Search results for: rolling stock reliability

Authors: Manel Youssef, Lotfi Belkacem

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This paper employs multivariate long memory GARCH models to simultaneously estimate mean and conditional variance spillover effects between oil prices and different financial markets. Since different financial assets are traded based on these market sector returns, it’s important for financial market participants to understand the volatility transmission mechanism over time and across these series in order to make optimal portfolio allocation decisions. We examine weekly returns from January 1, 2003 to November 30, 2012 and find evidence of significant transmission of shocks and volatilities between oil prices and some of the examined financial markets. The findings support the idea of cross-market hedging and sharing of common information by investors.

Keywords: oil prices, stock indices returns, oil volatility, contagion, DCC-multivariate (FI) GARCH

Procedia PDF Downloads 507

Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Wee Tong Liaw, Elaine Wong Yee Sing

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The main objective and focus of this study are to establish the significance of a sustained health promoting workplace on stock and portfolio returns focusing on companies listed on the Singapore stock exchange, using a two-factor model comprising of the single factor CAPM and a 'health promoting workplace' factor. The 'health promoting workplace' factor represents the excess returns derived between two portfolios of component stocks that, when combined, would represent a top tier stock market index in Singapore, namely the STI index. The first portfolio represents companies that are independently assessed by the Singapore’s Health Award, SHA, to have a sustained and comprehensive health promoting workplace (SHA-STI portfolio) and the second portfolio represents companies that had not been independently assessed (Non-SHA STI portfolio). Since 2001, many companies in Singapore have voluntarily participated in the bi-annual Singapore HEALTH Award initiated by the Health Promotion Board of Singapore (HPB). The Singapore HEALTH Award (SHA), is an industry-wide award and assessment process. SHA assesses and recognizes employers in Singapore for implementing a comprehensive and sustainable health promotion programme at their workplaces. When using a ten year holding period instead of a one year holding period, excess returns in the SHA-STI portfolio over Non-SHA STI portfolio were consistently being observed over all test periods, during 2001 to 2013. In addition, when applied to the SHA-STI portfolio, results from the Two Factor Model consistently revealed higher explanatory powers across all test periods for the portfolio as well as all the individual component stocks in SHA-STI portfolio, than the single factor CAPM model. However, with respect to attaining higher level of achievement in the Singapore Health Award, this study did not show any incentive for selecting listed companies that have achieved a higher level of award. Results from this study would give further insights to investors and fund managers alike who intend to consider health promoting workplace as a risk factor in their stock or portfolio selection process, in particular for investors who have a preference for STI’s component stocks and with a longer investment horizon. Key micro factors like management abilities, business development strategies and production capabilities that meet the needs of market would create the demand for a company’s product(s) or service(s) and consequently contribute to its top line and profitability. Thereafter, the existence of a sustainable health promoting workplace would be a key catalytic factor in sustaining a productive workforce needed to support the continued success of a profitable business.

Keywords: asset pricing model, company's performance, stock returns, financial risk factor, sustained health promoting workplace

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Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

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System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

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Authors: Idris Haruna Muhammad, Okorie Austine Uche

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This paper presents a study on reliability of shear connector exposed to fire situation in accordance with Eurocode 4. The reliability analysis i reliability analysis is based on First Order Second Moment Integration Technique (FOSMIT) using FORM 5. Performance functions for shear connector are derived for normal and under fire condition and their implied safety levels are evaluated. Four (4) design variables which include ultimate tensile strength, diameter of the stud, temperature and span of the steel beam are treated as random variables with their statistical characteristic adopted from literature. Results show that for normal condition the β – value decrease from 7.95 to 5.43 which show it is conservative in safety level for normal condition. Under fire condition, β – value decrease from 2.88 to – 0.32 with corresponding load ratio of 0.2 to 1.2. It was also shown from sensitivity assessment, that the temperature and span of the beam decrease with increase in their β – values while ultimate tensile strength and diameter of the stud increase with increase in their β – values for a given load ratio of 0.2 to 1.2.

