Abstract
The alignment of the information technology implementation with the ever-changing business strategies in an enterprise drives modernization of the legacy system. However, the existing modernization contexts have not adequately addressed the focus of customer experience and service-orientation within the SaaS system development. This paper investigates the modernization process of legacy system into SaaS system using services concept through multidisciplinary approach. Several best practices are discussed to propose the Service-Oriented Modernization Framework (SOMF) which involves the maturity model for evolution roadmap identification, the service-oriented SaaS reference architecture, and the User-Centered Service-Oriented Software Reengineering (UCSOSR) methodology. An industrial case study is demonstrated by applying the framework to develop the public transport document generator as a service. The modernization process described in the framework provides a comprehensive and systematic guideline in developing a scalable system. In conclusion, this research, by integrating service analysis and design with SOA towards the SaaS modernization, enables the creation of an agile business model to achieve competitive advantages.

Abstract

Abstract
While bottom-up approaches to object recognition are simple to design and implement, they do not yield the same performance as top-down approaches. On the other hand, it is not trivial to obtain a moderate number of plausible hypotheses to be efficiently verified by top-down approaches. To address these shortcomings, we propose a hybrid top-down bottom-up approach to object recognition where a bottom-up procedure that generates a set of hypothesis based on data is combined with a top-down process for evaluating those hypotheses. We use the recognition of rectangular cuboid shaped objects from 3D point cloud data as a benchmark problem for our research. Results obtained using this approach demonstrate promising recognition performances.

Abstract
Model-checking is increasingly popular in the early phases of the software development process. To establish the correctness of a software design one must usually verify both structural and behavioral(or temporal) properties. Unfortunately, most specification languages, and accompanying model-checkers, excel only in analyzing either one or the other kind. This limits their ability to verify dynamic systems with rich configurations: systems whose state space is characterized by rich structural properties, but whose evolution is also expected to satisfy certain temporal properties. To address this problem, we first propose Electrum, an extension of the Alloy specification language with temporal logic operators, where both rich configurations and expressive temporal properties can easily be de fined. Two alternative model-checking techniques are then proposed, one bounded and the other unbounded, to verify systems expressed in this language, namely to verify that every desirable temporal property holds for every possible configuration.

Abstract
Buffer caching mechanisms are paramount to improve the performance of today's massive scale NoSQL databases. In this work, we show that in fact there is a direct and univocal relationship between the resource usage and the cache hit ratio in NoSQL databases. In addition, this relationship can be leveraged to build a mechanism that is able to estimate resource usage of the nodes composing the NoSQL cluster.

Abstract
HARMONI is a visible and NIR integral field spectrograph, providing the E-ELT's core spectroscopic capability at first light. HARMONI will work at the diffraction limit of the E-ELT, thanks to a Classical and a Laser Tomographic AO system. In this paper, we present the system choices that have been made for these SCAO and LTAO modules. In particular, we describe the strategy developed for the different Wave-Front Sensors: pyramid for SCAO, the LGSWFS concept, the NGSWFS path, and the truth sensor capabilities. We present first potential implementations. And we asses the first system performance.