Wireless sensor networks (WSN) are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH) while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

A study of textural changes is presented concerning the nematic phase of 4-n-alkyloxybenzoic acids (in particular, 4-n-heptyl-and 4-n-octyl-oxybenzoic acids), by means of a statistical approach to the image data observed by polarized light microscopy (orthoscopic mode). A new image processing method is developed in order to detect with high sensitivity any structural change in the image frame. To do this, a set of parameters is introduced, charaterizing the observed textures. Such a set is a vector, working like a path® nder strongly increasing the human eyeÐ or in general the sensor Ð skilfulness to appreciate any change of the optical texture, both in space and in time. This is suitable for revealing smooth transitions, such as phase transitions between smectic and nematic phases (or between di erent smectic phases), or order transitions, like alignment transitions in poorly oriented nematic layers. In fact, by using this method for detecting the order transition between two nematic`subphases' of 4-n-alkyloxybenzoic acids, the sensitivity turns out to be enhanced by a factor higher than 10 with respect to that for standard techniques. The new method allows us to de® ne a characteristic size of the image texture: this concept is applied to analyse several image data for estimating the mean size of the domains appearing in the smectic and in the nematic phase of the compounds under study.

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Traceability is a key factor for the agri-food sector. RFID technology, widely adopted for supply chain management, can be used effectively for the traceability management. In this paper, a framework for the evaluation of a traceability system for the agri-food industry is presented and the automation level in an RFID-based traceability system is analyzed and compared with respect to traditional ones. Internal and external traceability are both considered and formalized, in order to classify different environments, according to their automation level. Traceability systems used in a sample sector are experimentally analyzed, showing that by using RFID technology, agri-food enterprises increase their automation level and also their efficiency, in a sustainable way.