Heat transfer enhancement in hydromagnetic dissipative flow past a moving wedge suspended by H2O-aluminum alloy nanoparticles in the presence of thermal radiation

This letter investigates the two dimensional magnetohydrodynamic Falkner Skan flow of water saturated with AA7072–H₂O and AA7075–H₂O nanoparticles over a moving wedge. Influence of viscous dissipation and thermal radiation is also under consideration. The model is reduced into nondimensional form by using defined self-similar transformations. Then, numerical study (Runge-Kutta numerical scheme) is carried out for solution purpose. The effects of pertinent flow parameters are discussed in the flow regimes by means of graphical aid. Graphical results for special cases (static wedge and when the movement of flow and wedge is in opposite direction) of the model are also elucidated graphically. It is noted that fluid velocity decreases for volumetric fraction and magnetic force favor the velocity. Significant effects of thermal radiation and nanoparticles volume fraction pointed for thermal filed and the influence of Eckert number is almost inconsequential. For more radiative fluid heat transfer coefficient decreases and nanoparticles volumetric fraction favor the local rate of heat transfer. In the presence of AA7075 nanoparticles, rate of heat transfer is quite rapid as compared to that of AA7072 nanoparticles. To validate the present computations, some present results are compared with already existing results in the literature and found better agreement between them. Finally, major points of the study ingrained in the last section of the letter.     

Towards a Secure IPv6 Autoconfiguration

ABSTRACT

Stateless Address Autoconfiguration (SLAAC) is one of the novel features introduced in IPv6 Neighbor Discovery Protocol (NDP) providing for self-configuration of nodes and supplementing the reduction of operational and deployment cost of networks. Although self-configuration elevates the idea of autonomy for network, it has also introduced vulnerabilities that require substantial solutions. The SLAAC is pivoted on the presumption that network consists of authentic and entrusted nodes, however with inception of public sector wireless networks; any node can affix to the link with trivial authentication and situation changes radically. Although some security extensions like IPsec or SeND have been proposed, but these security protocols have been reported to have serious limitations like complex cryptographic algorithms which negate their adoption. This paper revisits the stateless auto configuration process and discusses its inherent vulnerabilities. The paper surveys existing research and available defense mechanisms available to protect SLAAC. The paper also suggests some guidelines from existing literature which can further promote and supplement the research to secure the auto configuration process. Finally, a novel technique is proposed for securing IPv6 link layer communication against DoS and Man-in-the-Middle attack which can be used as an alternate approach for CGA and SeND protocol.     

Prediction of postpartum depression using machine learning techniques from social media text

Early screening of mental disorders plays a crucial role in diagnosis and treatment. This study explores how data‐driven methods can leverage the information available on social media platforms to predict postpartum depression (PPD). A generalized approach is proposed where linguistic features are extracted from user‐generated textual posts on social media and categorized as general, depressive, and PPD representative using multiple machine learning techniques. We find that techniques used in our study exhibit strong predictive capabilities for PPD content. Holdout validation showed that multilayer perceptron outperformed other techniques such as support vector machine and logistic regression used in this study with 91.7% accuracy for depressive content identification and up to 86.9% accuracy for PPD content prediction. This work adopts a hierarchical approach to predict PPD. Therefore, the reported PPD accuracy represents the performance of the model to correctly classify PPD content from non‐PPD depressive content.     

Compact high isolation and improved bandwidth hybrid RF MEMS SPDT switch for 5G applications

Microsystem Technologies - Fifth generation (5G) communication system enables the pathway for a higher data transfer rate. The frequency bands used for 5G communication system are distributed from...     

Insight into kinetics and thermodynamics properties of multicomponent lead(II), cadmium(II) and manganese(II) adsorption onto Dijah-Monkin bentonite clay

Multicomponent adsorption of lead(II), cadmium(II) and manganese(II) by Nigerian Dijah-Monkin bentonite clay was investigated. The clay samples were characterized for elemental composition, cation exchange capacity and textural properties. Natural bentonite exhibits cation exchange capacity of 47.7?meq/100?g and specific surface area of 23.5?m²/g. Manganese(II) displays higher values of rate constant than lead(II) in multimetals adsorption. However, lead(II) is favorably adsorbed onto bentonite adsorbents at different concentrations studied. The multimetals adsorption onto bentonite clay samples is site selective and site specific. The pseudo-second-order kinetics model gave a better fit to the adsorption data, suggesting ion exchange and/or complex formation. The adsorption mechanism could be described by intraparticle diffusion with some restriction of metals diffusion due to film or boundary layer. Also, the multicomponent adsorption is endothermic and becomes more spontaneous as temperature increased from 303 to 338?K. Nigerian bentonite clay in its natural form is a promising adsorbent for multimetals removal in aqueous solution.     

