Collaborative delay management towards demand-capacity balancing within User Driven Prioritisation Process

The concept of User Driven Prioritisation Process (UDPP) was introduced to give Airspace Users (AUs) more flexibility under demand-capacity imbalance. This paper presents two UDPP-DCB models, built on the UDPP principle, using the Selective Flight Protection (SFP) approach to minimize the total delay cost. AUs are enabled to adapt their operations in a more cost-efficient way in the presence of capacity constraints in airspace, optimizing their flights to keep the priorities track. Then, ATFM integrates the AUs’ decision to reassign the time slots and the preferred rerouting trajectories. Results suggest that the delay cost for AUs can be largely reduced through applying the UDPP-DCB models proposed in this paper, while allowing rerouting proves effective in reducing the system delay cost.     

Equity premium prediction and optimal portfolio decision with Bagging

We propose using the statistical method of Bagging to forecast the equity premium out-of-sample for multivariate regression models. Bagging allows for the flexible and efficient extraction of valuable informational content from a large set of predictors, leading to statistically and economically significant gains relative to not only the historical mean, but also other soft-threshold methods such as forecast combinations and shrinkage estimators in our empirical results. Furthermore, we find that the source of economic gains for Bagging primarily comes from the fact that it encourages the investor to actively manage portfolio by flexibly utilizing short selling or leveraging to better time the market following correctly prognosticated trends. However, other strategies such as forecast combinations keep the equity shares nearly fixed regardless of the predicted market prospect.     

媒体情绪与房价波动*

本文使用2000—2015年中国112个大中城市媒体报道和房价月度指数研究了媒体异质性对房价波动的影响。研究发现，纸媒情绪对房价波动的影响大于网媒情绪，中央媒体情绪对房价波动的影响大于地方媒体情绪，明星微博情绪对房价波动的影响大于普通微博情绪，媒体语气确定性和报道篇幅对房价波动有正影响，明星城市媒体情绪较非明星城市更易引起房价波动。据此，为防范非理性房价波动，应加强对不同媒体报道的监管。     

Understanding homophily of service failure within the hotel guest cycle: Applying NLP-aspect-based sentiment analysis to the hospitality industry

Online complaints have become increasingly influential on the purchasing behavior of customers in recent years. In an effort analyze large quantities of textual complaints and detail the various aspects of them, Aspect-Based Sentiment Analysis was looked to as an ideal framework to take on the task. This study set out to synthesize specific service failure items and categorize them into the groupings related to the hotel guest cycle and the corresponding operations, then compare the patterns of expression used by Asian and Non-Asian guests as the related their hotel experiences. A total of 390,236 online complaint terms posted about 353 hotels in the UK by hotel guests from 63 nations were manually derived from TripAdvisor for analysis. With consideration given to the homophily theory, we posited that Asian and non-Asian guests would exhibit similarities and differences with respect to the service failures they encountered when presented with various items of service. The results confirmed this as Asian guests were shown to encounter more service failures with respect to the engineering segment of operations (e.g. hotel room equipment issues), while non-Asian guests encountered more service failures on the housekeeping end of operations (e.g. toilets, public areas, cleanliness, and bedding). By organizing the failures according the four stages of the guest cycle, it was observed that approximately 80% of the service failures occurred during the occupancy period. This study contributes to the existing literature on hotel guest satisfaction both with respect to the methodology it uses and the new findings it presents on differences in perceptions of service failures members among different cultures.     

An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry

Driven by business strategies, digital transformation (DT) facilitates dramatic change in air passenger behavior. This study aims to determine and analyze different DT strategies (DTSs) with the help of an integrated SWOT-based fuzzy AHP-MARCOS methodology that is proposed for the first time in the literature for this purpose. This methodology is validated with a case study concerning the airline industry in Turkey. The weights of the SWOT factors are determined with the fuzzy AHP method. The fuzzy MARCOS approach is used to select the most suitable DTS. The most appropriate strategy is obtained as “focusing on differentiated digital customer experience and service quality by the adaptation of business models to DT to provide benefits”.     