Keywords: Composite steel beam, Fire condition, Shear stud, Sensitivity study

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Authors: Wael M. Bazzi, Amir Rastegarnia, Azam Khalili

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In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition.

Keywords: adaptive filter, distributed estimation, sensor network, IDLMS algorithm

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Authors: Sujit Kumar Pradhan, Anil Kumar, Vijay Kumar

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The testing process of the software during the software development time is a crucial step as it makes the software more efficient and dependable. To estimate software’s reliability through the mean value function, many software reliability growth models (SRGMs) were developed under the assumption that operating and testing environments are the same. Practically, it is not true because when the software works in a natural field environment, the reliability of the software differs. This article discussed an SRGM comprising change-point and imperfect debugging in a simulated testing environment. Later on, we extended it in a multi-release direction. Initially, the software was released to the market with few features. According to the market’s demand, the software company upgraded the current version by adding new features as time passed. Therefore, we have proposed a generalized multi-release SRGM where change-point and imperfect debugging concepts have been addressed in a simulated testing environment. The failure-increasing rate concept has been adopted to determine the change point for each software release. Based on nine goodness-of-fit criteria, the proposed model is validated on two real datasets. The results demonstrate that the proposed model fits the datasets better. We have also discussed the optimal release time of the software through a cost model by assuming that the testing and debugging costs are time-dependent.

Keywords: software reliability growth models, non-homogeneous Poisson process, multi-release software, mean value function, change-point, environmental factors

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Authors: Mustapha Kamel Mihoubi, Mohamed Essadik Kerkar

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Probabilistic risk analysis models are used to provide a better understanding of the reliability and structural failure of works, including when calculating the stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of reliability analysis methods including the methods used in engineering. It is in our case, the use of level 2 methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type first order risk method (FORM) and the second order risk method (SORM). By way of comparison, a level three method was used which generates a full analysis of the problem and involves an integration of the probability density function of random variables extended to the field of security using the Monte Carlo simulation method. Taking into account the change in stress following load combinations: normal, exceptional and extreme acting on the dam, calculation of the results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities, thus causing a significant decrease in strength, shear forces then induce a shift that threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case the increase of uplift in a hypothetical default of the drainage system.

Keywords: dam, failure, limit-state, monte-carlo, reliability, probability, simulation, sliding, taylor

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Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: V. V. Singh

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We have studied the reliability measures of a system, which consists of two subsystems i.e. subsystem-1 and subsystem-2 in series configuration under different types of failure. The subsystem-1 has three identical units in parallel configuration and operating under 2-out-of-3: G policy and connected to subsystem-2 in series configuration. Each subsystem has different types of failure and repair rates. An important cause for failure of system is unsuitability of the environmental conditions, like overheating, weather conditions, heavy rainfall, storm etc. The environmental failure is taken into account in the proposed repairable system. Supplementary variable technique is used to study of system and some traditional measures such as; availability, reliability, MTTF and profit function are obtained for different values of parameters. In the proposed model, some particular cases of failure rates are explicitly studied.

Keywords: environmental failure, human failure, availability, MTTF, reliability, profit analysis, Gumbel-Hougaard family copula

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Authors: Gökhan Polat, Dicle Kocaoğlu Yılmazer, Muhlis Nezihi Sarıdede

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Iron oxides are the main input to produce iron in integrated iron and steel plants. During production of iron from iron oxides, some wastes with high iron content occur. These main wastes can be classified as basic oxygen furnace (BOF) sludge, flue dust and rolling scale. Recycling of these wastes has a great importance for both environmental effects and reduction of production costs. In this study, recycling experiments were performed on basic oxygen furnace sludge, flue dust and rolling scale which contain 53.8%, 54.3% and 70.2% iron respectively. These wastes were mixed together with coke as reducer and these mixtures are pressed to obtain cylindrical briquettes. These briquettes were pressed under various compacting forces from 1 ton to 6 tons. Also, both stoichiometric and twice the stoichiometric cokes were added to investigate effect of coke amount on reduction properties of the waste mixtures. Then, these briquettes were reduced at 1000°C and 1100°C during 30, 60, 90, 120 and 150 min in a muffle furnace. According to the results of reduction experiments, the effect of compacting force, temperature and time on reduction ratio of the wastes were determined. It is found that 1 ton compacting force, 150 min reduction time and 1100°C are the optimum conditions to obtain reduction ratio higher than 75%.

