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This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

Different from Marx's analysis of the dialectical relationship between the production and realization of surplus value, the Okishio theorem only shows one aspect of the contradictory movement of the total social capital, that is, the reverse effect of the realization of surplus value on the production of surplus value.

The production of surplus value and the realization of surplus value are simplified into one process. This simplification eliminates the contradiction between the production and realization of surplus value, and the antagonistic contradiction between accumulation and consumption and the antagonistic production-distribution relationship in capitalist society are naturally covered up.

Therefore, it cannot explain the actual expansion way of the falling general rate of profit as the historical development law of capitalism. Nevertheless, it should be noted that the Okishio theorem places the analysis of the general rate of profit back into the social reproduction model with department equilibrium, which points out the significance of wage income to the realization of surplus value and outlines the macro mechanism of the realization of surplus value reacting to the production of surplus value. It also strongly promotes the research progress of the law that the profit rate tends to decline.

The mistake of the Okishio theorem is that the exchange process in the labor market forms the real wage rate. It determines the production price of wage goods, which thereby determines that the production price of capital goods and general rate of profit, the production of surplus value and realization of surplus value are simplified into the same process, and only the value that can be realized is the real value.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

The purpose of this study is to analyze the influence of booking website (hotel or third-party) characteristics and hotel star-rating classification, as signals of quality, on travelers’ relationships with hotels or hotel chains, taking into account the moderating effect of travelers’ tendencies to seek variety.

To test the hypothesized relationships, structural equation modeling was performed. A multi-group analysis was also conducted to test the moderating effect of travelers’ variety seeking.

Both booking website quality and star rating improve customer satisfaction with specific experiences at hotels and behavioral intentions toward hotels. The results also show that travelers’ variety-seeking levels (low/high) exert a moderating effect on their overall relationships with hotels, and quality signals are more relevant for those who are less inclined to seek variety in their travel experiences.

This paper analyzes the importance of quality signals on travelers’ relationships with hotels in an electronic shopping environment. Furthermore, the influence of travelers’ variety-seeking in the hotel sector in particular is studied. For hotel managers, a better knowledge of this personality trait can help to apply successful segmentation strategies.

Este estudio analiza la influencia de las características del sitio web de reserva -web propia del hotel o de un tercero- y del número de estrellas del hotel, como señales de calidad, en la relación del cliente con el hotel o cadena, teniendo en cuenta el efecto moderador de la tendencia del viajero a buscar variedad.

Para probar las hipótesis, se llevó a cabo un modelo de ecuaciones estructurales (SEM). También se realizó un análisis multi-grupo para probar el efecto moderador de la búsqueda de variedad del viajero.

Tanto la calidad del sitio web de reserva como las estrellas favorecen la satisfacción del cliente con la experiencia concreta en el hotel y, finalmente, las intenciones de comportamiento hacia el hotel. Además, el análisis muestra que el nivel de búsqueda de variedad del viajero (bajo/alto) ejerce un efecto moderador en su relación global con el hotel y que las señales parecen ser más relevantes para los individuos con menor tendencia a buscar variedad en sus experiencias de viaje.

Este trabajo analiza la importancia de las señales de calidad en la relación de los viajeros con los hoteles en un entorno de compra electrónica. Además, se estudia la influencia de la búsqueda de variedad de los viajeros en el sector hotelero en particular. Un mejor conocimiento de este rasgo de la personalidad puede ayudar a los gerentes de hotel a aplicar estrategias de segmentación exitosas.

摘要

本研究的目的是分析作为品质判断因素的预订网站(酒店或第三方)特征和酒店星级评分分类对游客与酒店或连锁酒店关系的影响，并考虑游客寻求多样性倾向的调节作用。

为了检验假设的关系，我们进行了结构方程建模。本研究还采用多组分析的方法来检验旅客的多样性寻求的调节作用。

预订网站的质量和星级评分都可以提高客户对酒店具体体验的满意度和对酒店的行为意向。结果还表明，游客的多样性寻求水平(低/高)对他们与酒店的整体关系具有调节作用，而质量因素对那些不太倾向于在旅行体验中寻求多样性的人更相关。

本文分析了在电子购物环境下，品质因素对游客与酒店关系的重要性。此外，本文还特别研究了游客的多样性寻求对酒店行业的影响。对于酒店管理者来说，更好地了解这一个性特征有助于成功地应用细分策略。

The authors consider the mutual benefits of the ceding company and reinsurance company in the design of reinsurance contracts. Two objective functions to maximize social expected utilities are established, which are to maximize the sum of the expected utilities of both the ceding company and reinsurance company, and to maximize their products. The first objective function, additive, emphasizes the total gains of both parties, while the second, multiplicative, accounts for the degree of substitution of gains of one party through the loss of the other party. The optimal price and retention of reinsurance are found by a grid search method, and numerical analysis is conducted. The results indicate that the optimal solutions for two objective functions are quite different. However, optimal solutions are sensitive to the change of the means and volatilities of the claim loss for both objective functions. The results are potentially valuable to insurance regulators and government entities acting as reinsurers of last resort.

In this paper, the authors apply relatively simple, but in the view significant, methods and models to discuss the optimization of excess loss reinsurance strategy. The authors only consider the influence of loss distribution on optimal retention and reinsurance price but neglect the investment factor. The authors also consider the benefits of both ceding company and reinsurance company to determine optimal premium and retention of reinsurance jointly based on maximizing social utility: the sum (or the product) of expected utilities of reinsurance company and ceding company. The authors solve for optimal solutions numerically, applying simulation.

