Smart phones are conquering the mobile phone market; they are not just phones they also act as media players, gaming consoles, personal calendars, storage, etc. They are portable computers with fewer computing capabilities than personal computers. However unlike personal computers users can carry their smartphone with them at all times. The ubiquity of mobile phones and their computing capabilities provide an opportunity of using them as a life logging device. Life-logs (personal e-memories) are used to record users' daily life events and assist them in memory augmentation. In a more technical sense, life-logs sense and store users' contextual information from their environment through sensors, which are core components of life-logs. Spatiotemporal aggregation of sensor information can be mapped to users' life events. We propose UbiqLog, a lightweight, configurable and extendable life-log framework that uses mobile phone as a device for life logging. The proposed framework extends pre- vious research in this field, which investigated mobile phones as life-log tool through continuous sensing. Its openness in terms of sensor configuration allows developers to create flexible, multipurpose life-log tools. In addition to that this framework contains a data model and an architecture, which can be used as reference model for further life-log development, including its extension to other devices, such as ebook readers, T.V.s, etc.

Agroforestry systems may play a critical role in reducing the vulnerability of farmers' livelihood to droughts as tree-based systems provide several mechanisms that can mitigate the impacts from extreme weather events. Here, we use a replicated throughfall reduction experiment to study the drought response of a cacao/Gliricidia stand over a 13-month period. Soil water content was successfully reduced down to a soil depth of at least 2.5 m. Contrary to our expectations we measured only relatively small nonsignificant changes in cacao (À11%) and Gliricidia (À12%) sap flux densities, cacao leaf litterfall ( 1 8%), Gliricidia leaf litterfall (À2%), soil carbon dioxide efflux (À14%), and cacao yield (À10%) during roof closure. However, cacao bean yield in roof plots was substantially lower (À45%) compared with control plots during the main harvest following the period when soil water content was lowest. This indicates that cacao bean yield was more sensitive to drought than other ecosystem functions. We found evidence in this agroforest that there is complementary use of soil water resources through vertical partitioning of water uptake between cacao and Gliricidia. This, in combination with acclimation may have helped cacao trees to cope with the induced drought. Cacao agroforests may thus play an important role as a drought-tolerant land use in those (sub-) tropical regions where the frequency and severity of droughts is projected to increase.

In this short editorial we present some thoughts on present and future trends in Artificial Intelligence (AI) generally, and Machine Learning (ML) specifically. Due to the huge ongoing success in machine learning, particularly in statistical learning from big data, there is rising interest of academia, industry and the public in this field. Industry is investing heavily in AI, and spin-offs and start-ups are emerging on an unprecedented rate. The European Union is allocating a lot of additional funding into AI research grants, and various institutions are calling for a joint European AI research institute. Even universities are taking AI/ML into their curricula and strategic plans. Finally, even the people on the street talk about it, and if grandma knows what her grandson is doing in his new start-up, then the time is ripe: We are reaching a new AI spring. However, as fantastic current approaches seem to be, there are still huge problems to be solved: the best performing models lack transparency, hence are considered to be black boxes. The general and worldwide trends in privacy, data protection, safety and security make such black box solutions difficult to use in practice. Specifically in Europe, where the new General Data Protection Regulation (GDPR) came into effect on May, 28, 2018 which affects everybody (right of explanation). Consequently, a previous niche field for many years, explainable AI, explodes in importance. For the future, we envision a fruitful marriage between classic logical approaches (ontologies) with statistical approaches which may lead to context-adaptive systems (stochastic ontologies) that might work similar as the human brain.

This paper is aiming at illustrating the potential of ICT for achieving the Sustainable Development Goals which were declared by the United Nations in 2015 as binding for all nations of our planet addressing both developing and developed countries. ICT must play a significant role if the SDGs should be achieved as projected in 2030. The paper gives an overview of some of the existing efforts in this area and is written as an appeal to all professionals, scientists and IT-professional and their organization to take a holistic approach for all ICT-activities and projects to always include and monitor the effects of their work on the SDGs. The impacts of ICT on sustainability are twofold: On the one hand there might be negative effects on sustainability such as the generation of electronic waste, on the other hand ICT is definitely an enabler to more efficient resource usage, education and business operations which is critical success factor for achieving the SDGs.