Keywords: Coke, iron oxide wastes, recycling, reduction

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Authors: Nabil Mekaoui, Nacer Jabour, Abdelhamid Allaoui, Abderahim Oulidi

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The reliability of several insurance indexes of the seismic risk is evaluated and compared for an efficient seismic risk coverage of buildings in Morocco, thus, reducing the basic risk. A large database of earthquake ground motions is established from recent seismic events in Morocco and synthetic ground motions compatible with the design spectrum in order to conduct nonlinear time history analyses on three building models representative of the building stock in Morocco. The uninhabitability index is evaluated based on the simulated damage index, then correlated with preselected insurance indexes. Interestingly, the commonly used peak ground acceleration index showed poor correlation when compared with other indexes, such as spectral accelerations at low periods. Recommendations on the choice of suitable insurance indexes are formulated for efficient seismic risk coverage in Morocco.

Keywords: catastrophe modeling, damage, earthquake, reinsurance, seismic hazard, trigger index, vulnerability

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Authors: Henok Metaferia Gebremariam

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Worldwide, considerable resources are spent implementing public health interventions that are interrupted soon after the initial funding ends. However, ambiguity remains as to how health programs can be effectively sustained over time because of the diversity of perspectives, definitions, study methods, outcomes measures and timeframes. From all the above-mentioned research challenges, standardized measures of sustainability should ultimately become a key research issue. To resolve this key challenge, the objective of the study was to adapt a tool for measuring the program’s capacity for sustainability and evaluating its reliability and validity. To adapt and validate the tool, a cross-sectional and cohort study design was conducted at 26 programs in Addis Ababa between September 2014 and May 2015. An adapted version of the tool after the pilot test was administered to 220 staff. The tool was analyzed for reliability and validity. Results show that a 40-item PSAT tool had been adapted into the Amharic version with good internal consistency (Cronbach’s alpha= 0.80), test-retest reliability(r=0.916) and construct validity. Factor analysis resulted in 7 components explaining 56.67 % of the variance. In conclusion, it was found that the Amharic version of PAST was a reliable and valid tool for measuring the program’s capacity for sustainability.

Keywords: program sustainability, public health interventions, reliability, validity

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Authors: Nguyen Ngoc Que Tran

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Purpose: The purpose of this paper is to investigate the relationship between internal market orientation, external market orientation, employee commitment and job satisfaction. Design/methodology/approach: This study collected data through a survey and utilized simple linear regression and multiple regression analysis to determine if there was any support for the research hypotheses as presented in the previous chapter. Findings: Using data from 256 employees of four leading joint stock banks in Vietnam, the empirical results indicates that employee commitment is positively related with external market orientation, job satisfaction is positively related to employee commitment, and employee commitment and job satisfaction are positively related to external market orientation. However, job satisfaction has no significant positive effect on external market orientation. Theoretical contribution: The primary contribution to marketing theory arising from this study is the integration of job satisfaction, employee commitment, and external market orientation in a single research model. Practical implications: The major contribution to practice is an external market oriented bank has to respond rapidly to the future needs and preferences of its customers. This could result in high levels of commitment to the service process and in doing so provide Vietnamese joint-stock commercial banks with a competitive advantage. The finding is important for the banking service sector in general and the Vietnamese banking industry in particular.

