Home automation has achieved a lot of popularity in recent years, as day-to-day life is getting simpler due to the rapid growth of technology. Almost everything has become digitalized and automatic. In this paper, a system for interconnecting sensors, actuators, and other data sources with the purpose of multiple home automations is proposed. The system is called qToggle and works by leveraging the power of a flexible and powerful Application Programming Interface (API), which represents the foundation of a simple and common communication scheme. The devices used by qToggle are usually sensors or actuators with an upstream network connection implementing the qToggle API. Most devices used by qToggle are based on ESP8266/ESP8285 chips and/or on Raspberry Pi boards. A smartphone application has been developed that allows users to control a series of home appliances and sensors. The qToggle system is user friendly, flexible, and can be further developed by using different devices and add-ons.

Image segmentation operation has a great importance in most medical imaging applications, by extracting anatomical structures from medical images. There are many image segmentation techniques available in the literature, each of them having advantages and disadvantages. The extraction of bone contours from X-ray images has received a considerable amount of attention in the literature recently, because they represent a vital step in the computer analysis of this kind of images. The aim of X-ray segmentation is to subdivide the image in various portions, so that it can help doctors during the study of the bone structure, for the detection of fractures in bones, or for planning the treatment before surgery. The goal of this paper is to review the most important image segmentation methods starting from a data base composed by real X-ray images. We will discuss the principle and the mathematical model for each method, highlighting the strengths and weaknesses

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COVID-19 (Coronavirus) has affected our day to day life and the global economy and is far from being over. COVID-19 continues to spread rapidly around the world, more with the relaxation of restriction measures imposed by most countries. Limiting the further community spread of the epidemic has become a crucial issue, as employees return to office buildings. Technology, and especially intelligent building technology, can help to this purpose. Smart devices will have an important role to play in determining how the new normal workplace will function from now on. In this paper, we propose a solution for avoiding touching various objects and surfaces in offices, based on IoT. The system is called qToggle and provides a framework for efficiently and effectively interconnecting smart devices, equipping them with intelligence that helps automating many of the everyday activities in offices. Most qToggle devices are based on ESP8266/ESP8285 chips, Raspberry Pi boards and smart sensors. A mobile application allows users to control a series of appliances and sensors.

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The goal of this paper is to highlight the particularities of Worldwide Interoperability for Microwave Access (WiMAX) traffic from a long‐range dependence perspective. The application presented in this paper consists in the estimation of the quality of base stations (BS) positioning in the architecture of a WiMAX network. Analysing the traffic of the considered WiMAX network, with an original data mining methodology based on long‐range dependence, we determine which BS have a correct position in the topology of the network and which BS have an incorrect position. These BS must be repositioned when the next session of the network maintenance will take place.

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