Search results for: Malaysian market error
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5508

Search results for: Malaysian market error

4908 Predicting Recessions with Bivariate Dynamic Probit Model: The Czech and German Case

Authors: Lukas Reznak, Maria Reznakova

Abstract:

Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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4907 Stock Market Prediction by Regression Model with Social Moods

Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

Abstract:

This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

Procedia PDF Downloads 548
4906 Error Analysis of English Inflection among Thai University Students

Authors: Suwaree Yordchim, Toby J. Gibbs

Abstract:

The linguistic competence of Thai university students majoring in Business English was examined in the context of knowledge of English language inflection, and also various linguistic elements. Errors analysis was applied to the results of the testing. Levels of errors in inflection, tense and linguistic elements were shown to be significantly high for all noun, verb and adjective inflections. Findings suggest that students do not gain linguistic competence in their use of English language inflection, because of interlanguage interference. Implications for curriculum reform and treatment of errors in the classroom are discussed.

Keywords: interlanguage, error analysis, inflection, second language acquisition, Thai students

Procedia PDF Downloads 466
4905 Disruptive Innovation in Low-Income Countries: The Role of the Sharing Economy in Shaping the People Transportation Market in Nigeria

Authors: D. Tappi

Abstract:

In the past decades, the idea of innovation moved from being considered the result of development to being seen as its means. Innovation and its diffusion are indeed keys to the development and economic catch-up of a country. However, the process of diffusing existing innovation in low income countries has demonstrated dependent on inadequate infrastructures and institutions. The paper examines the role of disruptive innovation in bridging the technology gap between high- and low-income countries, overcoming the lack in infrastructures and institutions. In particular, the focus of this paper goes to the role of disruptive innovation in people transportation in Nigeria. Uber, Taxify, and Smartcab are covering a small and interesting market that was underserved, between the high-end private driver markets, the personal car owners and the low-priced traditional cab and the Keke (tricycle). Indeed the small Nigerian middle class and international community have found in the sharing people transportation market a safe, reasonably priced means of transportation in Nigerian big cities. This study uses mainly qualitative data collection methods in the form of semi-structured interviews with major players and users and quantitative data analysis in the form of a survey among users in order to assess the role of these new transportation modes in shaping the market and even creating a new niche. This paper shows how the new sharing economy in people transportation is creating new solutions to old problems as well as creating new challenges for both the existing market players and institutions. By doing so, the paper shows how disruptive innovations applied to low income countries, not only can overcome the lacking infrastructure problem but could also help bridge the technology gap between those and high income countries. This contribution proves that it is indeed exactly because the market presents these obstacles that disruptive innovations can succeed in countries such as Nigeria.

Keywords: development, disruptive innovation, sharing economy, technology gap

Procedia PDF Downloads 119
4904 Capital Market Reaction to Governance and Disclosure Violations: Evidence from the Saudi Arabian Capital Market

Authors: Nasser Alsadoun

Abstract:

Today's companies in Saudi Arabian capital market must comply with strict criteria and adhere to rigid corporate governance rules and continuous disclosure requirements. Unlike other regulators in the region, decision makers of the Capital Market Authority (hereafter CMA) of Saudi Arabia believes that the announcements of economic sanctions and penalties for non-compliance firms will foster more effective regulatory compliance and hence improve the quality of financial reporting. An implied argument put forward by the opponents, however, states that such penalties are unnecessary and stated to be onerous for non-compliance firms. Over that last years, the CMA has publicly announced several economic fines levied on some listed companies for their failing to comply with corporate governance and continuous disclosure regulation clauses, with the amount of fine levied ranges between 50,000 SR to 100,000 SR for each failing. Economic theory suggests that rational investors make decisions based on a cost-benefit principal. The regulatory intervention made by CMA on the announcement of economic sanctions has been costly to the society (economy) hoping that it improves the transparency of financial statements. It is argued, therefore, that threat of regulators and economic sanctions will provide incentives for firms’ managers to report more relevant and reliable accounting information, and the benefit of such announcements is likely to be reflected in the context of the quality of the financial reports. Yet, the economic consequences of the revealed fines announcement for non-compliance firms in Saudi Arabian market have not been examined. Thus, this study attempts to empirically examine whether market participants are pricing the supposed benefits of rigid governance and disclosure rules in the Saudi market. The study employs an event study methodology to assess the impact of CMA economic sanctions announcements on the market price of non-compliance firms. The study also estimates and examines bid–ask spread behavior of violated firms around the CMA announcements. The findings indicate that the CMA fines announcements for failing to comply with governance and disclosure rules do not appear to play any significant role in securities pricing. In addition, tests of bid-ask behavior does not indicate any significant increases in information asymmetry surrounding these announcements. While the CMA has developed many goals to increase the awareness of listed companies with the best governance and disclosure practices, it seems they have to develop more goals to improve market efficiency and increase investors and public awareness.