Governing Suburbia through regionalized land-use planning? Experiences from the Greater Frankfurt region

This paper explores the case of peripheral settlement growth in the Greater Frankfurt (Main) region within current debates on global suburbanization. Within Germany’s sophisticated spatial planning regime, Greater Frankfurt’s system of regionalized land-use planning marks an ambitious initiative to contain urban sprawl. Nonetheless, expansive peripheral settlement growth, and socio-spatial polarization remain distinct characteristics of the booming region. Analyzing state regulation vis-à-vis dynamics of capitalist urbanization and private authoritarianism, we decipher the complex governance arrangements producing this, at first sight, contradictory simultaneity. We uncover the rationales of local growth politics of autonomous municipalities and the region’s multiplied institutional fragmentation that undermine planning ambitions to contain suburban growth. We conclude by critically assessing the political economies of suburbanization in Greater Frankfurt and point to prospects for regional reform.     

Bread or justice - Land restitution and investments in Montes de Maria,Colombia

In 2011, Colombia started a legal land restitution process whereby government institutions help internally displaced people (IDPs) reclaim land dispossessed after 1991 through the violent conflict involving the communist guerilla, paramilitaries and the army. The designated land courts normally covers voluntary sales at the going market price at the time of dispossession, presuming buyers took advantage of the IDPs’ need for money and their low expectations of returning from their current sites of refuge. We study the rise and fall of a commercial cassava operation that started to buy land from IDPs openly in the Montes de María region on Colombia’s Caribbean coast after peace returned in 2007. After losing several land restitution court cases, the company shifted from dairy cattle that required high investments to the less demanding, but also less productive, buffalo to minimize losses in case of future successful restitution claims. The land restitution law will probably be extended beyond the initial 2021 limit due to slow progress, thereby perpetuating the insecure property rights situation that hinders investments in agriculture.     

基于软件无线电平台的1090ES扩容信号收发处理

随着空中交通的信息传输与新应用拓展需求不断增加，1090ES信号容量有限问题日益显现，对1090ES信号进行容量扩充是一种有效解决途径。针对一种基于脉内调相的1090ES信号扩容技术，给出了叠加调制的信号模型，研究了1090ES信号的解调解码算法；在GNU Radio+ USRP软件无线电平台上，实现了1090ES扩容信号的产生和接收处理，包括脉冲位置调制（Pulse Position Modulation，PPM）与8PSK叠加调制、低通滤波、报头检测、载波同步、PPM解码和相位解调等，并利用Matlab对实验的解码错误率和信号的频谱特性做了统计分析与仿真，结果表明了该扩容技术的可行性。     

双平行线阵的快速一维DOA估计

针对传统子空间算法需要进行特征值分解或奇异值分解等复杂计算的问题，提出一种双平行线阵（Double Parallel Linear Array,DPLA）的快速一维波达方向（Direction of Arrival，DOA）估计算法。算法通过处理互协方差矩阵的第一列元素构造出等效的噪声子空间，再通过求根MUSIC（Multiple Signal Classification）算法得到DOA估计，有效避开了特征值分解或奇异值分解，降低了计算复杂度，提高了运算速度。仿真结果表明，该算法在提高了估计精度的同时减少了估计时间。     

一种利用机器学习优化MIMO窃听信道天线选择的方法

为保障多输入多输出窃听信道系统中信息传输的保密性，提出了一种基于机器学习的天线选择方案。首先利用机器学习解决分类问题准确率高、处理大数据高效这一优势，设计了基于奇异值分解的特征值提取、基于信干噪比的标签赋值方案，建立了k最近邻分类器和逻辑回归分类器选择最优天线最大化保密性能（可达保密速率和保密中断概率）。与传统天线选择方案相比，所提方案获得了几乎一致的保密性能，并且大幅降低了系统的选择复杂度和误比特率。