Keywords: employee commitment, job satisfaction and external market orientation, vietnam, bank

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Authors: Ayşegül Bilge, Merve Uğuryol, Şeyda Dülgerler, Mustafa Yıldız

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The purpose of this research is to prove the Attitude towards Using Complementary Treatments Scale reliability and validity. The research is a methodological type of research that has been planned to determine the validity and reliability of the Attitude towards Using Complementary Treatments Scale. The scale has been developed by the researchers. In the scale, there are 23 questions including complementary and modern therapies individuals apply when they have health problems 4-item Likert-type evaluation has been carried out in preparing the questionnaire. High score obtained from the scale indicates a positive attitude towards complementary therapies. In the course of validity assessment of the scale, expert opinion has been received, and the content validity of the scale has been determined by using Kendall coefficient correlation test (Wa=0.200, p = 0.460). In the course of the reliability assessment of the scale, total score correlations of 23 materials have been examined, and those under 0.20 correlation limit has been removed from the scale correlation. As a result, the scale was left to be 13 items. In the internal consistency tests of the analyses, Cronbach's alpha value has been found to be 0.79. As a result, of the validity analyses of the Attitude towards Using Complementary Treatments Scale, the content and language validity analyses has been found to be at the expected level. It has been determined to be a highly reliable scale as the result of the reliability analyses. In conclusion, Attitude towards Using Complementary Treatments Scale is a valid and reliable scale.

Keywords: alternative health care, complementary treatment, instrument development, nursing practice

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Authors: S. L. Tulasi Devi, Shivam Azad

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The primary objective of this study is to analyze the impact of green bond issuance on the stock prices of respective Indian companies. An event study methodology has been employed to study the effect of green bond issuance. For in-depth study and analysis, this paper used different window frames, including 15-15 days, 10-10 days, 7-7days, 6-6 days, and 5-5 days. Further, for better clarity, this paper also used an uneven window period of 7-5 days. The period of study covered all the companies which issued green bonds during the period of 2017-2022; Adani Green Energy, State Bank of India, Power Finance Corporation, Jain Irrigation, and Rural Electrification Corporation, except Indian Renewable Energy Development Agency and Indian Railway Finance Corporation, because of data unavailability. The paper used all three event study methods as discussed in earlier literature; 1) constant return model, 2) market-adjusted model, and 3) capital asset pricing model. For the fruitful comparison between results, the study considered cumulative average return (CAR) and buy and hold average return (BHAR) methodology. For checking the statistical significance, a two-tailed t-statistic has been used. All the statistical calculations have been performed in Microsoft Excel 2016. The study found that all other companies have shown positive returns on the event day except for the State Bank of India. The results demonstrated that constant return model outperformed compared to the market-adjusted model and CAPM. The p-value derived from all the methods has shown an almost insignificant impact of the issuance of green bonds on the stock prices of respective companies. The overall analysis states that there’s not much improvement in the market efficiency of the Indian Stock Markets.

Keywords: green bonds, event study methodology, constant return model, market-adjusted model, CAPM

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Authors: Nabil Elkhatri, Mohamed Louay Metougui, Ngonidzashe Chirinda

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Mining activities have left a legacy of degraded landscapes, prompting urgent efforts for ecological restoration. Reforestation holds promise as a potent tool to rehabilitate these old mining sites, with the potential to sequester carbon and contribute to climate change mitigation. This study focuses on evaluating the carbon stock and sequestration potential of reforestation species in the context of Morocco's mining areas, employing the DeNitrification-DeComposition (DNDC) model. The research is grounded in recognizing the need to connect theoretical models with practical implementation, ensuring that reforestation efforts are informed by accurate and context-specific data. Field data collection encompasses growth patterns, biomass accumulation, and carbon sequestration rates, establishing an empirical foundation for the study's analyses. By integrating the collected data with the DNDC model, the study aims to provide a comprehensive understanding of carbon dynamics within reforested ecosystems on old mining sites. The major findings reveal varying sequestration rates among different reforestation species, indicating the potential for species-specific optimization of reforestation strategies to enhance carbon capture. This research's significance lies in its potential to contribute to sustainable land management practices and climate change mitigation strategies. By quantifying the carbon stock and sequestration potential of reforestation species, the study serves as a valuable resource for policymakers, land managers, and practitioners involved in ecological restoration and carbon management. Ultimately, the study aligns with global objectives to rejuvenate degraded landscapes while addressing pressing climate challenges.

