Image analysis of microstructural changes in almond cotyledon as a result of processing

Release of oil from nuts due to damaged cellular structures can degrade the quality of products incorporating nuts. The aim of this study was to investigate the effects of different processing conditions on microstructure of almond tissue and to quantify these changes using image processing. Spinning disk confocal fluorescence microscopy was used for imaging changes in microstructure of almonds as a function of different thermal processing of almonds. Multiple staining of Nile Red and Calcofluor White was applied to differentiate cell wall structures and oil bodies within individual almond cells without chemical fixation. An algorithm for image processing, included image preprocessing, segmentation, and determination of morphological features of segmented objects, was developed. Oil-roasting processes (140 °C and 150 °C) were found to have a significant impact on microstructure of almonds when compared to the hot air-roasting and blanching processes. Oil-roasted almond at 150 °C had a greater cellular damage due to cell wall and membrane rupture. These changes in microstructure of almonds would make them slightly more susceptible to release oil during storage. The image analysis presented allows quantitative evaluation for the effect of different processing on almond microstructure.     

Formal modeling and verification of software‐defined networks: A survey

Unlike traditional networking devices, control and management plane are decoupled from data plane in software‐defined networks (SDN). The logically centralized control and management plane facilitate dynamic orchestration of network resources, services, and policies by writing software programs. This provides much needed flexibility and programmability where networking rules and policies can be modified dynamically depending upon the application context. As the operation of network services entirely depends on a program, a small fault may induce several issues which can adversely affect the expected behavior of the network. Formal modeling and verification help in catching inconsistencies and existence of errors prior to the deployment of the programs that control the behavior of a network. In this paper, we provide a comprehensive survey of tools and techniques available in the literature for formal modeling and verification of SDN. These tools and techniques are classified based on their types, the components of SDN where they can be applied, and the design and development phase when they are utilized. In particular, their respective benefits and limitations are discussed in terms of ease of use, interfaces, and the ability to capture and verify intended network properties.     

Design of wideband comb shape substrate integrated waveguide multimode resonator bandpass filter with high selectivity and improved upper stopband performance

In this article, a wideband bandpass filter (BPF) is designed using the comb slotted substrate integrated waveguide (SIW) cavities. The comb‐shaped slots engraved on the SIW cavity are used to constitute a novel multiple‐mode resonator (MMR) that accomplishes a wide passband of operation. Further, a Jerusalem cross defected ground structure (DGS) is introduced to miniaturize it and enhance filter performance in the pass band and stop band. The filter is fabricated on RT/Duroid 5880 having dielectric constant 2.2 and tested to prove the validity of design. The filter achieves 3 dB fractional bandwidth of 48%, return loss above 14 dB and insertion loss of 1.1 dB in the passband. Also, the proposed filter has steep selectivity and wide upper stopband with 25 dB attenuation from 16.7 to 24 GHz.     

RP-LPP : a random permutation based locality preserving projection for cancelable biometric recognition

Biometrics are being increasingly used across the world, but it also raises privacy and security concerns of the enrolled identities. The main reason is due to the fact that biometrics are not cancelable and if compromised may give access to the intruder. Cancelable biometric template is a solution to this problem which can be reissued if compromised. In this paper, we suggest a simple and powerful method called Random Permutation Locality Preserving Projection (RP-LPP) for Cancelable Biometric Recognition. Here, we exploit the mathematical relationship between the eigenvalues and eigenvectors of the original biometric image and its randomly permuted version is exploited for carrying out cancelable biometric recognition. The proposed technique work in a cryptic manner by accepting the cancelable biometric template and a key (called PIN) issued to a user. The effectiveness of the proposed techniques is demonstrated on three freely available face (ORL), iris (UBIRIS) and ear (IITD) datasets against state-of-the-art methods. The advantages of proposed technique are (i) the classification accuracy remains unaffected due to cancelable biometric templates generated using random permutation, (ii) security and quality of generated templates and (iii) robustness across different biometrics. In addition, no image registration is required for performing recognition.

     

Load balancing aware scheduling algorithms for fog networks

Fog networks have attracted the attention of researchers recently. The idea is that a part of the computation of a job/application can be performed by fog devices that are located at the network edge, close to the users. Executing latency sensitive applications on the cloud may not be feasible, owing to the significant communication delay involved between the user and the cloud data center (cdc). By the time the application traverses the network and reaches the cloud data center, it might already be too late. However, fog devices, also known as mobile data centers (mdcs), are capable of executing such latency sensitive applications. In this paper, we study the problem of balancing the application load while taking account of security constraints of jobs, across various mdcs in a fog network. In case a particular mdc does not have sufficient capacity to execute a job, the job needs to be migrated to some other mdc. To this end, we propose three heuristic algorithms: minimum distance, minimum load, and minimum hop distance and load (MHDL). In addition, we also propose an ILP-based algorithm called load balancing aware scheduling ILP (LASILP) for solving the task mapping and scheduling problem. The performance of the proposed algorithms have been compared with the cloud only algorithm and another heuristic algorithm called fog-cloud-placement (FCP). Simulation results performed on real-life workload traces reveal that the MHDL heuristic performs better as compared to other scheduling policies in the fog computing environment while meeting application privacy requirements.     

Trust-aware energy-efficient stable clustering approach using fuzzy type-2 Cuckoo search optimization algorithm for wireless sensor networks

Wireless Networks - With the advancement of communication and sensor technologies, it has become possible to develop low-cost circuitry to sense and transmit the state of surroundings. Wireless...     

Enhancing data delivery with density controlled clustering in wireless sensor networks

Microsystem Technologies - Wireless sensor networks (WSN) are primarily used for sensing and collecting the information from environment. This information is sent to base station (BS), where, it is...     

A stable energy efficient clustering protocol for wireless sensor networks

Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.     

High-performance elastomeric nanocomposites via solvent-exchange processing

The incorporation of nanoparticles into engineering thermoplastics affords engineers an opportunity to synthesize polymer nanocomposites that potentially rival the most advanced materials in nature. Development of these materials is difficult because thermodynamic and kinetic barriers inhibit the dispersal of inorganic, often hydrophilic nanoparticles in hydrophobic polymer matrices. Using a new solvent-exchange approach, we preferentially reinforce the hard microdomains of thermoplastic elastomers with smectic clay of similar characteristic dimensions. The strong adhesion between the clay and the hard microdomains coupled with the formation of a percolative network not only stiffens and toughens, but increases the heat distortion temperature of the material and induces reversible thermotropic liquid-crystalline transitions. The discotic clay platelets induce morphological ordering over a range of length scales, which results in significant thermomechanical enhancement and expands high-temperature applications. Merging block-copolymer processing techniques with this method for preferential ordering of nanoparticle facilitates the development of new, hierarchically ordered materials.