Abstract
Unified communications (UC) have the potential to dramatically simplify and improve enterprise communications, reducing costs and improving revenue opportunities. By integrating various forms of communications, such as voice, video, instant messaging, conferencing, presence and voicemail, individuals and groups can more effectively control and manage their inbound and outbound communications sessions. However, Large Enterprises (LE) and Small & Medium Enterprises (SMEs) have a diverse perspective look of UC and different needs. In this paper we will analyze the reasons that motivate the business leaders to introduce unified communications and we will study with detail the large enterprises and SMEs approach for the implementation of a unified communications solution. © 2009 IADIS.

Abstract
Unified Communications (UC) have the potential to dramatically simplify and improve enterprise communications, reducing costs and improving revenue opportunities. However, these benefits do not come without risks. The introduction of an IP-based UC solution brings an array of new vulnerabilities into the enterprise, exploited by a growing number of malicious programs. This paper presents the most common of risks faced by the major dominant technologies used in unified communications solutions and an approach to mitigate them.

Abstract
Two programs were recently developed for the aesthetic evaluation of results in breast cancer conservative treatment: the Breast Cancer Conservative Treatment cosmetic results (BCCT.core) and the Breast Analyzing Tool (BAT). Both make use of a face-only photographic view of the patient and were developed to overcome the lack of reproducibility observed with subjective visual evaluation. The BCCT.core analyses several parameters related to asymmetry, color differences and scar appearance, while the BAT considers only asymmetry measurements. The purpose of this study was to compare the performance of these two methods. Material and methods Digital pictures of 59 patients from Porto and 60 from Vienna were evaluated subjectively by two panels using the four-class Harris scale. The Porto photographs had a similar backlight and better quality, and were evaluated by an international panel of 23 experts. The Vienna photographs had different backlight and lower quality, and were evaluated by four students and two breast cancer specialists. All 119 cases were submitted to analysis using the BCCT.core and BAT. Agreement between the software programs and the subjective evaluation was calculated using kappa (k), weighted kappa statistics (wk) and error rate (er). Results In overall analysis, BCCT.core program obtained a better agreement with the subjective evaluation (k = 0.56; wk = 0,64; er = 0.20) than the BAT software (k = 0.39; wk = 0.46; er = 0.42) (P < 0.0007). Results were again better for the BCCT.core program, when analysing the photographs obtained in Porto (k = 0.71; wk = 0.78; er = 0.14) than for the BAT (k = 0.35; wk = 0.41; er = 0.51) (P < 0.0003) while no significant differences in agreement were obtained regarding the Vienna images (P > 0.1). Conclusions The results suggest that the inclusion of multiple parameters in image analyses of aesthetic results has the potential to improve results. However, picture quality is probably important for analysis of other features besides asymmetry.

Abstract
Text line segmentation in freestyle handwritten documents remains an open document analysis problem. Curvilinear text lines and small gaps between neighbouring text lines present a challenge to algorithms developed for machine-printed or hand-printed documents. We investigate a general-purpose, knowledge-free method for the automatic detection of text lines based on a stable path approach. Lines affected by curvature and inclination are robustly detected. The proposed methodology was tested on a modern set of handwritten images made available on the ICDAR 2009 handwriting segmentation competition, with promissing results. © 2009 IEEE.

Abstract
In this work we consider the problem of binary classification where the classifier may abstain instead of classifying each observation, leaving the critical items for human evaluation. This article motivates and presents a novel method to learn the reject region on complex data. Observations are replicated and then a single binary classifier determines the decision plane. The proposed method is an extension of a method available in the literature for the classification of ordinal data. Our method is compared with standard techniques on synthetic and real datasets, emphasizing the advantages of the proposed approach.

Abstract
Media content adaptation is the action of transforming media files to adapt to device capabilities, usually related to mobile devices that require special handling because of their limited computational power, small screen size and constrained keyboard functionality. Image retargeting is one of such adaptations, transforming an image into another with different size. Tools allowing the author to imagery once and automatically retarget that imagery for a variety of different display devices are therefore of great interest. The performance of these algorithms is directly related with the preservation of the most important regions and features of the image. In this work, we introduce an algorithm for automatically retargeting images. We explore and extend a recently proposed algorithm on the literature. The central contribution is the introduction of the stable paths for image resizing, improving both the computational performance and the overall quality of the resulting image. The experimental results confirm the potential of the proposed algorithm.