep learning, machine learning, stock price, trading volume

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Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

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Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

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Authors: Nur Sulihatimarsyila Abd Wafti, Harrison Lik Nang Lau, Nabilah Kamaliah Mustaffa, Nur Azreena Idris

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The use of biolubricant has gained its popularity over the last decade. Base stock produced using methyl ester and trimethylolethane (TME) can be potentially used for biolubricant production due to its biodegradability, non-toxicity and good thermal stability. The synthesis of biolubricant base stock e.g. triester (TE) via transesterification of palm methyl ester and TME in the presence of sodium methoxide as the catalyst was conducted. Factors influencing the reaction conditions were investigated including reaction time, temperature and pressure. The palm-based biolubricant base stock produced was analysed for its monoester (ME), diester (DE) and TE contents using gas chromatography as well as its lubricating properties such as viscosity, viscosity index, oxidation stability, and density. The resulting base stock containing 90 wt% TE was successfully synthesized.

Keywords: biolubricant, methyl ester, triester transesterification, lubricating properties

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

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

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Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian automotive sector, stock market decisions, equity portfolio analysis, decision tree classifiers, statistical data analysis

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Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

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The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

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Authors: Maziar Yazdani, Ahmad Khodaee, Fatemeh Hajizadeh

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The purpose of this research was analysis of the reliability of the signaling system in the railway and planning repair and maintenance of its subsystems. For this purpose, it will be endeavored to introduce practical strategies for activities control and appropriate planning for repair and preventive maintenance by statistical modeling of reliability. Therefore, modeling, evaluation, and promotion of reliability of the signaling system appear very critical. Among the key goals of the railway is provision of quality service for passengers and this purpose is gained by increasing reliability, availability, maintainability and safety of (RAMS). In this research, data were analyzed, and the reliability of the subsystems and entire system was calculated and with emphasis on preservation of performance of each of the subsystems with a reliability of 80%, a plan for repair and preventive maintenance of the subsystems of the signaling system was introduced.

Keywords: reliability, modeling reliability, plan for repair and preventive maintenance, signaling system

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Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

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Authors: Joon Ho Kim, Tae Kwon Ha

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Effect of aging treatment on microstructural aspects of interfacial layers of the Cu/Al clad sheet produced by Differential Speed Rolling (DSR) process were studied by Electron Back Scattered Diffraction (EBSD). Clad sheet of Al/Cu has been fabricated by using DSR, which caused severe shear deformation between Al and Cu plate to easily bond to each other. Rolling was carried out at 100°C with speed ratio of 2, in which the total thickness reduction was 45%. Interface layers of clad sheet were analyzed by EBSD after subsequent annealing at 400°C for 30 to 120 min. With increasing annealing time, thickness of interface layer and fraction of high angle grain boundary were increased and average grain size was decreased.

Keywords: aluminium/copper clad sheet, differential speed rolling, interface layer, microstructure, annealing, electron back scattered diffraction

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Authors: Anurag Savarnya

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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.

Keywords: reliability, Weibull model, electric mining shovel

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Authors: Serpil Türkyılmaz, Mesut Balıbey

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In this study, long memory properties in volatility of Turkey Stock Market are being examined through the FIGARCH, FIEGARCH and FIAPARCH models under different distribution assumptions as normal and skewed student-t distributions. Furthermore, structural changes in volatility of Turkey Stock Market are investigated. The results display long memory property and the presence of asymmetric effects of shocks in volatility of Turkey Stock Market.

Keywords: FIAPARCH model, FIEGARCH model, FIGARCH model, structural break

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Authors: Somnath Mukhuti, Prem Kumar Ghosh

