Investigating the use of vague language as a communicative strategy in Chinese business negotiations

Chinese has long been perceived as being a hánxù (‘inscrutable’) language with indirect ways of communicating. This study aims to investigate indirectness in Chinese communication by exploring the use of vague language as a communicative strategy in Chinese business negotiations where vagueness plays a vital role in the communicative process. Vague language in this study is defined as inexplicit expressions used strategically, exemplified by diǎnr/yīdiǎnr (‘a little’), kěnéng (‘possibly’), dàyuē (‘about’), hěnduō (‘many’), and jīngcháng (‘often’), etc. It should not be confused with ‘misused language’. On the contrary, it is an integral part of the language and is indispensable in communication. This is one of the first attempts to study the use of vague language in real-life Chinese business negotiations, providing insights into the vagueness in Chinese language and developing possible models for effective communication in Chinese business discourse.This research is conducted by examining linguistic representations of vague language as they occur naturally in Chinese business negotiations. Through investigating the roles vague language plays in the real-life data with salient characteristics of inexplicitness, and its socio-cultural features, the research holistically addresses the questions of what lexical and syntactic patterns of vague language are frequently used in Chinese business negotiations, how negotiators interact in the realization of vagueness using sequential patterns, and what the pragmatic and cultural reasons for the use of vague language are.It is concluded that being communicative strategies, vague expressions should be as, or more, conventional and effective as non-vague expressions. Very often they may be preferable to non-vague expressions, because of their greater efficiency and relevance. The findings in this study are that while vague language is used for a combination of practical and interpersonal purposes, the priority is the practical functions. The ways in which it is mobilised are, in different shapes and forms and to lesser or greater degree, influenced by the social factors of age, social distance and gender. The findings of this study add an important dimension to the study of vague language and also have implications for the exploration of effective communication in general

Digital forensics challenges to big data in the cloud

As a new research area, Digital Forensics is a subject in a rapid development society. Cyber security for Big Data in the Cloud is getting attention more than ever. Computing breach requires digital forensics to seize the digital evidence to locate who done it and what has been done maliciously and possible risk/damage assessing what loss could leads to. In particular, for Big Data attack cases, Digital Forensics has been facing even more challenge than original digital breach investigations. Nowadays, Big Data due to its characteristics of three “V”s (Volume, Velocity, and Variety), they are either synchronized with Cloud (Such as smart phone) or stored on the Cloud, in order to sort out the storage capacity etc. problems, which made Digital Forensics investigation even more difficult. The Big Data-Digital Forensics issue for Cloud is difficult due to some issues. One of them is physically identify specific wanted device. Data are distributed in the cloud, customer or the digital forensics practitioner cannot have a fully access control like the traditional investigation does. The Smart City technique is making use of ICT (information communications technology) to collecting, detecting, analysing and integrating the key information data of core systems in running the cities. Meantime, the control is making intelligent responses to different requirements that include daily livelihood, PII (Personally identifiable information) security, environmental protection, public safety, industrial and commercial activities and city services. The Smart City data are Big Data, collected and gathered by the IoT (Internet of Things). This paper has summerised our review on the trends of Digital Forensics served for Big Data. The evidence acquisition challenge is discussed. A case study of a Smart City project with the IoT collected services Big data which are stored at the cloud computing environment is represented. The techniques can be generalised to other Big Data in the Cloud environment

4d4d steady gradient Ricci solitons with nonnegative curvature away from a compact set

In the paper, we analysis the asymptotic behavior of noncompact $\kappa$-noncollapsed steady gradient Ricci soliton $(M, g)$ with nonnegative curvature operator away from a compact set $K$ of $M$. In particular, we prove: any $4d$ noncompact $\kappa$-noncollapsed steady gradient Ricci soliton $(M^4, g)$ with nonnegative sectional curvature must be a Bryant Ricci soliton up to scaling if it admits a sequence of rescaled flows of $(M^4, g)$, which converges subsequently to a family of shrinking quotient cylinders.Comment: Proof of Proposition 4.1 has been modified. Also some typos are correcte

Federated Generative Learning with Foundation Models

Existing federated learning solutions focus on transmitting features, parameters or gadients between clients and server, which suffer from serious low-efficiency and privacy-leakage problems. Thanks to the emerging foundation generative models, we propose a novel federated learning framework, namely Federated Generative Learning, that transmits prompts associated with distributed training data between clients and server. The informative training data can be synthesized remotely based on received prompts containing little privacy and the foundation generative models. The new framework possesses multiple advantages, including improved communication efficiency, better resilience to distribution shift, substantial performance gains, and enhanced privacy protection, which are verified in extensive experiments on ImageNet and DomainNet datasets

The Long-Term Effectiveness of Eco-Driving Training: A Pilot Study

Eco-driving has been proven to have a great benefit in reducing vehicle fuel consumption in many developed countries. However, the potential of ecodriving on energy-saving in China is not very clear. Taking three taxi drivers from Beijing Beiqi Taxi Group Company as examples, the petrol consumption, travel distance and many other factors influencing vehicle fuel use before and after ecodriving training were collected through survey forms. The short-term and long-term effect of eco-driving was compared. The results showed that, taking one month as the statistical cycle, the benefit of eco-driving in saving fuel consumption averaged is 19.04%; while it reduced to 14.41% after four months from taking eco-driving training. Thus, drivers would partially regressed back to less economically driving behaviors and thus resulting in lower fuel savings after sometime. This study laid a foundation to evaluate the benefit of eco-driving in saving energy use