13,359 research outputs found
Intelligent Agents for Disaster Management
ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains
Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data
In the context of a myriad of mobile apps which collect personally
identifiable information (PII) and a prospective market place of personal data,
we investigate a user-centric monetary valuation of mobile PII. During a 6-week
long user study in a living lab deployment with 60 participants, we collected
their daily valuations of 4 categories of mobile PII (communication, e.g.
phonecalls made/received, applications, e.g. time spent on different apps,
location and media, photos taken) at three levels of complexity (individual
data points, aggregated statistics and processed, i.e. meaningful
interpretations of the data). In order to obtain honest valuations, we employ a
reverse second price auction mechanism. Our findings show that the most
sensitive and valued category of personal information is location. We report
statistically significant associations between actual mobile usage, personal
dispositions, and bidding behavior. Finally, we outline key implications for
the design of mobile services and future markets of personal data.Comment: 15 pages, 2 figures. To appear in ACM International Joint Conference
on Pervasive and Ubiquitous Computing (Ubicomp 2014
New technologies for e-commerce
Today electronic commerce (e-commerce) has changed the way of doing business, and
contributes significantly to economic activity. In any case, e-commerce is not a static field but
it is always evolving in order to support new and more complex real world processes. The
agriculture sector is expected to undergo significant transformation as a result of new business
models being adopted through ecommerce. Examples of the adoption of new technologies in
agriculture are provided with a view to demonstrating the benefits that can be achieved. The
first part I expound the basics of e-commerce and e-markets. After I describe potential
benefits to agriculture from adoption of e-commerce. The last part I describe the ecommerce
2.0, what is a prospect evolution of e-commerce
Fairs for e-commerce: the benefits of aggregating buyers and sellers
In recent years, many new and interesting models of successful online
business have been developed. Many of these are based on the competition
between users, such as online auctions, where the product price is not fixed
and tends to rise. Other models, including group-buying, are based on
cooperation between users, characterized by a dynamic price of the product that
tends to go down. There is not yet a business model in which both sellers and
buyers are grouped in order to negotiate on a specific product or service. The
present study investigates a new extension of the group-buying model, called
fair, which allows aggregation of demand and supply for price optimization, in
a cooperative manner. Additionally, our system also aggregates products and
destinations for shipping optimization. We introduced the following new
relevant input parameters in order to implement a double-side aggregation: (a)
price-quantity curves provided by the seller; (b) waiting time, that is, the
longer buyers wait, the greater discount they get; (c) payment time, which
determines if the buyer pays before, during or after receiving the product; (d)
the distance between the place where products are available and the place of
shipment, provided in advance by the buyer or dynamically suggested by the
system. To analyze the proposed model we implemented a system prototype and a
simulator that allow to study effects of changing some input parameters. We
analyzed the dynamic price model in fairs having one single seller and a
combination of selected sellers. The results are very encouraging and motivate
further investigation on this topic
NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks
With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)
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