Keywords: carbon stock, carbon sequestration, DNDC model, ecological restoration, mining sites, Morocco, reforestation, sustainable land management.

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Authors: Cameron Truong, Mikhail Bhatia, Yangyang Chen, Viet Nga Cao

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Using a sample of U.S. firms between 1996 and 2011, this paper documents a positive association between options trading volume and future stock price crash risk. This relation is evidently more pronounced among firms with higher information asymmetry, business uncertainty, and short-sale constraints. In a dichotomous cross-sectional setting, we also document that firms with options trading have higher future crash risk than firms without options trading. We further show in a difference-in-difference analysis that firms experience an increase in crash risk immediately after the listing of options. The results suggest that options traders are able of identifying bad news hoarding by management and choose to trade in a liquid options market in anticipation of future crashes.

Keywords: bad news hoarding, cross-sectional setting, options trading, stock price crash

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Authors: E. Ramprasath, P. Manojkumar, P. Veena

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DC motors have been widely used in the past centuries which are proudly known as the workhorse of industrial systems until the invention of the AC induction motors which makes a huge revolution in industries. Since then, the use of DC machines have been decreased due to enormous factors such as reliability, robustness and complexity but it lost its fame due to the losses. A new methodology is proposed to construct a DC motor through the simulation in LabVIEW to get an idea about its real time performances, if a change in parameter might have bigger improvement in losses and reliability.

Keywords: analysis, characteristics, direct current motor, LabVIEW software, simulation

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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In this study, three Chinese versions of the Achenbach systems of empirically based assessment (ASEBA) scales were used to examine adolescent psychological and behavioral problems. These three scales are CBCL, TRF, and YSR. In order to further understand the robustness of these scales, their reliability and construct validity have been examined. Each scale consists of about 113 items plus relevant background variables. These 113 items were further classified into 8 psychological and behavioral problems: emotionally reactive, anxious/depressed, somatic complaints, withdrawn, attention problems, aggressive behavior, social problems, thought problems, and association problems. The study explored the item and construct correlation relations and the correlations between the corresponding constructs among three scales. The results indicated that the associations between item and constructs varied. The construct validities were very robust.

Keywords: ASEBA, construct validity, psychological and behavioral problems, reliability

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Authors: A. Sohouli, A. Suleman

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This study focuses on reliability analysis of variable stiffness composite laminate structures to investigate the potential structural improvement compared to conventional (straight fibers) composite laminate structures. A computational framework was developed which it consists of a deterministic design step and reliability analysis. The optimization part is Discrete Material Optimization (DMO) and the reliability of the structure is computed by Monte Carlo Simulation (MCS) after using Stochastic Response Surface Method (SRSM). The design driver in deterministic optimization is the maximum stiffness, while optimization method concerns certain manufacturing constraints to attain industrial relevance. These manufacturing constraints are the change of orientation between adjacent patches cannot be too large and the maximum number of successive plies of a particular fiber orientation should not be too high. Variable stiffness composites may be manufactured by Automated Fiber Machines (AFP) which provides consistent quality with good production rates. However, laps and gaps are the most important challenges to steer fibers that effect on the performance of the structures. In this study, the optimal curved fiber paths at each layer of composites are designed in the first step by DMO, and then the reliability analysis is applied to investigate the sensitivity of the structure with different standard deviations compared to the straight fiber angle composites. The random variables are material properties and loads on the structures. The results show that the variable stiffness composite laminate structures are much more reliable, even for high standard deviation of material properties, than the conventional composite laminate structures. The reason is that the variable stiffness composite laminates allow tailoring stiffness and provide the possibility of adjusting stress and strain distribution favorably in the structures.

