161 research outputs found
Court Judgment Decision Support System Based on Medical Text Mining
Medical damage is a common problem faced by hospitals around the world and is widely watched by countries and the World Health Organization. As the number of medical damage dispute lawsuit cases rapidly grows, many countries in the world face the problem how to improve the efficiency of the judicial system under the premise of guaranteeing the quality of the trial. Therefore, in addition to reforming the system, the decision support system will effectively improve judicial decisions. This paper takes medical damage judgment documents in China as example, and proposes a court judgment decision support system (CJ-DSS) based on medical text mining and the automatic classification technology. The system can predict the trail results of the new lawsuit documents according to the previous cases verdict - rejected and non-rejected. Combined with the cases, the study in this paper found that combined feature extraction method does improve the performance of three kinds of classifiers - Support Value Machine (SVM), Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN), the degree of improved performance is different from using DF-CHI combined feature extraction method. In addition, integrated learning algorithm also improves the classification performance of the overall system
A Robust Site Selection Model under uncertainty for Special Hospital Wards in Hong Kong
This paper process two robust models for site selection problems for one of
the major Hospitals in Hong Kong. Three parameters, namely, level of
uncertainty, infeasibility tolerance as well as the level of reliability, are
incorporated. Then, 2 kinds of uncertainty; that is, the symmetric and bounded
uncertainties have been investigated. Therefore, the issue of scheduling under
uncertainty has been considered wherein unknown problem factors could be
illustrated via a given probability distribution function. In this regard, Lin,
Janak, and Floudas (2004) introduced one of the newly developed strong
optimisation protocols. Hence, computers as well as the chemical engineering
[1069-1085] has been developed for considering uncertainty illustrated through
a given probability distribution. Finally, our accurate optimisation protocol
has been on the basis of a min-max framework and in a case of application to
the (MILP) problems it produced a precise solution that has immunity to
uncertain data
Using Gray-Markov Model and Time Series Model to Predict Foreign Direct Investment Trend for Supporting China’s Economic Development
Foreign direct investment (FDI) is one of the important factors affecting China’s economic development, the prediction of which is the basis of its development and decision-making. Based on elaborating the significant role in China’s economic growth and the status quo of utilizing foreign investment over the period between 2000 and 2016, this chapter attempts to construct Gray-Markov model (GMM) and time series model (TSM) to forecast the trend of China’s utilization of FDI and then compares the precision of two different prediction models to obtain a better one. Results indicate that although it is qualified, traditional Gray model needs to be optimized; GMM is built to help modify the result, improve Gray-related degrees, and narrow the gap with real value. Comparing the accuracy of GMM with that of TSM, we can conclude that the fitting effect of GMM is better. To increase the credibility of these results, this chapter is based on the data of Beijing and Chongqing from 1990 till 2016, also verifying that the fitting effect of GMM is superior to that of the TSM. Then, we can safely draw a conclusion that the prediction model of GMM is more credible, which has a certain referencing value for the utilization of FDI
Entrepreneurial Intentions and Behaviour as the Creation of Business: Based on the Theory of Planned Behaviour Extension Evidence from Polish Universities and Entrepreneurs
The purpose of this research was to analyze the relationships between the factors that influence entrepreneurial Intention (EI), using a modified version of Ajzen’s theory of planned behaviour (TPB), considering the perception of behaviour. This examination depended on participants' demographic characteristics and psycho-social behavioural traits of attitude (ATT), Subjective norm (SN), and perceived behavioural control (PBC). The establishment of a new business entails various forms of action to achieve desired results. This research analyzes entrepreneurship as the creation of business by engaging in rational behaviour to optimize the use of available technologies and financial sources. These activities are not standardized: They emerge from the entrepreneurial imagination, the perception of new opportunities, and innovation. The aim of a business is not just to produce and sell goods or services. A company must determine the appropriate means of providing them and choose the values to be adopted in the procedure of doing so. Companies should also identify the actions to be taken so that principals or employees incorporate these values into their activities and establish the character that will permit them to regards options and make correct decisions in keeping with the business’s goals
Exchange Rate Forecasting Using Entropy Optimized Multivariate Wavelet Denoising Model
