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IoT cloud-based connected smart dustbins (equipped with sensors) are imperative for efficient waste management in smart city. Municipal agencies can reduce the use of both man and machine by cutting down their overall waste collection route distance as well as number of waste collection vehicles (WCVs) by deploying this proposed cyber-physical system for route optimization of WCVs with capacitated vehicle-routing model. A novel cost function is mathematically modelled using data from dustbin-sensors and real-time road-traffic with modified Dijkstra's algorithm for optimisation of WCVs routes. Amount of solid waste in the dustbin (GC in %), rate of the filling (ΔG) and real-time/dynamic road traffic information from Google distance matrix advanced application programming interface (API) are used for estimation of the optimised route for WCVs. Optimisation goal of this work is to reduce both capital expense (CapEx) and operational expense (OpEx) of solid waste collection in the city by cutting the WCV fleet size and reducing overall distance covered by WCVs. The proposed route optimisation technique is analytically simulated for Bhubaneswar smart city and the result shows 30.28% saving in overall WCVs route distance and hence reducing OpEx around 29.07% and CapEx around 26.83% by reducing WCV fleet size.

The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation. Furthermore, to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 96.51% accuracy, 94.2% specificity, and 97.72% sensitivity, demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 0.82 dice similarity index coefficient, which indicates better overlap between the automated (machines) extracted tumor region with manually extracted tumor region by radiologists. The simulation results prove the significance in terms of quality parameters and accuracy in comparison to state-of-the-art techniques.

The echo signal amplitude received by radar is very low, necessitating signal amplification for effective detection and processing. A Low Noise Amplifier (LNA) has been developed to boost signal amplitude without adding extra noise. This paper presents innovative techniques such as gm-boosting, RC coupling, an L-type matching network, and common source inductive degeneration. These techniques achieve a wide bandwidth of 1.3 GHz (4.7 to 6 GHz) and a low undesired signal level of 0.8 dB. The bias network enhances transconductance, resulting in a gain of 36-40 dB, while the RC coupling network ensures stability from DC to 36 GHz. The LNA achieves an output 1 dB compression point of 9 dBm, an OIP3 of 23.91 dBm, a sensitivity of -137.8 dBm, a linear dynamic range of 108.8 dB, and a spurious free dynamic range of 87.87 dB. This LNA operates well in RF interference environments and demonstrates strong detection capability and linearity. Built on GaAs technology, the MMIC circuit has a compact footprint of 3.5052 mm². This efficient LNA boosts the tracking range from 128 km to 243 km when integrated into larger systems.

Diseases in aquatic organisms, including fish, are a major concern in aquaculture production. In this present investigation, we have evaluated the beneficial effects of dietary Bacillus amyloliquefaciens CCF7 (GenBank Acc. No. KP256501) supplementation in rohu ( Labeo rohita ) challenged by a pathogenic strain of Aeromonas hydrophila MTCC 1739. Four experimental diets were formulated: control diet (no probiotics) and three experimental diets (different concentrations of probiotic candidate B. amyloliquefaciens CCF7 at 10 5 (T1), 10 7 (T2), 10 9 (T3) CFU/g). Further, we have divided the feeding trial into pre-challenge (70 days) and post-challenge (28 days) periods and various immune parameters (serum protein, globulin, albumin, lysozyme, and IgM), and stress parameters (malondialdehyde, catalase, and superoxide dismutase) were examined during both the periods. Throughout the entire experiment, control group was fed with probiotic free basal diet, while the treatment groups received probiotic supplemented diets (PSD). After challenge test, serum aspartate transaminase (AST), serum alanine transaminase (ALT) activity, and liver malondialdehyde level have increased significantly in control groups; however, level of these parameters were considerably lower in fish fed with PSD. In contrast, liver catalase and superoxide dismutase activities and serum globulin concentration was significantly higher in the group fed with T3 diet followed by T2. Furthermore, an elevated level of serum IgM and higher activity of serum lysozyme was also recorded in PSD fed groups, especially for T3 group which confirmed the probiotic efficiency of the bacterium B. amyloliquefaciens CCF7. We strongly believe that B. amyloliquefaciens CCF7 will be a good probiotic candidate in aquaculture industries.

In this paper, we present a survey concerned with research focusing on the convergence of wireless sensor networks (WSN) and mobile cellular networks (MCN). The convergence of WSNs and MCNs may be a trigger stimulating new research dealing with such issues as architecture, protocols and air interfaces. The highlights and constraints of the phenomenon are discussed in this paper as well. The survey deals with convergence networks and with their smarty city applications. A few open research issues are also brought to the attention of researchers specializing in this field

The digestion process in fish is a complex phenomenon and is accomplished with the help of both endogenous and exogenous enzymes. A wide range of enzymes have been reported in fish and their secretion and concentrations highly depend on feeding habits, gut structure and environmental conditions. In this present investigation, we have demonstrated the activity of two endogenous enzymes (protease and amylase) in four economically important air-breathing fish species (Clarias batrachus, Channa punctatus, Anabas testudineus and Heteropneustes fossilis) at different seasonal temperatures. Our results demonstrated that protease activity was higher in all fish during the month of May, followed by September and December. It was also detected that enzyme activity was higher in the hindgut region (HG) compared to the foregut (FG), which suggests that HG is more active in digestion compared to FG. The optimization of feeding efficiency in aquaculture industries is very important, as the cost of feed is high and its availability is also limited. The information presented may be of importance when developing optimized diets and feeding regimes for the species considered.