Keywords: governance and disclosure violations, financial reporting quality, regulatory intervention, market efficiency

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4903 Utilizing Grid Computing to Enhance Power Systems Performance

Authors: Rafid A. Al-Khannak, Fawzi M. Al-Naima

Abstract:

Power load is one of the most important controlling keys which decide power demands and illustrate power usage to shape power market. Hence, power load forecasting is the parameter which facilitates understanding and analyzing all these aspects. In this paper, power load forecasting is solved under MATLAB environment by constructing a neural network for the power load to find an accurate simulated solution with the minimum error. A developed algorithm to achieve load forecasting application with faster technique is the aim for this paper. The algorithm is used to enable MATLAB power application to be implemented by multi machines in the Grid computing system, and to accomplish it within much less time, cost and with high accuracy and quality. Grid Computing, the modern computational distributing technology, has been used to enhance the performance of power applications by utilizing idle and desired Grid contributor(s) by sharing computational power resources.

Keywords: DeskGrid, Grid Server, idle contributor(s), grid computing, load forecasting

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4902 Drivers and Barriers to the Acceptability of a Human Milk Bank Among Malaysians: A Cross Sectional Study

Authors: Kalaashini Ramachandran, Maznah Dahlui, Nik Daliana Nik Farid

Abstract:

WHO recommends all babies to be exclusively breastfed and donor milk is the next best alternative in the absence of mother’s own milk. The establishment of a human milk bank (HMB) is still being debated due to religious concerns in Malaysia leading to informal milk sharing practices, but little is known on the knowledge, attitude and perception of women towards HMB and its benefits. This study hypothesizes that there is no association between knowledge and attitude and the acceptance towards the establishment of human milk bank among Malaysian women and healthcare providers. The aim of this study is to determine the drivers and barriers among Malaysian towards the acceptance of an HMB. A cross-sectional study with 367 participants was enrolled within a period of 3 months to answer an online self-administered questionnaire. Data on sociodemographic, knowledge on breastfeeding benefits, knowledge and attitude on HMB and its specific issues were analyzed in terms of frequency and then proceed to multiple logistic regression. Majority of the respondents are of Islamis religion (73.3%), have succeesfully completed their tertiary education (82.8%), and are employed (70.8%). Only 55.9% of respondents have heard of an HMB stating internet as their main source of information but a higher prevalence is agreeable to the establishment of a human milk bank (67.8%). Most respondents have a good score on knowledge of breastfeeding benefits and on HMB specific issues (70% and 54.2% respectively) while 63.8% of them have a positive attitude towards HMB. In the multivariate analysis, mothers with a good score on general knowledge of breastfeeding (AOR: 1.715) were more likely to accept the establishment of an HMB while Islamic religion was negatively associated with its establishment (AOR:0.113). This study has found a high prevalence rate of mothers who are willing to accept the establishment of an HMB. This action can be potentially shaped by educating mothers on the benefits of breastfeeding as well as addressing their religious concerns so the establishment of a religiously abiding HMB in Malaysia may be accepted without compromising their belief or the health benefit of donor milk.

