Search results for: Measurement of Market Orientation

Authors: Tina Vuko, Marija Maretić, Marko Čular

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The aim of this study is to analyze the role and effectiveness of internal mechanism (audit committee) of corporate governance on credit institutions performance in Croatia. Based on research objective, sample of 78 credit institutions listed on Zagreb Stock Exchange, from 2007 to 2012, has been collected and efficiency index of audit committee (EIAC) has been created. Based on the sample and created EIAC, conclusions are as follows: audit committees of credit institutions have medium efficiency, based on EIAC measurement; there is a significant difference in audit committee effectiveness, in observed period; there is no positive relationship between audit committee effectiveness and credit institution performance; there is a significant difference between level of audit committee effectiveness and audit firm type. Future research should contain increased number of elements in EIAC creation and increased sample, for all obligators who need to establish audit committee.

Keywords: Corporate Governance, Audit Committee, Financial Institutions, Efficiency Index of Audit Committee.

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: Prediction of financial markets, Adaptive methods, MSE, LSE.

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Authors: Tanyatorn Panyasopon

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Many Thai movies have been very popular domestically and internationally. Some movies were box office hits and receiving awards. However, there has not yet been research about how Thai movies can sell in international markets The objectives of the research were 1) To analyze the characteristics of Thai movies that can sell to world audiences; 2) To investigate the factors making Thai movies into foreign markets. Thai film professionals were interviewed. Their ideas were analyzed to find out what factors contributing to Thai movies widely seen in worldwide markets. Nine foreign audiences were also interviewed to reveal what characteristics of Thai movies would be well accepted by the markets. The results showed that major characteristics of Thai movies proving successful worldwide were cultural and exotic Thai movies, outstanding genres, well-known actors, music and songs. Factors contributing to global market were marketing, qualities of Thai movies, and financial support from the government.

Keywords: Characteristics, factors, international markets, Thai movies.

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Authors: Yi-Chang Chen, Shan-Lin Chang, Chia-Chun Wu

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Unlike this study focused extensively on trading behavior of option market, those researches were just taken their attention to model-driven option pricing. For example, Black-Scholes (B-S) model is one of the most famous option pricing models. However, the arguments of B-S model are previously mentioned by some pricing models reviewing. This paper following suggests the importance of the dynamic character for option pricing, which is also the reason why using the genetic algorithm (GA). Because of its natural selection and species evolution, this study proposed a hybrid model, the Genetic-BS model which combining GA and B-S to estimate the price more accurate. As for the final experiments, the result shows that the output estimated price with lower MAE value than the calculated price by either B-S model or its enhanced one, Gram-Charlier garch (G-C garch) model. Finally, this work would conclude that the Genetic-BS pricing model is exactly practical.

Keywords: genetic algorithm, Genetic-BS, option pricing model.

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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Authors: María Teresa García-Álvarez, Isabel Soares, Rosa María Mariz-Pérez

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Directive 2009/28/CE establishes, as obligatory objective, a share of renewable energies on energetic consumption of 20%, in European Union, in 2020 However, such European normative gives freedom to member states in the selection of the renewable promotion mechanism that allows them to obtain that objective. In this paper, we analyze the main characteristics of the promotion mechanisms of renewable energy used in the countries that shape the Electricity Iberian Market (Spain and Portugal) and the results in employment. The importance of these countries is given by the great increasing of the renewable energies which suppose a share higher than 30% of the overall generation in 2010. Therefore, this research paper can serve as the basis for the learning of other countries with regard to the main advantages that entail the use of a feed-in tariff system.

Keywords: Employment, Energy policy, Professional profiles, Renewable energies, Professional profiles.

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Authors: Wissem Saidani, Yacine Morsly, Mohand Saïd Djouadi

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In this paper, we consider the problem of tracking multiple maneuvering targets using switching multiple target motion models. With this paper, we aim to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to avoid the Extended Kalman filter because of its limitations and substitute it with the Unscented Kalman filter which seems to be more efficient especially according to the simulation results obtained with the nonlinear IMM algorithm (IMMUKF). To resolve the problem of data association, the JPDA approach is combined with the IMM-UKF algorithm, the derived algorithm is noted JPDA-IMM-UKF.