Exchange rate is one of the key variables in the international economics and international trade. Its movement constitutes one of the most important dynamic systems, characterized by nonlinear behaviors. It becomes more volatile and sensitive to increasingly diversified influencing factors with higher level of deregulation and global integration worldwide. Facing the increasingly diversified and more integrated market environment, the forecasting model in the exchange markets needs to address the individual and interdependent heterogeneity. In this paper, we propose the heterogeneous market hypothesis- (HMH-) based exchange rate modeling methodology to model the micromarket structure. Then we further propose the entropy optimized wavelet-based forecasting algorithm under the proposed methodology to forecast the exchange rate movement. The multivariate wavelet denoising algorithm is used to separate and extract the underlying data components with distinct features, which are modeled with multivariate time series models of different specifications and parameters. The maximum entropy is introduced to select the best basis and model parameters to construct the most effective forecasting algorithm. Empirical studies in both Chinese and European markets have been conducted to confirm the significant performance improvement when the proposed model is tested against the benchmark models
Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model
As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations
INVESTIGATING THE IMPACT OF CRISIS ON CORPORATE COSTS AND SALES USING ECONOMETRICS METHOD
Постановка проблеми: стаття доповнює попередні дослідження і фокусується на питаннях прискорення глобалізації і глобальної економічної кризи, який зачепить більшість країн прямо або побічно. Оскільки криза зачіпає компанії то в статті розглядається один із шляхів виходу з нього шляхом управління витратами на маркетинг. Мета: в статті робиться спроба виявити детермінанти, встановити вплив кризи на корпоративні витрати і продажу з використанням методу динамічної панельної економетрики, а також дослідити вплив кризи на витрати і продажу компаній. Вхідні дані: в статті розглядається вплив маркетингових витрат на чисті продажі; були використані дані від 25 компаній, що діють на Тегеранській фондовій біржі протягом 11 років (2002-2012 роки). Методи: для перевірки гіпотези дослідження ми аналізуємо інформацію економетричними методами. У цьому дослідженні методи економетрики наступні: (дані панелі, дані статичної панелі, фіксовані ефекти і випадкові ефекти, модель фіксованих ефектів, модель випадкових ефектів, тест Хаусмана, модель даних статичної панелі, дані динамічного компонування, тест Вальда). Крім того, слід зазначити, що для аналізу даних в цьому дослідженні ми використовували тест F Лібера, тест Хаусмана і тест Вальда. У дослідженні використовувалося програмне забезпечення Stata, метод різниці першого порядку використовується для усунення статичних ефектів, а перервані значення залежної змінної використовуються в якості змінних інструменту. Результати: результати перевірки гіпотези показують, що перша і друга гіпотеза дослідника підтверджуються, а нульові гіпотези відкидаються. Крім того, третя, четверта і п'ята гіпотези дослідника відкидаються, а нульові гіпотези підтверджуються. Висновок: результати вказують на значний вплив на чисті продажі оціночних маркетингових витрат компанії, показують, що витрати на 1 риал в маркетингу призводять до збільшення продажів на 58 риалів, і навіть під час глобальної економічної кризи ця цифра еквівалентна 26 риалах. Аналіз наголошує на важливості маркетингових витрат на продажу в Ірані. Особливо в періоди криз і після них маркетингові витрати мали значний вплив на продажу.Постановка проблемы: статья дополняет предыдущие исследования и фокусируется на вопросах ускорения глобализации и глобального экономического кризиса, который затронет большинство стран прямо или косвенно. Поскольку кризис затрагивает компании то в статье рассматривается один из путей выхода из него путем управления расходами на маркетинг. Цель: в статье делается попытка выявить детерминанты, установить влияние кризиса на корпоративные издержки и продажи с использованием метода динамической панельной эконометрики, а также исследовать влияние кризиса на издержки и продажи компаний. Исходные данные: в статье рассматривается влияние маркетинговых затрат на чистые продажи; были использованы данные от 25 компаний, действующих на Тегеранской фондовой бирже в течение 11 лет (2002–2012 годы). Методы: для проверки гипотезы исследования мы анализируем информацию эконометрическими методами. В этом исследовании методы эконометрики следующие: (данные панели, данные статической панели, фиксированные эффекты и случайные эффекты, модель фиксированных эффектов, модель случайных эффектов, тест Хаусмана, модель данных статической панели, данные динамической компоновки, тест Вальда). Кроме того, следует отметить, что для анализа данных в этом исследовании мы использовали тест F Либера, тест Хаусмана и тест Вальда. В исследовании использовалось программное обеспечение Stata, метод разности первого порядка используется для устранения статических эффектов, а прерванные значения зависимой переменной используются в качестве переменных инструмента. Результаты: результаты проверки гипотезы показывают, что первая и вторая гипотеза исследователя подтверждаются, а нулевые гипотезы отвергаются. Кроме того, третья, четвертая и пятая гипотезы исследователя отвергаются, а нулевые гипотезы подтверждаются. Вывод: результаты указывают