Keywords: acceptability, attitude, human milk bank, knowledge

Procedia PDF Downloads 102
4901 Marketing Strategy Adjustment of Multinational Companines in China in the New Period

Authors: Xue Junwei

Abstract:

The rapid economic development of China has made it a critical global market. Multinational companies operating in China face evolving challenges, necessitating adjustments in their marketing strategies. This study uses SWOT analysis and qualitative research methods to explore the trends and countermeasures for adjusting the marketing strategies of multinational companies in China. The research employs the SWOT analysis, quantitative as well as qualitative research techniques to investigate the marketing strategy adjustments of multinational companies in China. The study reveals emerging trends and proposes strategic countermeasures for multinational companies to adapt their marketing strategies in the Chinese market. This research contributes to the existing literature by providing insights into the dynamic environment of multinational companies in China and offering practical recommendations for strategy adjustments. Data were collected using qualitative research methods, including interviews and case studies, and quantitative research methods, such as questionnaires to study multinational companies in China. The collected data were analyzed using SWOT analysis to identify the strengths, weaknesses, opportunities, and threats faced by multinational companies in China, guiding the formulation of effective marketing strategies. This study addresses the challenges faced by multinational companies in China, the need for strategic adjustments, and the potential approaches to enhancing marketing effectiveness in this market. The study emphasizes the significance of adapting marketing strategies to align with the changing landscape of the Chinese market. It provides actionable recommendations for multinational companies to thrive in this environment.

Keywords: multinational company, marketing strategies, Chinese market, SWOT

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4900 Design and Test a Robust Bearing-Only Target Motion Analysis Algorithm Based on Modified Gain Extended Kalman Filter

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

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4899 Numerical Analysis of a Reaction Diffusion System of Lambda-Omega Type

Authors: Hassan J. Al Salman, Ahmed A. Al Ghafli

Abstract:

In this study, we consider a nonlinear in time finite element approximation of a reaction diffusion system of lambda-omega type. We use a fixed-point theorem to prove existence of the approximations at each time level. Then, we derive some essential stability estimates and discuss the uniqueness of the approximations. In addition, we employ Nochetto mathematical framework to prove an optimal error bound in time for d= 1, 2 and 3 space dimensions. Finally, we present some numerical experiments to verify the obtained theoretical results.

Keywords: reaction diffusion system, finite element approximation, stability estimates, error bound

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4898 Comparison of the Distillation Curve Obtained Experimentally with the Curve Extrapolated by a Commercial Simulator

Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

Abstract:

True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: distillation curve, petroleum distillation, simulation, true boiling point curve

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4897 Mathematical and Numerical Analysis of a Reaction Diffusion System of Lambda-Omega Type

Authors: Hassan Al Salman, Ahmed Al Ghafli

Abstract:

In this study we consider a nonlinear in time finite element approximation of a reaction diffusion system of lambda-omega type. We use a fixed point theorem to prove existence of the approximations. Then, we derive some essential stability estimates and discuss the uniqueness of the approximations. Also, we prove an optimal error bound in time for d=1, 2 and 3 space dimensions. Finally, we present some numerical experiments to verify the theoretical results.

Keywords: reaction diffusion system, finite element approximation, fixed point theorem, an optimal error bound

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4896 Improvement of Parallel Compressor Model in Dealing Outlet Unequal Pressure Distribution

Authors: Kewei Xu, Jens Friedrich, Kevin Dwinger, Wei Fan, Xijin Zhang

Abstract:

Parallel Compressor Model (PCM) is a simplified approach to predict compressor performance with inlet distortions. In PCM calculation, it is assumed that the sub-compressors’ outlet static pressure is uniform and therefore simplifies PCM calculation procedure. However, if the compressor’s outlet duct is not long and straight, such assumption frequently induces error ranging from 10% to 15%. This paper provides a revised calculation method of PCM that can correct the error. The revised method employs energy equation, momentum equation and continuity equation to acquire needed parameters and replace the equal static pressure assumption. Based on the revised method, PCM is applied on two compression system with different blades types. The predictions of their performance in non-uniform inlet conditions are yielded through the revised calculation method and are employed to evaluate the method’s efficiency. Validating the results by experimental data, it is found that although little deviation occurs, calculated result agrees well with experiment data whose error ranges from 0.1% to 3%. Therefore, this proves the revised calculation method of PCM possesses great advantages in predicting the performance of the distorted compressor with limited exhaust duct.