Keywords: Estimation, Kalman filtering, Multi-Target Tracking, Visual servoing, data association.

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Authors: Thanapol Wisuttikul, Choochart Haruechaiyasak, Santipong Thaiprayoon

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Thailand has evolved many unique culture and knowledge, and the leading is the Thai traditional medicine (TTM). Recently, a number of researchers have tried to save this indigenous knowledge. However, the system to do so has still been scant. To preserve this ancient knowledge, we therefore invented and integrated multi-linguistic techniques to create the system of the collected all of recipes. This application extracted the medical recipes from antique scriptures then normalized antiquarian words, primitive grammar and antiquated measurement of them to the modern ones. Then, we applied ingredient-duplication-calculation, proportion-similarity-calculation and score-ranking to examine duplicate recipes. We collected the questionnaires from registrants and people to investigate the users’ satisfaction. The satisfactory results were found. This application assists not only registrants to validating the copyright violation in TTM registration process but also people to cure their illness that aids both Thai people and all mankind to fight for intractable diseases.

Keywords: Medicine Registration, Search Engine, Text Approximation, Traditional Medicine.

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Authors: Charalampos Saridakis, Stelios Tsafarakis

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Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.

Keywords: Clean-fuel vehicles, product line design, conjoint analysis, choice experiment, differential evolution.

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Authors: Florian Müller, Christian Kukla, Thomas Lucyshyn, Clemens Holzer

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In this paper, the influencing parameters of a novel purely mechanical wireless in-mould injection moulding sensor were investigated. The sensor is capable of detecting the melt front at predefined locations inside the mould. The sensor comprises a movable pin which acts as the sensor element generating structure-borne sound triggered by the passing melt front. Due to the sensor design, melt pressure is the driving force. For pressure level measurement during pin movement a pressure transducer located at the same position as the movable pin. By deriving a mathematical model for the mechanical movement, dominant process parameters could be investigated towards their impact on the melt front detection characteristic. It was found that the sensor is not affected by the investigated parameters enabling it for reliable melt front detection. In addition, it could be proved that the novel sensor is in comparable range to conventional melt front detection sensors.

Keywords: Injection Moulding, In-Mould Sensor, Structure-Borne Sound, Wireless Sensor

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Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

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Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.

Keywords: Complex adaptive systems, X-events, risk management, antifragility, banking antifragility index, triangular fuzzy number.

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices over the past five years of 10 major tech companies: Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We implemented and tested three models – a linear regressor model, a k-nearest neighbor model (KNN), and a sequential neural network – and two algorithms – Multiplicative Weight Update and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: Finance, machine learning, opening price, stock market.

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Authors: Ivan C. Mustakerov, Daniela I. Borissova

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In recent years, new product development became more and more competitive and globalized, and the designing phase is critical for the product success. The concept of modularity can provide the necessary foundation for organizations to design products that can respond rapidly to market needs. The paper describes data structures and algorithms of intelligent Web-based system for modular design taking into account modules compatibility relationship and given design requirements. The system intelligence is realized by developed algorithms for choice of modules reflecting all system restrictions and requirements. The proposed data structure and algorithms are illustrated by case study of personal computer configuration. The applicability of the proposed approach is tested through a prototype of Web-based system.

Keywords: Data structures, algorithms, intelligent web-based system, modular design.

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Authors: Huseyin Cetin, Halil Akmese, Sercan Aras, Vahit Aytekin

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Economic crisis, terrorism, global crisis and the relations between countries are the factors affecting tourism industry and tourism industry is vulnerable against these factors. In our study, there are two dimensions about Russian crisis. The crisis between Russia and Ukraine and decreased oil prices in global market have been entailed Russian economic crisis. This crisis has induced that the ruble, Russian currency, has depreciated against American dollars and consequently the purchasing power of Russian has weakened. This is the first dimension of our study. Second dimension is a political crisis between Turkey and Russia owing to the fact that the Russian Warcraft was brought down by Turkish army. The aim of this study is to explain the impact of the consequences of Russian crisis on Turkish tourism industry. The study has been limited only Antalya province.