на значительное влияние на чистые продажи оценочных маркетинговых затрат компании, показывают, что затраты на 1 риал в маркетинге приводят к увеличению продаж на 58 риалов, и даже во время глобального экономического кризиса эта цифра эквивалентна 26 риалам. Анализ отмечает важность маркетинговых расходов на продажи в Иране. Особенно в периоды кризисов и после них маркетинговые расходы оказали значительное влияние на продажи.Background: this article seeks to complement the previous literature and clarify the importance of paying attention to the acceleration of globalization, and the global economic crisis that all countries will be affected directly and indirectly, through the crisis is important for the companies and one way out of the crisis, manages the marketing costs. Aim: this article seeks to identify the determinants, to find the Impact of Crisis on Corporate Costs and Sales with the using dynamic panel econometrics method and also, finding crisis effect on the costs and sales of companies. Setting: this article examines the effect of marketing costs on net sales; data from the 25-company’s active in the Tehran Stock Exchange (TSE) during 11 years (2002-2012) have been used. Methods: in order to test the hypothesis of the research, we analyze the information by econometric methods. In this research econometrics methods are respectively: (Panel data, static panel data, fixed effects, and random effects, fixed effects model, random effects model, Hausman test, static panel data model, dynamic layout data, Wald test). Also, it should be noted for data analysis in this research we used from (F Lieber test and Hausman test and Wald test). Software used in this study was Stata software, the first order difference method is used to eliminate the static effects, and the interrupted values of the dependent variable are used as tool variables. Results: research hypothesis test results shows the first and second researcher hypothesis is confirmed and the zero hypotheses are rejected. Also, the third and fourth and fifth researcher hypothesis is rejected, and the zero hypotheses are confirmed. Conclusion: the results indicate a significant impact on net sales of company's marketing costs estimates indicate that costs 1 Rial in marketing, leading to increased sales of 58 Rials, and even during the global economic crisis, this figure is equivalent to 26 Rials. The analyses notice the importance of marketing expenditures on sales in Iran. Especially during the crises periods and after, marketing expenditures are found as having significant effects on sales
Análisis y modelización de la corrupción entre emprendedores
El soborno puede erradicar el bienestar social. En la investigación actual, inspeccionamos el mecanismo del comportamiento de soborno basado en la (Teoría NASH o teoría del juego estático no cooperativo) que declaró John Forbes Nash Jr. en 1978. Con la hipótesis general de "Rational Player", dos juegos de bimatrix Se establecen modelos para evaluar el soborno y la elección de la estrategia de soborno. Después de discutir el costo-beneficio de los (Participantes o jugadores), se extraen algunas conclusiones útiles y análisis de disolución. El estudio actual
proporciona tres experimentos novedosos que ponen a prueba ambas metáforas. En general, un pequeño estudio cuantitativo ha investigado el comportamiento no ético secuencial. Algunos estudios previos se centran en la aceptación por parte de observadores externos de actos inmorales continuos versus abruptos, o el papel del autocontrol y la desconexión ética en la pendiente resbaladiza de los actos de engaño menores. Los avances recientes en la metodología de estudios empíricos de corrupción permiten el primer examen de estos diferentes procedimientos al tiempo que mantienen constantes los costos y beneficios económicos. En el
estudio actual, utilizamos un juego de corrupción recientemente mejorado por [Köbis, van Prooijen, Righetti, Van Lange, 2015]
Forecasting Crude Oil Price with Multiscale Denoising Ensemble Model
Crude oil price becomes more volatile and sensitive to increasingly diversified influencing factors with higher level of deregulations worldwide. Current methodologies are being challenged as they have been constrained by traditional approaches assuming homogeneous time horizons and investment strategies. Approximations they provided over the long term time horizon no longer satisfy the accuracy requirement at shorter term and more microlevels. This paper proposes a novel crude oil price forecasting model based on the wavelet denoising ARMA models ensemble by least square support vector regression with the reduced forecasting matrix dimensions by independent component analysis. The proposed methodology combines the multi resolution analysis and nonlinear ensemble framework. The wavelet denoising based algorithm is introduced to separate and extract the underlying data components with distinct features, corresponding to investors with different investment scales, which are modeled with time series models of different specifications and parameters. Then least square support vector regression is introduced to nonlinearly ensemble results based on different wavelet families to further reduce the estimation biases and improve the forecasting generalizability. Empirical studies show the significant performance improvement when the proposed model is tested against the bench-mark models
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