Keywords: parallel compressor model (pcm), revised calculation method, inlet distortion, outlet unequal pressure distribution

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4895 Aggregate Supply Response of Some Livestock Commodities in Algeria: Cointegration- Vector Error Correction Model Approach

Authors: Amine M. Benmehaia, Amine Oulmane

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The supply response of agricultural commodities to changes in price incentives is an important issue for the success of any policy reform in the agricultural sector. This study aims to quantify the responsiveness of producers of some livestock commodities to price incentives in Algerian context. Time series analysis is used on annual data for a period of 52 years (1966-2018). Both co-integration and vector error correction model (VECM) are used through the Nerlove model of partial adjustment. The study attempts to determine the long-run and short-run relationships along with the magnitudes of disequilibria in the selected commodities. Results show that the short-run price elasticities are low in cow and sheep meat sectors (8.7 and 8% respectively), while their respective long-run elasticities are 16.5 and 10.5, whereas eggs and milk have very high short-run price elasticities (82 and 90% respectively) with long-run elasticities of 40 and 46 respectively. The error correction coefficient, reflecting the speed of adjustment towards the long-run equilibrium, is statistically significant and have the expected negative sign. Its estimates are 12.7 for cow meat, 33.5 for sheep meat, 46.7 for eggs and 8.4 for milk. It seems that cow meat and milk producers have a weak feedback of about 12.7% and 8.4% respectively of the previous year's disequilibrium from the long-run price elasticity, whereas sheep meat and eggs producers adjust to correct long run disequilibrium with a high speed of adjustment (33.5% and 46.7 % respectively). The implication of this is that much more in-depth research is needed to identify those factors that affect agricultural supply and to describe the effect of factors that shift supply in response to price incentives. This could provide valuable information for government in the use of appropriate policy measures.

Keywords: Algeria, cointegration, livestock, supply response, vector error correction model

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4894 Portfolio Restructuring of Banks: The Impact on Performance and Risk

Authors: Hannes Koester

Abstract:

Driven by difficult market conditions and increasing regulations, many banks are making the strategic decision to restructure their portfolio by divesting several business segments. Using a unique dataset of 727 portfolio restructuring announcements by 161 international listed banks over the period 1999 to 2015, we investigate the impact of restructuring measurements on the stock performance as well as on the banks’ profitability and risk. Employing the event study methodology, we detect positive stock market reactions on the announcement of restructuring measurements. These positive stock market reactions indicate that shareholders reward banks’ specialization activities. However, the results of the system GMM regressions show a negative relation between restructuring measurements and banks’ return on assets and a positive relation towards the individual and systemic risk of banks. These empirical results indicate that there is no guarantee that portfolio restructurings will result in a more profitable and less risky institution.

Keywords: bank performance, bank risk, divestiture, restructuring, systemic risk

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4893 Continuous Differential Evolution Based Parameter Estimation Framework for Signal Models

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

Abstract:

In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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4892 An Association between Stock Index and Macro Economic Variables in Bangladesh

Authors: Shamil Mardi Al Islam, Zaima Ahmed

Abstract:

The aim of this article is to explore whether certain macroeconomic variables such as industrial index, inflation, broad money, exchange rate and deposit rate as a proxy for interest rate are interlinked with Dhaka stock price index (DSEX index) precisely after the introduction of new index by Dhaka Stock Exchange (DSE) since January 2013. Bangladesh stock market has experienced rapid growth since its inception. It might not be a very well-developed capital market as compared to its neighboring counterparts but has been a strong avenue for investment and resource mobilization. The data set considered consists of monthly observations, for a period of four years from January 2013 to June 2018. Findings from cointegration analysis suggest that DSEX and macroeconomic variables have a significant long-run relationship. VAR decomposition based on VAR estimated indicates that money supply explains a significant portion of variation of stock index whereas, inflation is found to have the least impact. Impact of industrial index is found to have a low impact compared to the exchange rate and deposit rate. Policies should there aim to increase industrial production in order to enhance stock market performance. Further reasonable money supply should be ensured by authorities to stimulate stock market performance.