Keywords: Economic crisis, Turkey-Russian crisis, Turkey's tourism industry, tourism in Turkey.

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Authors: Ana Bobirca, Paul-Gabriel Miclaus

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International competitiveness receives much attention nowadays, but up to now its assessment has been heavily based on manufacturing industry statistics. This paper addresses the need for competitiveness indicators that cover the service sector and sets out a multilevel framework for measuring international services trade competitiveness. The approach undertaken here aims at comparatively examining the international competitiveness of the EU-25 (the twenty-five European Union member states before the 1st of January 2007), Romanian and Bulgarian services trade, as well as the last two countries- structure of specialization on the EU-25 services market. The primary changes in the international competitiveness of three major services sectors – transportation, travel and other services - are analyzed. This research attempts to determine the ability of the two recent European Union (EU) member states to contend with the challenges that might arise from the hard competition within the enlarged EU, in the field of services trade.

Keywords: Bulgaria, EU-25, international competitiveness, international services trade, Romania.

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Authors: Dmitry A. Mikoyelov

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The paper presents a set of guidelines for analysis of industrial embedded distributed systems and introduces a mathematical model derived from these guidelines. In this study, the author examines a set of modern communication technologies that are or possibly can be used to build communication links between the subsystems of a distributed embedded system. An investigation of these guidelines results in a algorithm for analysis of specific use cases of target technologies. A goal of the paper acts as an important base for ongoing research on comparison of communication technologies. The author describes the principles of the model and presents results of the test calculations. Practical implementation of target technologies and empirical experiment data are based on a practical experience during the design and test of specific distributed systems in Latvian market.

Keywords: Distributed embedded system, analytical model, communication technology.

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Authors: Jan Busch, Maurice Schmidt, Peter Nyhuis

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The change of conditions for production companies in high-wage countries is characterized by the globalization of competition and the transition of a supplier´s to a buyer´s market. The companies need to face the challenges of reacting flexibly to these changes. Due to the significant and increasing degree of automation, assembly has become the most expensive production process. Regarding the reduction of production cost, assembly consequently offers a considerable rationalizing potential. Therefore, an aerodynamic feeding system has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. This system has been enabled to adjust itself by using a genetic algorithm. The longer this genetic algorithm is executed the better is the feeding quality. In this paper, the relation between the system´s setting time and the feeding quality is observed and a function which enables the user to achieve the minimum of the total feeding time is presented.

Keywords: Aerodynamic feeding system, batch size, optimisation, setting time.

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Authors: Khaled M. EL-Naggar

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Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.

Keywords: Optimization, estimation, synchronous, machine, crow search.

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Authors: Sayali Sandbhor, Ravindra Bapat, N. B. Chaphalkar

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Decisions for investment, buying and selling of properties depend upon the market value of that property. Issues arise in arriving at the actual value of the property as well as computing the rate of returns from the estate. Addressing valuation related issues through an understanding of behavior of real property rates provide the means to explore the quality of past decisions and to make valid future decisions. Pune, an important city in India, has witnessed a high rate of growth in past few years. Increased demand for housing and investment in properties has led to increase in the rates of real estate. An attempt has been made to study the change and behavior of rates of real estate and factors influencing the same in Pune city.