Mapping past,current and future energy research trend in Pakistan: a scientometric assessment

This work describes the contribution of researchers in the field of the energy from Pakistan in the period 1990–2016. A scientometric approach was applied to analyze the scientific publications in the field using the Scopus Elsevier database. Different aspects of the publications were analyzed, such as publication type, major research areas, journals, citations, authorship pattern, affiliations as well as the keyword occurrence frequency. The present research trends are analyzed and future research directions are outlined. The impact factor, h-index and number of citations were used to investigate the strength of active institutes, authors, and journals in the field of the energy in Pakistan. From 1990 to 2016, 991 articles have been published by 2139 authors from 213 research institutes. The total number of citations and impact factor are 10,287 and 2301 respectively, corresponding to 10 citations per paper and an impact factor of 2.32 per publication. The research articles originate primarily from COMSATS, NUST, PIEAS, and PINSTECH. Pakistan has published 60% of publication with the collaboration of the foreign institutes, mainly from the United States, the United Kingdom, China and Malaysia. The core research activities in the field are mainly focused on resource assessment, energy policy, energy efficiency, feasibility study, energy economics, and performance assessment. The most productive journal, author, institution, are renewable & sustainable energy review, Shahbaz M., and COMSATS, respectively.     

Novel Analytical Thermal Performance Rate Analysis in ZnO-SAE50 Nanolubricant: Nonlinear Mathematical Model

The investigation of local thermal transport rate in the nanolubricants is significant. These lubricants are broadly used in environmental pollution, mechanical engineering and in the paint industry due to high thermal performance rate. Therefore, thermal transport in ZnO-SAE50 nanolubricant under the impacts of heat generation/absorption is conducted. The colloidal suspension is flowing between parallel stretching disks in which the lower disk is positioned at z = 0 and upper disk apart from distance d. The problem is transformed in dimensionless version via described similarity transforms. In the next stage, an analytical technique (VPM) is implemented for the solution purpose. The graphical results against multiple flow parameters were furnished over the region of interest and explained comprehensively. It is imperative to mention that the results are plotted for ZnO-SAE50 and conventional liquid as well. Further, rapid motion of the fluid is perceived against high Reynolds and γ parameters. The wall shear stresses at the upper end rises for multiple Reynolds and γ while; decrement is detected at the lower end. The significant contribution of an internal heat source is noted for thermal performance rate at the upper end. Foremost, the local heat transport rate declines at the lower disk. By altering Reynolds number, prompt heat transfer rate is gained at the upper disk and increasing behavior of the local heat transport rate is slow at the lower disk. From the study, it is concluded that the nanolubricants have high thermal characteristics. Therefore, such fluids are reliable to use in above stated areas.     

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic. Overcrowding in internet traffic may cause several problems; such as high packet hold-up, high packet dropping, and low packet output. In the course of data transmission for various applications in the Internet of things, such problems are usually generated relative to the input. To tackle such problems, this paper presents an analytical model using an optimized Random Early Detection (RED) algorithm-based approach for internet traffic management. The validity of the proposed model is checked through extensive simulation-based experiments. An analysis is observed for different functions on internet traffic. Four performance metrics are taken into consideration, namely, the possibility of packet loss, throughput, mean queue length and mean queue delay. Three sets of experiments are observed with varying simulation results. The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.     

Investigating the relevance of Environmental Kuznets curve hypothesis in Saudi Arabia: towards energy efficiency and minimal carbon dioxide emission

Clean Technologies and Environmental Policy - The Saudi economy is driven by the energy sector which mainly derived from petroleum-based resources. Besides export, the Kingdom’s consumption...