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Listing 27 manuscripts matching the search of "adaptation"

The challenge of the Paris Agreement to contain climate change

by E. Grigoroudis, F. Kanellos, V. S. Kouikoglou, Y. A. Phillis

Climate change due to anthropogenic CO 2 and other greenhouse gas emissions has had and will continue to have widespread negative impacts on human society and natural ecosystems. Drastic and concerted actions should be undertaken immediately if such impacts are to be prevented. The Paris Agreement on climate change aims to limit global mean temperature below 2 °C compared to the pre-industrial level. Using simulation and optimization tools and the most recent data, this paper investigates optimal emissions policies satisfying certain temperature constraints. The results show that only if we consider negative emissions coupled with drastic emissions reductions, temperature could be stabilized at about 2.5 °C, otherwise higher temperatures could possibly occur. To this end, two scenarios are developed based on the national emissions reduction plan of China and the USA. According to the simulation results, the objective of keeping temperature rise under 2 °C cannot be met. Clearly, negative emissions are needed if the Paris targets are to be given a chance for success. However, the feasibility of negative emissions mainly depends on technologies not yet developed. Reliance on future technological breakthroughs could very well prove unfounded and provide excuses for continued carbon releases with possible severe and irreversible climate repercussions. Thus, the Paris Agreement needs immediate amendments that will lead to stronger mitigation and adaptation commitments if it is to stay close to its goals.

Volume: 24, Issue: 2

A Hybrid Modular Context-Aware Services Adaptation For A Smart Living Room

by Moeiz Miraoui, Sherif El-etriby, Chakib Tadj, Abdulbasit Zaid Abid

Smart spaces have attracted considerable amount of interest over the past few years. The introduction of sensor networks, powerful electronics and communication infrastructures have helped a lot in the realization of smart homes. The main objective of smart homes is the automation of tasks that might be complex or tedious for inhabitants by distracting them from concentrating on setting and configuring home appliances. Such automation could improve comfort, energy savings, security, and tremendous benefits for elderly persons living alone or persons with disabilities. Context awareness is a key enabling feature for development of smart homes. It allows the automation task to be done pro-actively according to the inhabitant’s current context and in an unobtrusive and seamlessly manner. Although there are several works conducted for the development of smart homes with various technologies, in most cases, robust. However, the context-awareness aspect of services adaptation was not based on clear steps for context elements extraction (resp. clear definition of context). In this paper, we use the divide and conquer approach to master the complexity of automation task by proposing a hybrid modular system for context-aware services adaptation in a smart living room. We propose to use for the context-aware adaptation three techniques of machine learning, namely Naïve Bayes, fuzzy logic and case-based reasoning techniques according to their convenience.

Volume: 24, Issue: 2

An Improved Evolutionary Algorithm for Reducing the Number of Function Evaluations

by Erik Cuevas, Eduardo Santuario, Daniel Zaldivar, Marco Perez-Cisneros

Many engineering applications can be approached as optimization problems whose solution commonly involves the execution of computational expensive objective functions. Recently, Evolutionary Algorithms (EAs) are gaining popularity for solving complex problems that are encountered in many disciplines, delivering a more robust and effective way to locate global optima in comparison to classical optimization methods. However, applying EA2019s to real-world problems demands a large number of function evaluations before delivering a satisfying result. Under such circumstances, several EAs have been adapted to reduce the number of function evaluations by using alternative models to substitute the original objective function. Despite such approaches employ a reduced number of function evaluations, the use of alternative models seriously affects their original EA search capacities and their solution accuracy. Recently, a new evolutionary method called the Adaptive Population with Reduced Evaluations (APRE) has been proposed to solve several image processing problems. APRE reduces the number of function evaluations through the use of two mechanisms: (1) The dynamic adaptation of the population and (2) the incorporation of a fitness calculation strategy, which decides when it is feasible to calculate or only estimate new generated individuals. As a result, the approach can substantially reduce the number of function evaluations, yet preserving the good search capabilities of an evolutionary approach. In this paper, the performance of APRE as a global optimization algorithm is presented. In order to illustrate the proficiency and robustness of APRE, it has been compared to other approaches that have been previously conceived to reduce the number of function evaluations. The comparison examines several standard benchmark functions, which are commonly considered within the EA field. Conducted simulations have confirmed that the proposed method achieves the best balance over its counterparts, in terms of the number of function evaluations and the solution accuracy.

Volume: 22, Issue: 2

A Proxy-Based System For Dynamic Content Negotiation And Collaborative Optimization In Heterogenic Environments

by Xavier Sanchez-Loro, Victoria Beltran, Jordi Casademont, Marisa Catalan

Ubiquitous and Pervasive Computing relies on ubiquitous network access and applications’ context-awareness. This pervasive access implies exchanging traffic with a wide spectrum of devices across heterogenic networks. Services and applications deployed on these networks should adapt its operation and presentation to the characteristics of the underlying network technologies and the actual client device capabilities. Cellulaz wide azea networks like UMTS are used as Internet access networks for particular users but, in some cases, they can also be employed to provide Internet access to other smaller networks. The main inconvenient is that cellular networks have not the same bandwidth as wired networks and therefore, the cellular channel becomes a network bottle-neck. To help to mitigate this situation and in order to improve the user’s experience different optimization techniques exist, especially in web traffic. This paper studies the existing synergies at HTTP layer between device capabilities expression, content negotiation, channel optimization and content adaptation. And secondly, it presents a system where HTTP requests transmission is optimized by means of HTTP header reduction over the cellulaz channel, showing a significant improvement in response time. In order to allow content negotiation, headers should be restored when reaching the Internet. This dynamic header reconstruction allows giving enriched and more expressive information about user’s device and browser capabilities. Thus navigation speed and user’s QoE can be enhanced by means of dynamic content negotiation in order to obtain adapted and lighter content and responses from web servers and adaptation proxies alike.

Volume: 16, Issue: 4


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
PREVIOUS DOI PREFIX (with T&F): 10.1080/10798587
InCites Journal IMPACT FACTOR (JIF) Data

2018  0.790
2017  0.652
2016  0.644

Scimago Journal and Country Rank (SJR) Data

2018  0.993
2017  0.655
2016  0.660
SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."

Journal: 1995-Present


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