Global rates and patterns of channel migration in river deltas

River deltas are dynamic systems whose channels can widen, narrow, migrate, avulse, and bifurcate to form new channel networks through time. With hundreds of millions of people living on these globally ubiquitous systems, it is critically important to understand and predict how delta channel networks will evolve over time. Although much work has been done to understand drivers of channel migration on the individual channel scale, a global-scale analysis of the current state of delta morphological change has not been attempted. In this study, we present a methodology for the automatic extraction of channel migration vectors from remotely sensed imagery by combining deep learning and principles from particle image velocimetry (PIV). This methodology is implemented on 48 river delta systems to create a global dataset of decadal-scale delta channel migration. By comparing delta channel migration distributions with a variety of known external forcings, we find that global patterns of channel migration can largely be reconciled with the level of fluvial forcing acting on the delta, sediment flux magnitude, and frequency of flood events. An understanding of modern rates and patterns of channel migration in river deltas is critical for successfully predicting future changes to delta systems and for informing decision makers striving for deltaic resilience.

Design of an Adaptive Near Field Communication Technology using Finite State Machine within Web Services

The ongoing Web success can be related to its scalability and sustainability. Web Services (WSs) can provide different patterns for delivering software application abilities and the models by which enterprises and associated parties will trade. WSs represent a flexible way to offer existing components available to applications through the Internet. WSs are a new trend that shares ubiquitous systems with others. The popularity of Web is increasing with their associated systems. These systems play a significant key role as their compromise has a technical effect, and their need is rising. One of these systems is called Technology wireless (NFC). NFC is becoming an active area nowadays. The complexity of setting the NFC increases as the application, system architecture, and associated parts must satisfy various requirements of ever involving project scenarios. Several organizations are getting the benefit from the NFC. This paper will explore and develop an approach of developing a technique that will permit to exchange by technology wireless (NFC) data between the parties within a Web services environment. This technique has an advantage that facilitates the possibility of adopting such a system to decrease the time-cost and effort for staff and customers. Several means of mobile payments technique have been entitled and adopted this service in many countries, e.g., Europe, USA, Asia, and in the Middle East such as Saudi Arabia. Many users of these countries using a smartphone to pay services via their mobile phones for a wide range of activities. Consequently, this paper involves an agile technique of validating Finite State Machine (FSM) and JFLAP tools.

Reversal, Disconnect, and Proposition

This paper examines the potential countertactics of contemporary interactive media art to interrogate the data-mining practices that encode the everyday and exploit user data in the big data economy. It argues that noise is the "other" of information, a way to counter the operation of turning the world into data commodities. Through a Brechtian methodology informed by philosophy and critical theories of media and technology, the paper suggests that amplifying the "noise" of the digital media assemblages deviates from their everyday normative functions and estranges our relationship to them, inviting critical ways of understanding, relating to, and engaging these ubiquitous systems. All three noted artworks destabilize the protocols of data-mining to examine data politics. Specifically, the paper looks at three different tactics that amplify the "noise" of digital culture in different ways: reversing roles, disconnecting, and proposing viable alternatives.

AI’S Contribution to Ubiquitous Systems and Pervasive Networks Security – Reinforcement Learning vs Recurrent Networks

Reinforcement learning and recurrent networks are two emerging machine-learning paradigms. The first learns the best actions an agent needs to perform to maximize its rewards in a particular environment and the second has the specificity to use an internal state to remember previous analysis results and consider them for the current one. Research into RL and recurrent network has been proven to have made a real contribution to the protection of ubiquitous systems and pervasive networks against intrusions and malwares. In this paper, a systematic review of this research was performed in regard to various attacks and an analysis of the trends and future fields of interest for the RL and recurrent network-based research in network security was complete.

ePassport and eID Technologies

This chapter is devoted to the design and implementation of electronic ID (eID) such as ePassports and electronic personal identity documents. We present an overview of existing and emerging concepts, both concerning threats and possible countermeasures. Thereby we aim to shed light on the development of ubiquitous systems, where many artifacts will require strong electronic identification with similar properties to those in the case of eIDs issued for humans.

Side Channel Assessment Platforms and Tools for Ubiquitous Systems

Side Channel Attacks are nowadays considered a serious risk for many security products and ubiquitous devices. Strong security solution providers need to evaluate their implementations against such attacks before publishing them on the market, thus performing a thorough assessment. However, this procedure is not straightforward and even with the appropriate equipment, it may require considerable time to provide results due to the slow process of collecting measurements (traces) and the inflexible way of controlling the tested implementation. In this chapter, we explore and overview the trace collection landscape for generic devices under test (including ubiquitous systems) highlighting and overviewing the latest trace collection toolsets and their shortcomings, but also proposing a trace collection approach that can be applied on the most recent, open source toolsets. We showcase our proposed approach on the FlexLeco project architecture, which we have developed in our lab, and manage to practically describe how an evaluator using the proposed methodology can collect traces easily and quickly without the need to completely redesign a control mechanism for the implementation under test.