Abstract
Quality control inspection systems are crucial and a key factor in maintaining and ensuring the integrity of any product. The quality inspection task is a repetitive task, when performed by operators only, it can be slow and susceptible to failures due to the lack of attention and fatigue. This work focuses on the inspection of parts made of high-pressure diecast aluminum for components of the automotive industry. In the present case study, last year, 18240 parts needed to be reinspected, requiring approximately 96 hours, a time that could be spent on other tasks. This article performs a comparison of four deep learning models: Faster R-CNN, RetinaNet, YOLOv7, and YOLOv7-tiny, to find out which one is more suited to perform the quality inspection task of detecting metal filings on casting aluminum parts. As for this use-case the prototype must be highly intolerant to False Negatives, that is, the part being defective and passing undetected, Faster R-CNN was considered the bestperforming model based on a Recall value of 96.00%.

Abstract
Atanassov's intuitionistic fuzzy sets (A-IFSs) have been used recently to determine the optimal threshold value for gray-level image segmentation [1]. Atanassov's intuitionistic fuzzy index values are used for representing the unknowledge/ignorance of an expert on determining whether a pixel of the image belongs to the background or the object of the image. This optimal global threshold of the image is computed automatically, regardless of the actual image analysis process. Although global optimal thresholding techniques give good results under experimental conditions, when dealing with real images having several objects and the segmentation purpose is to point out some application-specific information, one should use heuristic techniques in order to obtain better thresholding results. This paper introduces an evolution of the above mentioned technique intended for use with such images. The proposed approach takes into account the image and segmentation specificities by using a two-step procedure, with a restricted set of the image gray-levels. Preliminary experimental results and comparison with other methods are presented.

Abstract
In this work, image segmentation is addressed as the starting point within a motion analysis methodology intended for biomechanics behavior characterization. First, we propose a general segmentation framework that uses Atanassov's intuitionistic fuzzy sets (A-IFSs) to determine the optimal image threshold value. Atanassov's intuitionistic fuzzy index values are used for representing the unknowledge/ignorance of an expert on determining whether a pixel belongs to the background or the object of the image. Then, we introduce an extension of this methodology that uses a heuristic based multi-threshold approach to determine the optimal threshold. Experimental results are presented.

Abstract
CRM systems mark a new paradigm with regard to the customization and qualification of services delivery and to the relationships between local government and citizens. CRM are strategic tools that enable to optimize the relationship between municipalities and residents, as well as the optimization of most organizational processes. Despite the acknowledged importance of such tools, it appears in practice that most Portuguese municipalities has not yet to implemented CRM systems. Trying to identify the main reasons for this fact, the authors undertook a study based on a questionnaire, and the main findings are presented and discussed in this paper.

Abstract
Radio Frequency Identification (RFID) is one of the automatic identification technologies more in vogue nowadays. There is a wide research and development in this area trying to take maximum advantage of this technology, and in coming years many new applications and research areas will continue to appear. This sudden interest in RFID also brings about some concerns, mainly the security and privacy of those who work with or use tags in their everyday life. RFID has, for some time, been used to access control in many different areas, from asset tracking to limiting access to restricted areas. In this paper we propose an architecture and a prototype of a system that uses distributed RFID over Ethernet and we demonstrate how to automate an entire students' attendance registration system by using RFID in an educational institution environment. Although the use of RFID systems in educational institutions is not new, it is intended to show how the use of it came to solve daily problems in our university. © 2008 IEEE.

Abstract
Currently, due to questions of financial order, the Internet Service Providers do not invest in rural areas, because the investment does not pay. This fact originates, more and more, the appearance of the so called WBN (Wireless Broadband Networks), that are going to supply Internet access to the populations, discriminated by this circumstance. The aspects related to the management of these networks are normally forgotten and today there is a lack of economically and technical viable solutions, that can efficiently help with this function, without use an enterprise solution. After an intensive research of commercial and opensource solutions of wireless networks management, it was checked an absence of an economically viable solution as well as an absence of a model of management for the WBN. This article contributes to the definition of a management model of these networks, using opensource tools. The proposal model is based on a centralized solution that congregates several modules of opensource tools, which can be able to respond to a wide range of features identified in the model. The simulation shows how the model presented, can be practicable and able to cover several functions in WBN management. © 2008 IEEE.