In this comment, we report a difficulty with the-application of the possibilistic approach to fuzzy clustering (PCM) proposed by Keller and Krishnapuram (1993). In applying this algorithm we found that it has the undesirable tendency to produce coincidental clusters. Results illustrating this tendency are reported and a possible explanation for the PCM behavior is suggested

This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented.

Accurate vessel detection in retinal images is an important and difficult task. Detection is made more challenging in pathological images with the presence of exudates and other abnormalities. In this paper, we present a new unsupervised vessel segmentation approach to address this problem. A novel inpainting filter, called neighborhood estimator before filling, is proposed to inpaint exudates in a way that nearby false positives are significantly reduced during vessel enhancement. Retinal vascular enhancement is achieved with a multiple-scale Hessian approach. Experimental results show that the proposed vessel segmentation method outperforms state-of-the-art algorithms reported in the recent literature, both visually and in terms of quantitative measurements, with overall mean accuracy of 95.62% on the STARE dataset and 95.81% on the HRF dataset.

. Purpose:  Fabry Disease (FD) is a rare X‐linked metabolic disorder characterized by diffuse deposition of sphingolipids in many tissues. Retinal vessel tortuosity is a common ocular manifestation in FD and may represent a useful marker for the disease. Unfortunately its clinical evaluation is poorly reproducibile and alternative means of evaluation may be of interest. We tested a new semi‐automatic software measuring retinal vessel tortuosity from eye fundus digital images in a group of FD patients. Methods:  Observational case‐control study evaluating four mathematical parameters describing tortuosity (relative length, sum of angle metric [SOAM], product of angle distance [PAD], triangular index) obtained from fundus pictures of 35 FD patients and 35 age‐matched controls. Only the right eye was considered in order to reduce bias. Mann–Whitney test was used to compare the FD group versus the control group, males versus females and patients with versus without clinically identified retinal vessels tortuosity in the FD group. Linear regression analysis was performed on a subgroup of patients to evaluate the possible association of retinal vessels tortuosity parameters with age and with markers of systemic disease’s progression. Results:  Three parameters (SOAM, PAD and triangular index) were significantly higher in FD patients in comparison with the controls (p < 0.0001, p = 0.001, p = 0.002 respectively). In the FD group the same three parameters showed higher values in hemizygous males than in heterozygous females ((p < 0.0001, p = 0.002, p < 0.0001 respectively). Conclusion:  A computer assisted analysis of retinal vasculature demonstrated an increased vessels tortuosity in FD patients. The technique might be useful to establish disease severity and monitor its progression.

The vector median filter has good filtering capabilities; nevertheless, its huge computational complexity significantly limits its practical usability. In this letter, a vector median filter based on a fast approximation of the euclidean norm is presented. The proposed algorithm couples computational and filtering effectiveness, and it is well suited for hardware implementation. Theoretical and experimental results regarding both approximation error and speed improvement prove the validity of the proposed algorithm.