Keywords: Real estate, valuation, property rates, trend analysis

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Authors: Vesna Vulić

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Croatia has made large steps forward in the development of higher education over the past 10 years. Purposes and objectives of the tertiary education system are focused on the personal development of young people so that they obtain competences for employment on a flexible labour market. The most frequent tensions between the tertiary institutions and employers are complaints that the current tertiary education system still supplies students with an abundance of theoretical knowledge and not enough practical skills. Polytechnics and schools of professional higher education should deliver professional education and training that will satisfy the needs of their local communities. The 21^st century sets demand on undergraduates as well as their lecturers to strive for the highest standards. The skills students acquire during their studies should serve the needs of their future professional careers. In this context, teaching English for Specific Purposes (ESP) presents an enormous challenge for teachers. They have to cope with teaching the language in classes with a large number of students, limitations of time, inadequate equipment and teaching material; most frequently, this leads to focusing on specialist vocabulary neglecting the development of skills and competences required for future employment. Globalization has transformed the labour market and set new standards a perspective employee should meet. When knowledge of languages is considered, new generic skills and competences are required. Not only skillful written and oral communication is needed, but also information, media, and technology literacy, learning skills which include critical and creative thinking, collaborating and communicating, as well as social skills. The aim of this paper is to evaluate the needs of two groups of ESP first year Undergraduate Professional Administrative Study students taking ESP as a mandatory course: 47 first-year Undergraduate Professional Administrative Study students, 21 first-year employed part-time Undergraduate Professional Administrative Study students and 30 graduates with a degree in Undergraduate Professional Administrative Study with various amounts of work experience. The survey adopted a quantitative approach with the aim to determine the differences between the groups in their perception of the four language skills and different areas of law, as well as getting the insight into students' satisfaction with the current course and their motivation for studying ESP. Their perceptions will be compared to the results of the questionnaire conducted among sector professionals in order to examine how they perceive the same elements of the ESP course content and to what extent it fits into their working environment. The results of the survey indicated that there is a strong correlation between acquiring work experience and the level of importance given to particular areas of law studied in an ESP course which is in line with our initial hypothesis. In conclusion, the results of the survey should help lecturers in re-evaluating and updating their ESP course syllabi.

Keywords: English for Specific Purposes, ESP, language skills, motivation, needs analysis.

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Authors: Pei-Ju Chao, Tsair-Fwu Lee, Wei-Luen Huang, Long-Chang Chen, Te-Jen Su, Wen-Ping Chen

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The main goal in this paper is to quantify the quality of different techniques for radiation treatment plans, a back-propagation artificial neural network (ANN) combined with biomedicine theory was used to model thirteen dosimetric parameters and to calculate two dosimetric indices. The correlations between dosimetric indices and quality of life were extracted as the features and used in the ANN model to make decisions in the clinic. The simulation results show that a trained multilayer back-propagation neural network model can help a doctor accept or reject a plan efficiently. In addition, the models are flexible and whenever a new treatment technique enters the market, the feature variables simply need to be imported and the model re-trained for it to be ready for use.

Keywords: neural network, dosimetric index, radiation treatment, tumor

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Authors: Reinhard Haas, Amela Ajanovic

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In recent years various types of electric vehicles has gained again increasing attention as an environmentally benign technology in transport. Especially for urban areas with high local pollution this Zero-emission technology (at the point of use) is considered to provide proper solutions. Yet, the bad economics and the limited driving ranges are still major barriers for a broader market penetration of battery electric vehicles (BEV) and of fuel cell vehicles (FCV). The major result of our analyses is that the most important precondition for a further dissemination of BEV in urban areas are emission-free zones. This is an instrument which allows the promotion of BEV without providing excessive subsidies. In addition, it is important to note that the full benefits of EV can only be harvested if the electricity used is produced from renewable energy sources. That is to say, it has to be ensured that the use of BEV in urban areas is clearly linked to a green electricity purchase model. And moreover, the introduction of a CO2- emission-based tax system would support this requirement.

Keywords: Electric vehicles, economics, policies, history.

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Authors: Svetlana Saksonova

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Every commercial bank optimises its asset portfolio depending on the profitability of assets and chosen or imposed constraints. This paper proposes and applies a stylized model for optimising banks' asset and liability structure, reflecting profitability of different asset categories and their risks as well as costs associated with different liability categories and reserve requirements. The level of detail for asset and liability categories is chosen to create a suitably parsimonious model and to include the most important categories in the model. It is shown that the most appropriate optimisation criterion for the model is the maximisation of the ratio of net interest income to assets. The maximisation of this ratio is subject to several constraints. Some are accounting identities or dictated by legislative requirements; others vary depending on the market objectives for a particular bank. The model predicts variable amount of assets allocated to loan provision.

Keywords: asset structure, commercial bank, model, optimisation

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Authors: Chien-Hua Wang, Wei-Hsuan Lee, Chin-Tzong Pang

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In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.