Keywords: deposit rate, DSEX, industrial index, VAR

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4891 Design On Demand (DoD): Spiral Model of The Lifecycle of Products in The Personal 3D-Printed Products' Market

Authors: Zuk Nechemia Turbovich

Abstract:

This paper introduces DoD, a contextual spiral model that describes the lifecycle of products intended for manufacturing using Personal 3D Printers (P3DP). The study is based on a review of the desktop P3DPs market that shows that the combination of digital connectivity, coupled with the potential ownership of P3DP by home users, is radically changing the form of the product lifecycle, comparatively to familiar lifecycle paradigms. The paper presents the change in the design process, considering the characterization of product types in the P3DP market and the possibility of having a direct dialogue between end-user and product designers. The model, as an updated paradigm, provides a strategic perspective on product design and tools for success, understanding that design is subject to rapid and continuous improvement and that products are subject to repair, update, and customization. The paper will include a review of real cases.

Keywords: lifecycle, mass-customization, personal 3d-printing, user involvement

Procedia PDF Downloads 183
4890 Cellular Traffic Prediction through Multi-Layer Hybrid Network

Authors: Supriya H. S., Chandrakala B. M.

Abstract:

Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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4889 Transmission Network Expansion Planning in Deregulated Power Systems to Facilitate Competition under Uncertainties

Authors: Hooshang Mohammad Alikhani, Javad Nikoukar

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Restructuring and deregulation of power industry have changed the objectives of transmission expansion planning and increased the uncertainties. Due to these changes, new approaches and criteria are needed for transmission planning in deregulated power systems. The objective of this research work is to present a new approach for transmission expansion planning with considering new objectives and uncertainties in deregulated power systems. The approach must take into account the desires of all stakeholders in transmission expansion planning. Market based criteria must be defined to achieve the new objectives. Combination of market based criteria, technical criteria and economical criteria must be used for measuring the goodness of expansion plans to achieve market requirements, technical requirements, and economical requirements altogether.

Keywords: deregulated power systems, transmission network, stakeholder, energy systems

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4888 Profitability Assessment of Granite Aggregate Production and the Development of a Profit Assessment Model

Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an artificial neural network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R²), Root mean square error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: national development, granite, profitability assessment, ANN models

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4887 Improved Performance Scheme for Joint Transmission in Downlink Coordinated Multi-Point Transmission

Authors: Young-Su Ryu, Su-Hyun Jung, Myoung-Jin Kim, Hyoung-Kyu Song

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In this paper, improved performance scheme for joint transmission is proposed in downlink (DL) coordinated multi-point(CoMP) in case of constraint transmission power. This scheme is that serving transmission point (TP) request a joint transmission to inter-TP and selects one pre-coding technique according to channel state information(CSI) from user equipment(UE). The simulation results show that the bit error rate(BER) and throughput performances of the proposed scheme provide high spectral efficiency and reliable data at the cell edge.

Keywords: CoMP, joint transmission, minimum mean square error, zero-forcing, zero-forcing dirty paper coding

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4886 Prediction of Dubai Financial Market Stocks Movement Using K-Nearest Neighbor and Support Vector Regression

Authors: Abdulla D. Alblooshi

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The stock market is a representation of human behavior and psychology, such as fear, greed, and discipline. Those are manifested in the form of price movements during the trading sessions. Therefore, predicting the stock movement and prices is a challenging effort. However, those trading sessions produce a large amount of data that can be utilized to train an AI agent for the purpose of predicting the stock movement. Predicting the stock market price action will be advantageous. In this paper, the stock movement data of three DFM listed stocks are studied using historical price movements and technical indicators value and used to train an agent using KNN and SVM methods to predict the future price movement. MATLAB Toolbox and a simple script is written to process and classify the information and output the prediction. It will also compare the different learning methods and parameters s using metrics like RMSE, MAE, and R².

