Optimization of routing-based clustering approaches in wireless sensor network: Review and open research issues

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. In today’s sensor network research, numerous technologies are used for the enhancement of earlier studies that focused on cost-effectiveness in addition to time-saving and novel approaches. This survey presents complete details about those earlier models and their research gaps. In general, clustering is focused on managing the energy factors in wireless sensor networks (WSNs). In this study, we primarily concentrated on multihop routing in a clustering environment. Our study was classified according to cluster-related parameters and properties and is subdivided into three approach categories: (1) parameter-based, (2) optimization-based, and (3) methodology-based. In the entire category, several techniques were identified, and the concept, parameters, advantages, and disadvantages are elaborated. Based on this attempt, we provide useful information to the audience to be used while they investigate their research ideas and to develop a novel model in order to overcome the drawbacks that are present in the WSN-based clustering models

Modelling the impact of fiscal policy on non-oil GDP in a resource rich country: Evidence from Azerbaijan

This paper analyses the impact of public expenditures and tax revenues on non-oil economic growth in Azerbaijan for the period of 2000Q1-2015Q2 by employing OLS, ARDL, FMOLS, DOLS, CCR and Granger Causality techniques. Different cointegration methods result in consistent results. In this study, there is strong evidence of significant long-run positive contributions from public expenditures to non-oil sector output. Results also show that tax revenues significantly slow down non-oil economic growth in the long run. Granger Causality analysis finds the existence of a bidirectional short-run association between non-oil GDP and public expenditures, while tax revenues Granger Cause both variables. The research findings should be useful for Azerbaijan fiscal policy makers to consider now and in the future. Current plans in Azerbaijan for both public expenditure cuts and tax revenue increases are likely to cause contraction in the Azerbaijan's non-oil sector GDP

Influence of bio-deposited recycled aggregate on the concrete properties

Recycling construction wastes for their utilisation as aggregates will overcome the dumping and scarcity problems. However, their higher porosity affects the properties of concrete. Hence, this study examines the potential use of microbial-induced calcium carbonate precipitation techniques to improve the quality of recycled coarse aggregates (RCA). The natural coarse aggregate (NCA) was replaced with 50, 100% of RCA and bio-deposited recycled coarse aggregate (BRCA). The aggregate properties were tested and observed that the water absorption and crushing index of RCA were increased by 85.10% and 19.10%, whereas for BRCA, the water absorption and crushing index were increased by only 5.20% and 5.80%. The concrete mixture prepared with optimised and complete percentages of RCA and BRCA was tested for their fresh, hardened, and durable properties. It is observed that the strength of the RAC was 36% lesser than NAC, whereas the strength of the BRAC was 33.40% more compared to the RAC at 28 days. Also, the water absorption and sorptivity of BRAC were reduced by 33.68% and 15.50% and the resistance to carbonation and chloride ingression of BRAC was enhanced by 15.50% and 29.73% when compared to RAC. The microstructural investigations performed through SEM and XRD evident the CaCO3 precipitation that improves the quality of RCA.</p

Optimal virtual machine selection for anomaly detection using a swarm intelligence approach

© 2019 Elsevier B.V. Cloud computing plays a significant role in Healthcare Service (HCS) applications and rapidly improves it. A significant challenge is the selection of Virtual Machine (VM) in order to process a medical request. The optimal selection of VM increases the performance of HCS by minimizing the running time of the medical request and also substantially utilizes cloud resources. This paper presents a new idea for optimizing VM selection using a swarm intelligence approach called Analogous Particle swarm optimization (APSO) which works a cloud computing environment. To compute the running time of a medical request, three parameters are considered: Turnaround Time (TAT), Waiting time (WT), and CPU utilization. In addition, a selected optimal VM is used for predicting kidney disease. Early detection of kidney disease facilitates successful treatment. Here, the neural network is used as an automated technique to diagnose kidney disease. A set of experiments and comparisons were performed to analyze the proposed system (APSO and neural network). The results showed that the APSO model performed well, with an execution time of running all particle is 1 s (50 to 80%). Also, the proposed model improved the system efficiency by 5.6%. The precision of recognizing kidney disease using the neural network was 95.7% which outperfomed five other well-known classifiers