Keywords: material optimization, Monte Carlo simulation, reliability analysis, response surface method, variable stiffness composite structures

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Authors: Engy Eissa, Dina M. Yousri

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COVID-19 has hit massively the world economy, financial markets and even societies’ livelihood. The infectious disease caused by the most recently discovered coronavirus was claimed responsible for a shrink in the global economy by 4.4% in 2020. Shortly after the first case in Wuhan was identified, a quick surge in the number of confirmed cases in China was evident and a vast spread worldwide is recorded with cases surpassing the 500,000 cases. Irrespective of the disease’s trajectory in each country, a call for immediate action and prompt government intervention was needed. Given that there is no one-size-fits-all approach across the world, a number of containment and adoption policies were embraced. It was starting by enforcing complete lockdown like China to even stricter policies targeted containing the spread of the virus, augmenting the efficiency of health systems, and controlling the economic outcomes arising from this crisis. Hence, this paper has three folds; first, it examines the impact of containment policies taken by governments on controlling the number of cases and deaths in the given countries. Second, to assess the ramifications of COVID-19 on financial markets measured by stock returns. Third, to study the impact of containment policies measured by the government response index, the stringency index, the containment health index, and the economic support index on financial markets performance. Using a sample of daily data covering the period 31st of January 2020 to 15th of April 2021 for the 10 most hit countries in wave one by COVID-19 namely; Brazil, India, Turkey, Russia, UK, USA, France, Germany, Spain, and Italy. The aforementioned relationships were tested using Panel VAR Regression. The preliminary results showed that the number of daily deaths had an impact on the stock returns; moreover, the health containment policies and the economic support provided by the governments had a significant effect on lowering the impact of COVID-19 on stock returns.

Keywords: COVID-19, government policies, stock returns, VAR

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Authors: Gizem İntepe, Eti Mizrahi

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Investment and financing decisions are influenced by various economic features. Detailed analysis should be conducted in order to make decisions not only by companies but also by governments. Such analysis can be conducted either at the company level or on a sectoral basis to reduce risks and to maximize profits. Sectoral disaggregation caused by seasonality effects, subventions, data advantages or disadvantages may appear in sectors behaving parallel to BIST (Borsa Istanbul stock exchange) Index. Proposed logistic indices could serve market needs as a decision parameter in sectoral basis and also helps forecasting activities in import export volume changes. Also it is an indicator of logistic activity, which is also a sign of economic mobility at the national level. Publicly available data from “Ministry of Transport, Maritime Affairs and Communications” and “Turkish Statistical Institute” is utilized to obtain five logistics indices namely as; exLogistic, imLogistic, fLogistic, dLogistic and cLogistic index. Then, efficiency and reliability of these indices are tested.

Keywords: economic activity, export trade data, import trade data, logistics indices

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the newly developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: demand forecasting, machine learning, risk management, supply chain design

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Authors: Meida Laely Ramdani, Earmporn Thongkrajai, Dedy Purwito

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Lifestyle is one of the most important factors affecting health. Measurement of lifestyle behaviors is necessary for the identification of causal associations between unhealthy lifestyle and health outcomes. There was many instruments have been measured for lifestyle, but not specific for stroke recurrence. This study aimed to develop a new questionnaire of Lifestyle Adjustment Scale (LSAS) among recurrent stroke patients in Indonesia and to measure the reliability and validity of LSAS. The instrument consist of 33 items was developed from the responses of 30 recurrent stroke patients with the maximum age 60 years. Data was collected during October to November 2015. The properties of the instrument were evaluated by validity assessment and reliability measures. The content validity was judged adequate by a panel of five experts, with the result of I-CVI was 0.97. The Cronbach’s alpha analysis was carried out to measure the reliability of LSAS. The result showed that Cronbach’s alpha coefficient was 0.819. LSAS were classified under the domains of dietary habit, smoking habit, physical activity, and stress management. The results of Cronbach’s alpha coefficient for each subscale were 0.60, 0.39, 0.67, 0.65 and 0.76 respectively. LSAS instrument was valid and reliable therefore can be used as research tool among recurrent stroke patients. The development of this questionnaire has been adapted to the socio-cultural context in Indonesia.