Keywords: KNN, ANN, style, SVM, stocks, technical indicators, RSI, MACD, moving averages, RMSE, MAE

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4885 Identification of Architectural Design Error Risk Factors in Construction Projects Using IDEF0 Technique

Authors: Sahar Tabarroki, Ahad Nazari

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The design process is one of the most key project processes in the construction industry. Although architects have the responsibility to produce complete, accurate, and coordinated documents, architectural design is accompanied by many errors. A design error occurs when the constraints and requirements of the design are not satisfied. Errors are potentially costly and time-consuming to correct if not caught early during the design phase, and they become expensive in either construction documents or in the construction phase. The aim of this research is to identify the risk factors of architectural design errors, so identification of risks is necessary. First, a literature review in the design process was conducted and then a questionnaire was designed to identify the risks and risk factors. The questions in the form of the questionnaire were based on the “similar service description of study and supervision of architectural works” published by “Vice Presidency of Strategic Planning & Supervision of I.R. Iran” as the base of architects’ tasks. Second, the top 10 risks of architectural activities were identified. To determine the positions of possible causes of risks with respect to architectural activities, these activities were located in a design process modeled by the IDEF0 technique. The research was carried out by choosing a case study, checking the design drawings, interviewing its architect and client, and providing a checklist in order to identify the concrete examples of architectural design errors. The results revealed that activities such as “defining the current and future requirements of the project”, “studies and space planning,” and “time and cost estimation of suggested solution” has a higher error risk than others. Moreover, the most important causes include “unclear goals of a client”, “time force by a client”, and “lack of knowledge of architects about the requirements of end-users”. For error detecting in the case study, lack of criteria, standards and design criteria, and lack of coordination among them, was a barrier, anyway, “lack of coordination between architectural design and electrical and mechanical facility”, “violation of the standard dimensions and sizes in space designing”, “design omissions” were identified as the most important design errors.

Keywords: architectural design, design error, risk management, risk factor

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4884 Feature Location Restoration for Under-Sampled Photoplethysmogram Using Spline Interpolation

Authors: Hangsik Shin

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The purpose of this research is to restore the feature location of under-sampled photoplethysmogram using spline interpolation and to investigate feasibility for feature shape restoration. We obtained 10 kHz-sampled photoplethysmogram and decimated it to generate under-sampled dataset. Decimated dataset has 5 kHz, 2.5 k Hz, 1 kHz, 500 Hz, 250 Hz, 25 Hz and 10 Hz sampling frequency. To investigate the restoration performance, we interpolated under-sampled signals with 10 kHz, then compared feature locations with feature locations of 10 kHz sampled photoplethysmogram. Features were upper and lower peak of photplethysmography waveform. Result showed that time differences were dramatically decreased by interpolation. Location error was lesser than 1 ms in both feature types. In 10 Hz sampled cases, location error was also deceased a lot, however, they were still over 10 ms.

Keywords: peak detection, photoplethysmography, sampling, signal reconstruction

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4883 Effect of Non-Tariff Measures to Indonesian Shrimp Export in International Market: Case of Sanitary and Phytosanitary and Technical Barriers to Trade

Authors: Muhammad Khaliqi, Amzul Rifin, Andriyono Kilat Adhi

Abstract:

The non-tariff policy could make Indonesian shrimp exports decrease in the international market. This research was aimed to analyze factors affecting Indonesia's exports of shrimp and the impact of SPS and TBT policy on Indonesian shrimp. Factors affecting the exports of Indonesian shrimp were estimated using gravity model. The results showed the GDP of exporters and exchange rate, have a negative influence against the export of Indonesia’s shrimp exports. The GDP of the importers and trade cost have a positive influence against the export of shrimp Indonesia while the SPS policy and TBT don’t affect Indonesia's exports of shrimp in the international market.