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Background and significance of the study Indian stock market has undergone sudden changes after the current China crisis in terms of turnover, market capitalization, share prices, etc. The average returns on equity investment in both markets have more than three and half times after global financial crisis owing to the development of industrial activity, corporate sectors development, enhancement in global consumption, change of global financial association and fewer imports from developed countries. But the economic policies of both the economies are far different, that is to say, where Indian economy maintaining a conservative policy, Chinese economy maintaining an aggressive policy. Besides this, Chinese economy recently lowering its currency for increasing mysterious growth but Indian does not. But on August 24, 2015 Indian stock market and world stock markets were fall down due to the reason of Chinese stock market. Keeping in view of the above, this study seeks to examine the influence of Chinese stock on Indian stock market. Methodology This research work is based on daily time series data obtained from yahoo finance database between 2009 (April 1) to 2015 (September 28). This study is based on two important stock markets, that is, Indian stock market (Bombay Stock Exchange) and Chinese stock market (Shanghai Stock Exchange). In the course of analysis, the daily raw data were converted into natural logarithm for minimizing the problem of heteroskedasticity. While tackling the issue, correlation statistics, ADF and PP unit root test, bivariate cointegration test and causality test were used. Major findings Correlation statistics show that both stock markets are associated positively. Both ADF and PP unit root test results demonstrate that the time series data were not normal and were not stationary at level however stationary at 1st difference. The bivariate cointegration test results indicate that the Indian stock market was associated with Chinese stock market in the long-run. The Granger causality test illustrates there was a unidirectional causality between Indian stock market and Chinese stock market. Concluding statement The empirical results recommend that India’s stock market was not very much dependent on Chinese stock market because of Indian economic conservative policies. Nevertheless, Indian stock market might be sturdy if Indian economic policies are changed slightly and if increases the portfolio investment with Chinese economy. Indian economy might be a third largest economy in 2030 if India increases its portfolio investment and trade relations with both Chinese economy and US economy.

Keywords: Indian stock market, China stock market, bivariate cointegration, causality test

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Authors: Mahdi Karazmodeh, Pooyan Jafari

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One of the most interesting topics in finance is the relation between stock prices and exchange rates. During the past decades different stock markets in different countries have been the subject of study for researches. The volatilities of exchange rates and its effect on stock prices during the past 10 years have continued to be an attractive research topic. The subject of this study is one of the most important indices, FTSE 100. 20 firms with the highest market capitalization in 5 different industries are chosen. Firms are included in oil and gas, mining, pharmaceuticals, banking and food related industries. 5 different criteria have been introduced to evaluate the relationship between stock markets and exchange rates. Return of market portfolio, returns on broad index of Sterling are also introduced. The results state that not all firms are sensitive to changes in exchange rates. Furthermore, a Granger Causality test has been run to observe the route of changes between stock prices and foreign exchange rates. The results are consistent, to some level, with the previous studies. However, since the number of firms is not large, it is suggested that a larger number of firms being used to achieve the best results. However results showed that not all firms are affected by foreign exchange rates changes. After testing Granger Causality, this study found out that in some industries (oil and gas, pharmaceuticals), changes in foreign exchange rate will not cause any changes in stock prices (or vice versa), however, in banking sector the situation was different. This industry showed more reaction to these changes. The results are similar to the ones with Richards and Noel, where a variety of firms in different industries were evaluated.

Keywords: stock prices, foreign exchange rate, exchange rate exposure, Granger Causality

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Authors: Lela Mirtskhulava, Mariam Khunjgurua, Nino Lomineishvili, Koba Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability

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Authors: Emre Alan, Yusuf Yamanturk, Gokay Bas

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Non-grain oriented electrical steels are high silicon containing steels in which the direction of magnetism is intended the same in any direction of the material. Major applications of non-grain-oriented electrical steels are electrical motors, generators, etc. where low magnetic losses are required. Selection of proper hot rolling process parameters is an important factor in order to produce a material that has desired magnetic properties. In this study, the effect of finishing and coiling temperatures on magnetic properties of Fe-3%Si non-grain oriented electrical steels will be investigated. Additionally, the effect of slab reheating temperature at same entry finishing temperature will be investigated by means of reduction in roughing mill pass number from 1-5 to 1-3.