Background In India, fishmeal is habitually considered as the major protein source for fish culture. Rising cost, deteriorating quality and unavailability of fishmeal caused huge difficulty in modern aquaculture, particularly for fish nutrition. Nearly all Anabas testudineus cultures faced loss, due to high feed costs, inappropriate feed formulation and management. So it was necessary to find a profitable replacement of fishmeal, which could provide better growth performance to A. testudineus . Results In this study, different types of poultry wastes were tested, and poultry viscera confirmed satisfactory results, having 60.67 % crude protein (% Dry matter basis). Further, a feeding trial was conducted for 60 days in 90-L circular fibre tanks with proper aeration, to evaluate poultry viscera, in the formulated diet for A. testudineus . Triplicate groups of fingerlings each were fed four isonitrogenous diets, at 5 % of wet body weight basis. Feed readjusted biweekly. Comparatively, fish accumulated highest and significant ( P  < 0.05) increase in body weight and fat deposition, when dietary fishmeal completely replaced by poultry viscera. Discussions Thus, this study revealed that better growth performance in Koi, A. testudineus (Bloch) could be achieved through utilization of poultry viscera in the formulated fish feed, compared to fishmeal. Hence, poultry waste recycling could be stimulated also.

Dynamic spectrum access has been promoted as a key technology in cognitive radio to achieve better spectrum utilization. It allows unauthorized secondary users to utilize the authorized primary user’s spectrum opportunistically, when primary user is absent. Therefore, it is an important task for secondary users to observe primary user activity in the channel. Implementation of such spectrum access scheme, cognitive radio requires a fast and reliable spectrum sensing technique to monitor primary user activity. Among all the available spectrum sensing schemes, Energy detection is most widely used because of its low complexity. However, the conventional energy detection method produces poor performance in a lower signal regime, resulting in longer sensing duration and low detection probability. To overcome these challenges, we have proposed an adaptive decision threshold approach instead of a fixed decision threshold in a modified Three Event Energy Detection framework. Additionally, a new objective function is formulated prioritizing the PU over SU using a weight factor along with spectrum utilization factor which achieves a better trade-off between the miss detection and false alarm probability. Simulation results illustrate that the proposed approach has improved efficacy in decision error probability and detection performance compared to the existing methods.

The detection of a brain tumor and its classification from modern imaging modalities is a primary concern, but a time-consuming and tedious work was performed by radiologists or clinical supervisors. The accuracy of detection and classification of tumor stages performed by radiologists is depended on their experience only, so the computer-aided technology is very important to aid with the diagnosis accuracy. In this study, to improve the performance of tumor detection, we investigated comparative approach of different segmentation techniques and selected the best one by comparing their segmentation score. Further, to improve the classification accuracy, the genetic algorithm is employed for the automatic classification of tumor stage. The decision of classification stage is supported by extracting relevant features and area calculation. The experimental results of proposed technique are evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on segmentation score, accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 92.03% accuracy, 91.42% specificity, 92.36% sensitivity, and an average segmentation score between 0.82 and 0.93 demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 93.79% dice similarity index coefficient, which indicates better overlap between the automated extracted tumor regions with manually extracted tumor region by radiologists.

In the present investigation, probiotic potential (antagonistic activity, enzyme production, hemolytic activity, biosafety, antibiotic sensitivity and bile tolerance level) of Bacillus subtilis LR1 was evaluated. Bacteriocin produced by the bacterial strain B. subtilis LR1 isolated from the gastrointestinal tract of Labeo rohita was purified and characterized. The molecular weight of the purified bacteriocin was ~50 kDa in 12 % Native PAGE and showed inhibitory activity against four fish pathogens such as Bacillus mycoides , Aeromonas salmonicida , Pseudomonas fluorescens and Aeromonas hydrophila . The purified bacteriocin was maximally active at temperature 40 °C and pH 7.0, while none of the tested surfactants affect the bacteriocin activity. Extracellular enzyme activity of the selected bacterial strain was also evaluated. Amylase activity was estimated to be highest (38.23 ± 1.15 µg of maltose liberated mg −1  protein ml −1 of culture filtrate) followed by cellulase and protease activity. The selected bacterium was sensitive to most of the antibiotics used in this experiment, can tolerate 0.25 % bile salt and non-hemolytic in nature. Finally, the efficiency of the proposed probiotic candidate was evaluated in in vivo condition. It was detected that the bacterial strain can effectively reduce bacterial pathogenicity in Indian major carps.