Keywords: gravity model, international trade, non-tariff measure, sanitary and phytosanitary, shrimp, technical barriers to trade

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4882 Maximum Initial Input Allowed to Iterative Learning Control Set-up Using Singular Values

Authors: Naser Alajmi, Ali Alobaidly, Mubarak Alhajri, Salem Salamah, Muhammad Alsubaie

Abstract:

Iterative Learning Control (ILC) known to be a controlling tool to overcome periodic disturbances for repetitive systems. This technique is required to let the error signal tends to zero as the number of operation increases. The learning process that lies within this context is strongly dependent on the initial input which if selected properly tends to let the learning process be more effective compared to the case where a system starts from blind. ILC uses previous recorded execution data to update the following execution/trial input such that a reference trajectory is followed to a high accuracy. Error convergence in ILC is generally highly dependent on the input applied to a plant for trial $1$, thus a good choice of initial starting input signal would make learning faster and as a consequence the error tends to zero faster as well. In the work presented within, an upper limit based on the Singular Values Principle (SV) is derived for the initial input signal applied at trial $1$ such that the system follow the reference in less number of trials without responding aggressively or exceeding the working envelope where a system is required to move within in a robot arm, for example. Simulation results presented illustrate the theory introduced within this paper.

Keywords: initial input, iterative learning control, maximum input, singular values

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4881 The Non-Existence of Perfect 2-Error Correcting Lee Codes of Word Length 7 over Z

Authors: Catarina Cruz, Ana Breda

Abstract:

Tiling problems have been capturing the attention of many mathematicians due to their real-life applications. In this study, we deal with tilings of Zⁿ by Lee spheres, where n is a positive integer number, being these tilings related with error correcting codes on the transmission of information over a noisy channel. We focus our attention on the question ‘for what values of n and r does the n-dimensional Lee sphere of radius r tile Zⁿ?’. It seems that the n-dimensional Lee sphere of radius r does not tile Zⁿ for n ≥ 3 and r ≥ 2. Here, we prove that is not possible to tile Z⁷ with Lee spheres of radius 2 presenting a proof based on a combinatorial method and faithful to the geometric idea of the problem. The non-existence of such tilings has been studied by several authors being considered the most difficult cases those in which the radius of the Lee spheres is equal to 2. The relation between these tilings and error correcting codes is established considering the center of a Lee sphere as a codeword and the other elements of the sphere as words which are decoded by the central codeword. When the Lee spheres of radius r centered at elements of a set M ⊂ Zⁿ tile Zⁿ, M is a perfect r-error correcting Lee code of word length n over Z, denoted by PL(n, r). Our strategy to prove the non-existence of PL(7, 2) codes are based on the assumption of the existence of such code M. Without loss of generality, we suppose that O ∈ M, where O = (0, ..., 0). In this sense and taking into account that we are dealing with Lee spheres of radius 2, O covers all words which are distant two or fewer units from it. By the definition of PL(7, 2) code, each word which is distant three units from O must be covered by a unique codeword of M. These words have to be covered by codewords which dist five units from O. We prove the non-existence of PL(7, 2) codes showing that it is not possible to cover all the referred words without superposition of Lee spheres whose centers are distant five units from O, contradicting the definition of PL(7, 2) code. We achieve this contradiction by combining the cardinality of particular subsets of codewords which are distant five units from O. There exists an extensive literature on codes in the Lee metric. Here, we present a new approach to prove the non-existence of PL(7, 2) codes.