This paper establishes two optimization models of excess-of-loss reinsurance contract against catastrophic losses to determine optimal premium and retention. One model considers the sum of the expected utilities of a ceding company and a reinsurance company's expected utility; another considers the product of them. With an example, the authors find the optimal solutions of premium and retention of excess loss reinsurance. Finally, the authors carry out the sensitivity analysis. The results show that increasing the means and the volatilities of claim loss will increase the optimal retention and premium. For objective function I, increasing the coefficients of risk aversion of or reducing the coefficients of risk aversion of will make the optimal retention reduced but the optimal premium increased, and vice versa. However, for objective function 2, the change of coefficient of risk aversion has no effect on optimal solutions.

Utility of the two partners: The ceding company and the reinsurance company, may have different weights and different significance. The authors have not studied their relative significance. The simulation approach in numerical methods limits us to the probability distributions and stochastic processes the authors use, based on, generally speaking, lognormal models of rates of return. This may need to be generalized to other returns, including possible models of shocks through jump processes.

In the recent two decades, reinsurance companies have played a great role in hedging mega-catastrophic losses. For example, reinsurance companies (and special loss sharing arrangements) paid as much as two-thirds of the insured losses for the September 11, 2001 tragedy. Furthermore, large catastrophic events have increased the role of governments and regulators as reinsurers of last resort. The authors hope that the authors provide guidance for possible balancing of the needs of two counterparties to reinsurance contracts.

Nearly all governments around the world are engaged in regulation of insurance and reinsurance, and some are reinsurers themselves. The authors provide guidance for them in these activities.

The authors believe this paper to be a completely new and original contribution in the area, by providing models for balancing the utility to the ceding insurance company and the reinsurance company.

我們探討分出公司和再保險公司在再保險合約的設計上、如何能達至互利互惠。研究確立了兩個目標函數，分別為把分出公司和再保險公司兩者之預期效用的總和最大化，以及把它們的產品最佳化。第一個目標函數是加法的，強調兩個參與方的總增益;而第二個目標函數則是乘法的，這個目標函數，闡釋參與方因另一方虧損而有所收益之取代度。再保險的最佳價格和自留額是利用網格搜索法找出的，數值分析也予以進行。研究結果顯示，兩個目標函數的最佳解決方案甚為不同。唯最佳解決方案會對就這兩個目標函數而言的追討損失的波動、以及其平均值之改變產生敏感反應。研究結果將會見其價值於作為在萬不得已的時候的再保險人的保險業規管機構和政府實體。

在這學術論文裡，我們採用了相對簡單、但我們認為是重要的方法和模型，來探討超額賠款再保險策略的優化課題。我們只考慮虧損分佈對最佳自留額和再保險價格的影響，而不去檢視投資因素。我們亦考慮對分出公司和再保險公司兩者的利益，來釐定最佳保費和再保險的自留額，而這兩者則共同建基於把社會效益最大化之上：再保險公司和分出公司的預期效益的總和 (或其積數) 。 我們採用類比模仿方法、來解決尋求在數字上最佳解決方案的問題。

本研究建立了就應對嚴重虧損而設的兩個超額賠款再保險合約的優化模型，來釐定最佳的保費和自留額。其中一個模型考慮了分出公司和再保險公司兩者各自的預期效益的總和。另外的一個模型則考慮了兩者的預期效益的積數。透過例子，我們找到了保費和超額虧損再保險自留額的最佳解決方案。最後，我們進行了敏感度分析。研究結果顯示、若增加追討損失的平均值和波動，則最佳自留額和保費也會隨之而增加。就第一個目標函數而言，若增加風險規避係數、或減少這個係數，則最佳自留額會隨之而減少，但最佳保費卻會隨之而增加，反之亦然。唯就第二個目標函數而言，風險規避係數的改變，對最佳解決方案是沒有影響的。

• – 有關的兩個夥伴之效用性：分出公司和再保險公司或有不同的份量和重要性。我們沒有探討兩者的相對重要性。

• – 我們以數值方法為核心的類比模仿研究法、使我們局限於機率分配和一般而言建基於投資報酬率對數常態模型之隨機過程的使用。我們或許需要調節研究法。以能概括其它回報收益，包括透過跳躍過程而可能達至之沖擊模型。

– 有關的兩個夥伴之效用性：分出公司和再保險公司或有不同的份量和重要性。我們沒有探討兩者的相對重要性。

– 我們以數值方法為核心的類比模仿研究法、使我們局限於機率分配和一般而言建基於投資報酬率對數常態模型之隨機過程的使用。我們或許需要調節研究法。以能概括其它回報收益，包括透過跳躍過程而可能達至之沖擊模型。

在過去20年裡，再保險公司在控制極嚴重災難性的損失上曾扮演重要的角色。例如、再保險公司 (以及特殊的損失分擔安排) 為了2001年9月11日的災難事件而支付多至保險損失的三分之二的費用。而且，重大的災難性事件使政府及作為最後出路再保險人的調控者得扮演更重要的角色。我們希望研究結果能為再保險合約兩對手提供指導，以平衡雙方的需要。

全球差不多每個政府都參與保險和再保險的管理工作，有部份更加本身就是再保險人。研究結果為他們的管理工作提供了指導。

我們相信本學術論文、提供了平衡分出保險公司和再保險公司效用性的模型，就此而言，本論文在相關的領域上作出了全新和獨創性的貢獻。