Keywords: LSAS, recurrent stroke patients, lifestyle, Indonesia

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Authors: N. Tadayon, H. Yousefnia, S. Zolghadri, A. Ramazani, A. R. Jalilian

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Bone metastases occur in many patients with solid malignant tumors. Recently, 1,2 propylene di-amino tetra methylenephosphonic acid (PDTMP) has been introduced as a suitable carrier in the development of therapeutic bone-avid radiopharmaceuticals. In this study, due to the desirable characteristics of 68Ga, 68Ga-PDTMP was prepared. 68Ga was obtained from SnO2 based generator. A stock solution of PDTMP was prepared by dissolving in 2 N NaOH. A certain volume of the stock solution was added to the vial containing 68GaCl3 and the pH of the mixture was adjusted to 4 using HEPES. Radiochemical purity of the radiolabelled complex was checked by thin layer chromatography. 68Ga-PDTMP was prepared in only 15 min with radiochemical purity of more than 98%. This new bone-seeking complex can be considered as a good candidate of PET-based radiopharmaceutical for imaging of bone metastases.

Keywords: bone metastases, Ga-68, imaging, PDTMP

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Authors: Pawel Sowa, Joachim Bargiel

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This paper presents modern solutions of distributed generation in rural communities aiming at the improvement of energy and environmental security, as well as power supply reliability to important customers (e.g. health care, sensitive consumer required continuity). Distributed sources are mainly gas and biogas cogeneration units, as well as wind and photovoltaic sources. Some examples of their applications in a selected Silesian community are given.

Keywords: energy security, mini energy centres , power engineering, power supply reliability

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Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

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Authors: Yuta Chishima, Tatsuya Murakami, Michael McKay

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Temporal focus is described as one component of an individual’s time perspective and defined as the attention individuals devote to thinking about the past, present, and future. It affects how people incorporate perceptions about past experiences, current situations, and future expectations into their attitudes, cognitions, and behavior. The 12-item Temporal Focus Scale (TFS) is comprised of three-factors (past, current and future focus). The purpose of this study was to examine the reliability and validity of TFS scores in Japanese adolescents and young adults. The TFS was translated into Japanese by a professional translator, and the original author confirmed the back translated items. Study 1 involved 979 Japanese university students aged 18-25 years old in a questionnaire-based study. The hypothesized three-factor structure (with reliability) was confirmed, although there were problems with item 10. Internal consistency estimates for scores without item 10 were over .70, and test-retest reliability was also adequate. To verify the concurrent and convergent validity, we tested the relationship between TFS scores and life satisfaction, time perspective, self-esteem, and career efficacy. Results of correlational analyses supported our hypotheses. Specifically, future focus was strongly correlated to career efficacy, while past and current focus was not. Study 2 involved 1030 Japanese junior and junior high school students aged 12-18 years old in a questionnaire-based study, and results of multigroup analyses supported the age invariance of the TFS.

Keywords: Japanese, reliability, scale, temporal focus, validity

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Authors: Wilaiwan Sornpoon, Sébastien Bonnet, Savitri Garivait

Abstract:

Open burning of sugarcane fields is recognized to have a negative impact on soil by degrading its properties, especially soil organic carbon (SOC) content. Better understating the effect of open burning on soil carbon dynamics is crucial for documenting the carbon sequestration capacity of agricultural soils. In this study, experiments to investigate soil carbon stocks under burned and unburned sugarcane plantation systems in Thailand were conducted. The results showed that cultivation fields without open burning during 5 consecutive years enabled to increase the SOC content at a rate of 1.37 Mg ha-1y-1. Also it was found that sugarcane fields burning led to about 15% reduction of the total carbon stock in the 0-30 cm soil layer. The overall increase in SOC under unburned practice is mainly due to the large input of organic material through the use of sugarcane residues.

Keywords: soil organic carbon, soil inorganic carbon, carbon sequestration, open burning, sugarcane

Procedia PDF Downloads 278