Keywords: electrical steels, hot rolling, magnetic properties, roughing mill

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Authors: Sayed Kifayat Shah, Tang Zhongjun, Arfa Tanveer

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This study explores the significant heatwave effect on stock return and volatility. Using an ARCH/GARCH approach, it examines the relationship between the heatwave of Karachi, Islamabad, and Lahore on the KSE-100 index. It also explores the impact of heatwave on returns of the pharmaceutical and electronics industries. The empirical results confirm that that stock return is positively related to the heat waves of Karachi, negatively related to that of Islamabad, and is not affected by the heatwave of Lahore. Similarly, pharmaceutical and electronics indices are also positively related to heatwaves. These differences in results can be ascribed to the change in the behavior of the residents of that city. The outcomes are useful for understanding an investor's behavior reacting to weather and fluxes in stock price related to heatwave severity levels. The results can support investors in fixing biases in behavior.

Keywords: ARCH/GARCH model, heat wave, KSE-100 index, stock market return

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Authors: E. Stepanova, N. Popov, S. Demakov, S. Stepanov

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This paper examines the so-called invar-type behavior of metastable titanium alloy subjected to cold rolling. The effect was shown to occur due to the anisotropy of thermal expansion of titanium orthorhombic martensite. By means of X-ray diffraction analysis and dilatometry analyses, the influence of crystallographic texture of orthorhombic martensite on the coefficient of thermal expansion of sheets of metastable titanium alloy VT23 was examined. Anisotropy of the coefficient of thermal expansion has been revealed. It was lower in the rolling plane and higher along the transverse direction of the cold-rolled sheet comparing to the coefficient of thermal expansion of the unprocessed alloy.

Keywords: invar-type, cold rolling, metastable titanium alloy, texture

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Authors: Thomas Chinwe Urama, Patrick Oseloka Ezepue, Peters Chimezie Nnanwa

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This paper investigates the universal financial dynamics in two dominant stock markets in Sub-Saharan Africa, through an in-depth analysis of the cross-correlation matrix of price returns in Nigerian Stock Market (NSM) and Johannesburg Stock Exchange (JSE), for the period 2009 to 2013. The strength of correlations between stocks is known to be higher in JSE than that of the NSM. Particularly important for modelling Nigerian derivatives in the future, the interactions of other stocks with the oil sector are weak, whereas the banking sector has strong positive interactions with the other sectors in the stock exchange. For the JSE, it is the oil sector and beverages that have greater sectorial correlations, instead of the banks which have the weaker correlation with other sectors in the stock exchange.

Keywords: random matrix theory, cross-correlations, emerging markets, option pricing, eigenvalues eigenvectors, inverse participation ratios and implied volatility

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Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

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Authors: Prateep Wajeetongratana

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The objectives of the research were to examine that how management accounting techniques were perceived and used by companies listed on the stock exchange and to investigate similarities or differences of management accounting practices between companies listed on the stock exchange and Thai SMEs. Descriptive and inferential statistics were employed. The finding found that almost all of the companies used traditional management accounting techniques more than advanced management accounting techniques. Four management accounting techniques having no significant association with business characteristic were standard costing, job order costing, process costing. The barriers that Thai SMEs encountered were a lack of proper accounting system and the insufficient knowledge in management accounting of the accountants. The comparison results revealed that both companies listed on the stock exchange and Thai SMEs used traditional management accounting techniques more than advanced techniques.

Keywords: companies listed on the stock exchange, financial budget, management accounting, operating budget

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Authors: Z. Sakka, I. Assakkaf, T. Al-Yaqoub, J. Parol

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A reliability-based methodology for the analysis assessment and evaluation of reinforced concrete structural elements of concrete structures is presented herein. The results of the reliability analysis and assessment for structural elements are verified by the results obtained from the deterministic methods. The analysis outcomes of reliability-based analysis are compared against the safety limits of the required reliability index β according to international standards and codes. The methodology is based on probabilistic analysis using reliability concepts and statistics of the main random variables that are relevant to the subject matter, and for which they are to be used in the performance-function equation(s) related to the structural elements under study. These methodology techniques can result in reliability index β, which is commonly known as the reliability index or reliability measure value that can be utilized to assess and evaluate the safety, human risk, and functionality of the structural component. Also, these methods can result in revised partial safety factor values for certain target reliability indices that can be used for the purpose of redesigning the reinforced concrete elements of the building and in which they could assist in considering some other remedial actions to improve the safety and functionality of the member.

Keywords: structural reliability, concrete structures, FORM, Monte Carlo simulation

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