Keywords: Golomb-Welch conjecture, Lee metric, perfect Lee codes, tilings

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4880 Restriction on the Freedom of Economic Activity in the Polish Energy Law

Authors: Zofia Romanowska

Abstract:

Recently there have been significant changes in the Polish energy market. Due to the government's decision to strengthen energy security as well as to strengthen the implementation of the European Union common energy policy, the Polish energy market has been undergoing significant changes. In the face of these, it is necessary to answer the question about the direction the Polish energy rationing sector is going, how wide apart the powers of the state are and also whether the real regulator of energy projects in Poland is not in fact the European Union itself. In order to determine the role of the state as a regulator of the energy market, the study analyses the basic instruments of regulation, i.e. the licenses, permits and permissions to conduct various activities related to the energy market, such as the production and sale of liquid fuels or concessions for trade in natural gas. Bearing in mind that Polish law is part of the widely interpreted European Union energy policy, the legal solutions in neighbouring countries are also being researched, including those made in Germany, a country which plays a key role in the shaping of EU policies. The correct interpretation of the new legislation modifying the current wording of the Energy Law Act, such as obliging the entities engaged in the production and trade of liquid fuels (including abroad) to meet a number of additional requirements for the licensing and providing information to the state about conducted business, plays a key role in the study. Going beyond the legal framework for energy rationing, the study also includes a legal and economic analysis of public and private goods within the energy sector and delves into the subject of effective remedies. The research caused the relationships between progressive rationing introduced by the legislator and the rearrangement rules prevailing on the Polish energy market to be taken note of, which led to the introduction of greater transparency in the sector. The studies refer to the initial conclusion that currently, despite the proclaimed idea of liberalization of the oil and gas market and the opening of market to a bigger number of entities as a result of the newly implanted changes, the process of issuing and controlling the conduction of the concessions will be tightened, guaranteeing to entities greater security of energy supply. In the long term, the effect of the introduced legislative solutions will be the reduction of the amount of entities on the energy market. The companies that meet the requirements imposed on them by the new regulation to cope with the profitability of the business will in turn increase prices for their services, which will be have an impact on consumers' budgets.

Keywords: license, energy law, energy market, public goods, regulator

Procedia PDF Downloads 246
4879 Assessment of Time-variant Work Stress for Human Error Prevention

Authors: Hyeon-Kyo Lim, Tong-Il Jang, Yong-Hee Lee

Abstract:

For an operator in a nuclear power plant, human error is one of the most dreaded factors that may result in unexpected accidents. The possibility of human errors may be low, but the risk of them would be unimaginably enormous. Thus, for accident prevention, it is quite indispensable to analyze the influence of any factors which may raise the possibility of human errors. During the past decades, not a few research results showed that performance of human operators may vary over time due to lots of factors. Among them, stress is known to be an indirect factor that may cause human errors and result in mental illness. Until now, not a few assessment tools have been developed to assess stress level of human workers. However, it still is questionable to utilize them for human performance anticipation which is related with human error possibility, because they were mainly developed from the viewpoint of mental health rather than industrial safety. Stress level of a person may go up or down with work time. In that sense, if they would be applicable in the safety aspect, they should be able to assess the variation resulted from work time at least. Therefore, this study aimed to compare their applicability for safety purpose. More than 10 kinds of work stress tools were analyzed with reference to assessment items, assessment and analysis methods, and follow-up measures which are known to close related factors with work stress. The results showed that most tools mainly focused their weights on some common organizational factors such as demands, supports, and relationships, in sequence. Their weights were broadly similar. However, they failed to recommend practical solutions. Instead, they merely advised to set up overall counterplans in PDCA cycle or risk management activities which would be far from practical human error prevention. Thus, it was concluded that application of stress assessment tools mainly developed for mental health seemed to be impractical for safety purpose with respect to human performance anticipation, and that development of a new assessment tools would be inevitable if anyone wants to assess stress level in the aspect of human performance variation and accident prevention. As a consequence, as practical counterplans, this study proposed a new scheme for assessment of work stress level of a human operator that may vary over work time which is closely related with the possibility of human errors.

Keywords: human error, human performance, work stress, assessment tool, time-variant, accident prevention

Procedia PDF Downloads 671