Keywords: Data mining, association rule, fuzzy frequent patterngrowth.

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Authors: Alexander A. Karabutov, Natalia B. Podymova, Elena B. Cherepetskaya, Vladimir A. Makarov, Yulia G. Sokolovskaya

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The laser-ultrasonic method is realized for quantifying the influence of porosity on the local Young’s modulus of isotropic composite materials. The method is based on a laser thermooptical method of ultrasound generation combined with measurement of the phase velocity of longitudinal and shear acoustic waves in samples. The main advantage of this method compared with traditional ultrasonic research methods is the efficient generation of short and powerful probing acoustic pulses required for reliable testing of ultrasound absorbing and scattering heterogeneous materials. Using as an example samples of a metal matrix composite with reinforcing microparticles of silicon carbide in various concentrations, it is shown that to provide an effective increase in Young’s modulus with increasing concentration of microparticles, the porosity of the final sample should not exceed 2%.

Keywords: Laser ultrasonic, longitudinal and shear ultrasonic waves, porosity, composite, local elastic moduli.

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Authors: Penghui Zhang, Hua Zhang, Jun-Bo Wang, Cheng Zeng, Zijian Cao

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With the development of software-defined networks and programmable data planes, in-band network telemetry (INT) has become an emerging technology in communications because it can get accurate and real-time network information. However, due to the expansion of the network scale, existing telemetry systems, to the best of the authors’ knowledge, have difficulty in meeting the common requirements of low overhead, low latency and full coverage for traffic measurement. This paper proposes a network-wide telemetry system with a low-latency low-overhead path planning (INT-LLPP). This paper builds a mathematical model to analyze the telemetry overhead and latency of INT systems. Then, we adopt a greedy-based path planning algorithm to reduce the overhead and latency of the network telemetry with the full network coverage. The simulation results show that network-wide telemetry is achieved and the telemetry overhead can be reduced significantly compared with existing INT systems. INT-LLPP can control the system latency to get real-time network information.

Keywords: Network telemetry, network monitoring, path planning, low latency.

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: BERT, chatbot, cryptocurrency, deep learning.

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Authors: Stefan V. Stefanescu

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We intend to point out the differences which exist between the classical Gini concentration coefficient and a proposed bipolarization index defined for an arbitrary random variable which have a finite support. In fact Gini's index measures only the "poverty degree" for the individuals from a given population taking into consideration their wages. The Gini coefficient is not so sensitive to the significant income variations in the "rich people class" . In practice there are multiple interdependent relations between the pauperization and the socio-economical polarization phenomena. The presence of a strong pauperization aspect inside the population induces often a polarization effect in this society. But the pauperization and the polarization phenomena are not identical. For this reason it isn't always adequate to use a Gini type coefficient, based on the Lorenz order, to estimate the bipolarization level of the individuals from the studied population. The present paper emphasizes these ideas by considering two families of random variables which have a linear or a triangular type distributions. In addition, the continuous variation, depending on the parameter "time" of the chosen distributions, could simulate a real dynamical evolution of the population.

Keywords: Bipolarization phenomenon, Gini coefficient, income distribution, poverty measure.

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: Bioassay, machine learning, preprocessing, virtual screen.

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Authors: Gregor Radonjič, Aleksandra P. Korda, Damijan Krajnc

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The aim of the study was to investigate whether there is the promotion of product ecodesign measures as a result of adopting ISO 14001 certification in manufacturing companies in the Republic of Slovenia. Companies gave the most of their product development attention to waste and energy reduction during manufacturing process and reduction of material consumption per unit of product. Regarding the importance of different ecodesign criteria reduction of material consumption per unit of product was reported as the most important criterion. Less attention is paid to endof- life issues considering recycling or packaging. Most manufacturing enterprises considered ISO 14001 standard as a very useful tool or at least a useful tool helping them to accelerate and establish product ecodesign activities. Two most frequently considered ecodesign drivers are increased competitive advantage and legal requirements and two most important barriers are high development costs and insufficient market demand.

Keywords: ecodesign, environmental management system, ISO 14001, products

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