IADF-CPS: Intelligent Anomaly Detection Framework towards Cyber Physical Systems

Cyber–Physical Systems (CPSs) becoming one of the most complex, intelligent, and sophisticated system. Ensuring security is an important aspect towards CPSs. However, increase in sophisticated and complexity attacks in CPSs, the conventional anomaly detection methods are facing problems and also growth in volume of data becomes challenging which requires domain specific knowledge that could be applied directly to analyze these challenges. In order to overcome this problem, various deep learning based anomaly detection system is developed. In this research, we propose an anomaly detection approach by integration of intelligent deep learning technique named Convolutional Neural Network (CNN) with Kalman Filter (KF) based Gaussian-Mixture Model (GMM). The proposed model is used for identifying and detecting anomalous behavior in CPSs. This proposed framework consists of two important process. First is to pre-process the data by transforming and filtering original data into new format and achieved privacy preservation of the data. Secondly, we proposed GMM-KF integrated deep CNN model for anomaly detection and accurately estimated the posterior probabilities of anomalous and legitimate events in CPSs

Human exposure to mercury in artisanal small-scale gold mining areas of Kedougou region, Senegal, as a function of occupational activity and fish consumption

We investigated mercury (Hg) exposure of food web and humans in the region of Kedougou, Senegal, where Hg is used for gold amalgamation in artisanal small-scale gold mining (ASGM). For this purpose, total mercury (THg) concentration was determined in eight fish species and two shellfish species from Gambia River and in human hair from 111 volunteers of different age and sex, living in urban locations (Kedougou and Samekouta) or in ASGM areas (Tinkoto and Bantako). THg concentrations in fish samples range from 0.03 to 0.51mgkg−1 wet weight (ww) and 0.5 to 1.05mgkg−1 ww for shellfish. THg concentrations in fish are below the WHO guideline of 0.5mgkg−1 ww, whereas 100% of shellfish are above this safety guideline. In the entire set of fish and shellfish samples, we documented a decrease of THg concentrations with increasing selenium to mercury (Se:Hg) ratio suggesting a protection of Se against Hg. However, local population consuming fish from the Gambia River in the two ASGM areas have higher THg concentrations (median = 1.45 and 1.5mgkg−1 at Bantako and Tinkoto) in hair than those from others localities (median = 0.42 and 0.32mgkg−1 at Kedougou town and Samekouta) who have diverse diets. At ASGM sites, about 30% of the local population present Hg concentrations in hair exceeding 1mgkg−1, defined as the reference concentration of Hg in hair. We also evidence a higher exposure of women to Hg in the Tinkoto ASGM site due to the traditional distribution of daily tasks where women are more involved in the burning of amalgams. The discrepancy between the calculated moderate exposure through fish consumption and the high Hg concentrations measured in hair suggest that fish consumption is not the only source of Hg exposure and that further studies should focus on direct exposure to elemental Hg of population living at ASGM sites

Human exposure to mercury in artisanal small-scale gold mining areas of Kedougou region, Senegal, as a function of occupational activity and fish consumption

We investigated mercury (Hg) exposure of food web and humans in the region of Kedougou, Senegal, where Hg is used for gold amalgamation in artisanal small-scale gold mining (ASGM). For this purpose, total mercury (THg) concentration was determined in eight fish species and two shellfish species from Gambia River and in human hair from 111 volunteers of different age and sex, living in urban locations (Kedougou and Samekouta) or in ASGM areas (Tinkoto and Bantako). THg concentrations in fish samples range from 0.03 to 0.51 mg kg(-1) wet weight (ww) and 0.5 to 1.05 mg kg(-1) ww for shellfish. THg concentrations in fish are below the WHO guideline of 0.5 mg kg(-1) ww, whereas 100 % of shellfish are above this safety guideline. In the entire set of fish and shellfish samples, we documented a decrease of THg concentrations with increasing selenium to mercury (Se:Hg) ratio suggesting a protection of Se against Hg. However, local population consuming fish from the Gambia River in the two ASGM areas have higher THg concentrations (median = 1.45 and 1.5 mg kg(-1) at Bantako and Tinkoto) in hair than those from others localities (median = 0.42 and 0.32 mg kg(-1) at Kedougou town and Samekouta) who have diverse diets. At ASGM sites, about 30 % of the local population present Hg concentrations in hair exceeding 1 mg kg(-1), defined as the reference concentration of Hg in hair. We also evidence a higher exposure of women to Hg in the Tinkoto ASGM site due to the traditional distribution of daily tasks where women are more involved in the burning of amalgams. The discrepancy between the calculated moderate exposure through fish consumption and the high Hg concentrations measured in hair suggest that fish consumption is not the only source of Hg exposure and that further studies should focus on direct exposure to elemental Hg of population living at ASGM sites