Review of managing the risks of offshore banking and its implications for the China (Shanghai) Pilot Free Trade Zone

As more and more Chinese and foreign-funded banks settle in the China (Shanghai) Pilot Free Trade Zone (CSPFTZ), it has become an imperative to enhance risk management of offshore banking. At the international level, the regulatory effort for offshore banking mainly focuses on tax evasion and money laundering. Existing regulatory frameworks have established standards to identify countries providing facilities for money laundering and developed punitive measures. In terms of strategy, it is suggested that, firstly, relevant regulatory measures should be improved in the short term, and it is necessary to define the scope of offshore banking and regulatory measures for Chinese banks and foreign-funded banks under a suitable legal framework. Secondly, it is necessary to establish risk exposure mechanism and risk evaluation system for the offshore banking in the CSPFTZ, while risk management measures are implemented based on on-site supervision. Thirdly, in the medium and long term, it is necessary to enhance management of potential risks which can be created by offshore banking due to deregulation. Fourthly, on the one hand, specific regulations should be formulated to provide a regulatory basis for taxation; on the other hand, tax informational exchange agreements (TIEAs) may be used as a reference for achieving effective tax regulation.     

The jurisdictional challenges to the prosecution of piracy cases in Kenya: mixed fortunes for a perfect model in the global war against piracy

Since 2008 Kenya has distinguished itself in the global war against piracy by undertaking prosecutions in the national courts of suspected pirates arrested in the high seas and handed over by navies of leading maritime nations under bilateral agreements (MOUs) entered into between Kenya and these leading maritime nations. As of July 2011, Kenya had over 20 convicted pirates serving jail terms ranging between 7 and 20 years and over 100 suspected pirates awaiting trial in national courts. This is the largest number of suspected pirates held and tried in any one state at any given time in modern history. To achieve this, Kenya had to effect far reaching changes in the law. In the initial stages, suspected pirates were charged under Kenya’s Penal Code (Cap 63 Laws of Kenya). However, the high court in the case of Re Mohamud Mohamed Dashi and eight others [2010] eKLR, ruled that Kenya had no jurisdiction to try suspected pirates under that law. In September 2009, Kenya passed a new law (the Merchant Shipping Act), which not only defined more comprehensively and extensively the offence of piracy, but also extended the jurisdiction of Kenyan courts to try piracy committed by non-nationals. Though the law gives Kenya a very broad jurisdiction to try suspected pirates, the process is still fraught with challenges due to lack of financial and human resources. In the case of Republic vs Hassan Jama Haleys Alias Hassan Jamal and five others [2010] eKLR, the court commented thus:

“… I must note that the ‘piracy trials’ have presented a unique challenge to the Kenyan legal system. We cannot ignore the fact that these are suspects who having been arrested by foreign naval forces on the High Seas are brought to Kenya for trial. They are strangers in the country, do not understand the legal system, may not know what their rights are and do not understand the language… the Kenyan Government and the International partners supporting these trials put in place a system to provide free legal representation for the suspects…”     

Fast Ferry Smoothing Motion via Intelligent PD Controller

A novel type of control law was adopted to reduce the vertical acceleration of a fast ferry as well as the motion sickness incidence suffered by the passengers onboard by means of a submerged T-foil. Considering the system changing characteristics under high disturbances, a model-free approach was adopted. In addition, an upgraded proportional-derivative (PD) controller with correction terms resulting from a fast-online estimation of the system dynamics was designed. The overall controller, known as intelligent PD (i-PD) controller, was tested, and the obtained results were compared with those of a classic PD controller. The controllers were also tested in a changing environment and at different operating velocities. The results confirmed the effectiveness of the i-PD controller to smooth the motions with low computational cost control schemes. Furthermore, thanks to ability of the i-PD controller to continually update the estimated dynamics of the system, it showed a better reduction in both vertical motions and the seasickness level of the passengers with the needed robustness under external disturbances and system changing parameters.     

Full Duplex Communications for Next Generation Cellular Networks: The Capacity Gain

Full duplex communication highly improves spectrum efficiency of a wireless communication link. However, when it is applied to a cellular network, the capacity gain from this technology remains unknown. The reason is that full duplex communication changes the aggregate interference experienced by each communication link in cellular networks. In this paper, the capacity gain from full duplex communication is studied for cellular networks of 4G and beyond, where the same frequency channel is adopted in each cell. A two-layer Poisson point process (PPP) is adopted to model the network topology, and stochastic geometry is employed to derive the coverage probability and the average capacity of typical link in a cellular network. On the basis of these derived parameters, the capacity gain from full duplex communication is determined. Numerical results reveal that without mutual interference cancellation (MIC), the capacity gain is small under various power levels; with perfect MIC at base stations, the capacity gain can exceed 60%; with imperfect MIC at base stations, the capacity gain decreases quickly even with a slight drop of MIC performance.     

基于AHP的区域路网指路标志系统现状评价研究

为了准确评价某区域路网的指路标志系统现状,应先对其现状情况调查取证,收集其相关的数据。再针其现状存在的问题,构建起一个评价结构模型。模型的准则层由3个主要影响因素组成,而模型的方案层由10个小的指标组成。然后采用层次分析法(AHP法),给各项指标匹配相应的权重,进而计算出路网级指路标志系统的评分,并对其现状情况进行评价。根据评价结果,进一步评估其需改造的力度。同理于路网级评价,借助于AHP法,对单条道路的指路标志系统也可进行评价,且道路级的评价成果能指导其施工改造。研究结合黄埔区评价实例,验证了评价指标体系的可靠性和适用性,实例证明该评价体系能作出科学合理的评判。AHP法应用广泛,如工程、工业、管理、商业等行业,但用在指路标志系统评价上的研究还不太多见,故具有一定的前瞻性和可借鉴性。     

Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam,Tanzania

The household travel survey (HTS) finds itself in the midst of rapid technological change. Traditional methods are increasingly being sidelined by digital devices and computational power—for tracking movements, automatically detecting modes and activities, facilitating data collection, etc.. Smartphones have recently emerged as the latest technological enhancement. FMS is a smartphone-based prompted-recall HTS platform, consisting of an app for sensor data collection, a backend for data processing and inference, and a user interface for verification of inferences (e.g., modes, activities, times, etc.). FMS, has been deployed in several cities of the global north, including Singapore. This paper assesses the first use of FMS in a city of the global south, Dar es Salaam. FMS in Dar was implemented over a 1-month period, among 581 adults chosen from 300 randomly selected households. Individuals were provided phones with data plans and the FMS app preloaded. Verification of the collected data occurred every 3 days, via a phone interview. The experiment reveals various social and technical challenges. Models of individual likelihood to participate suggest little bias. Several socioeconomic and demographic characteristics apparently do influence, however, the number of days fully verified per individual. Similar apparent biases emerge when predicting the likelihood of a given day being verified. Some risk of non-random, non-response is, thus, evident.     

Optimal Threshold Policies for Robust Data Center Control

With the simultaneous rise of energy costs and demand for cloud computing, efficient control of data centers becomes crucial. In the data center control problem, one needs to plan at every time step how many servers to switch on or off in order to meet stochastic job arrivals while trying to minimize electricity consumption. This problem becomes particularly challenging when servers can be of various types and jobs from different classes can only be served by certain types of server, as it is often the case in real data centers. We model this problem as a robust Markov decision process (i.e., the transition function is not assumed to be known precisely). We give sufficient conditions (which seem to be reasonable and satisfied in practice) guaranteeing that an optimal threshold policy exists. This property can then be exploited in the design of an efficient solving method, which we provide. Finally, we present some experimental results demonstrating the practicability of our approach and compare with a previous related approach based on model predictive control.     

Research on Web Page Classification Method Based on Query Log

Web page classification is an important application in many fields of Internet information retrieval, such as providing directory classification and vertical search. Methods based on query log which is a light weight version of Web page classification can avoid Web content crawling, making it relatively high in efficiency, but the sparsity of user click data makes it difficult to be used directly for constructing a classifier. To solve this problem, we explore the semantic relations among different queries through word embedding, and propose three improved graph structure classification algorithms. To reflect the semantic relevance between queries, we map the user query into the low-dimensional space according to its query vector in the first step. Then, we calculate the uniform resource locator (URL) vector according to the relationship between the query and URL. Finally, we use the improved label propagation algorithm (LPA) and the bipartite graph expansion algorithm to classify the unlabeled Web pages. Experiments show that our methods make about 20% more increase in F1-value than other Web page classification methods based on query log.