MHD flow of a micropolar fluid towards a vertical permeable plate with prescribed surface heat flux

The problem of a steady mixed convection stagnation point flow towards a permeable vertical plate with prescribed surface heat flux immersed in an incompressible micropolar fluid is studied numerically. The governing partial differential equations are first transformed into a system of ordinary differential equations using a similarity transformation, before being solved numerically by a finite-difference scheme known as the Keller-box method and the Runge–Kutta–Fehlberg method with shooting technique. The effects of the material parameter, buoyancy parameter, suction/injection parameter and the Prandtl number on the fluid flow and heat transfer characteristics are discussed. It is found that dual solutions exist for both assisting and opposing flows. The skin friction coefficient and the local Nusselt number increase in the presence of suction and magnetic field. Moreover, suction as well as fluids with larger Prandtl number widens the range of the buoyancy parameter for which the solution exists.     

Effect of processing routes on the mechanical, thermal and morphological properties of PLA-based hybrid biocomposite

Due to environmental awareness and depletion of petroleum oil, bioplastics and their composites are one of the most researchable topics throughout the world. Polymers that are produced from renewable sources are expected to be the best alternative to replace conventional polymers. The bottles neck of these bioplastics is its cost which limits its application in certain purposes. Bioplastics filled or reinforced with natural fibers can reduce cost and improve properties, like stiffness, strength and toughness of biocomposites. Impact strength and fracture toughness are the main demerits of short fiber-filled biocomposite. On the other hand, when nanoclay, having a very high aspect ratio, is mixed with bioplastics it may significantly affect the thermal and mechanical properties of the final composites. A composite may also suffer dispersion inefficiency, which is considered the key factor to improve the properties. The aim of this paper was to hybridize nanoclay and short kenaf fiber in polylactic acid (PLA) by double extrusion method and followed by mechanical, thermal and morphological characterizations. Mechanical properties showed improvement with nanoclay, specifically the impact strength increased more than 50 % compared with unreinforced PLA. A double extruded composite showed 3–10 % better tensile and flexural properties than the single extruded composite. Similarly, addition of nanoclay increased decomposition and melting temperatures (T _m) from 198 to 225 °C and 152 to 155 °C, respectively. Crystallization temperature (T _c), however, dropped with nanoclay from 116 to 106 °C and storage modulus (E’) increased by about 1 GPa. These findings were also supported by scanning electron micrograph (SEM) and transmission electron micrograph (TEM) where in double extruded composite a better dispersion of nanoclay was observed. By employing X-ray diffraction (XRD) it was found that higher percentage of crystallinity was obtained while Fourier transform infrared (FTIR) displayed new bond formation. The presence of nanoclay enhanced thermal and mechanical properties of the hybrid composite.     

Tensile and Impact Properties of Thermoplastic Natural Rubber Reinforced Short Glass Fiber and Empty Fruit Bunch Hybrid Composites

Thermoplastic natural rubber (TPNR) hybrid composite with short glass fiber (GF) and empty fruit bunch (EFB) fiber were prepared via the melt blending method using an internal mixer type Thermo Haake 600p. The TPNR were prepared from natural rubber (NR), liquid natural rubber (LNR) and polypropylene (PP) thermoplastic, with a ratio of 20:10:70. The hybrid composites were prepared at various ratios of GF/EFB with 20% volume fraction. Premixture was performed before the material was discharged into the machine. The study also focused on the effect of fiber (glass and EFB) treatment using silane and maleic anhydride grafted polypropylene (MAgPP) as a coupling agent. In general, composite that contains 10% EFB/10% glass fiber gave an optimum tensile and impact strength for treated and untreated hybrid composites. Tensile properties increase with addition of a coupling agent because of the existence of adherence as shown in the scanning electron microscopy (SEM) micrograph. Further addition of EFB exceeding 10% reduced the Young's modulus and impact strength. However, the hardness increases with the addition of EFB fiber for the untreated composite and decreases for the treated composite.     

Boundary-layer flow of nanofluids over a moving surface in a flowing fluid

The steady boundary-layer flow of a nanofluid past a moving semi-infinite flat plate in a uniform free stream is investigated. The plate is assumed to move in the same or opposite directions to the free stream. The resulting system of nonlinear ordinary differential equations is solved numerically using the Keller-box method. Numerical results are obtained for the skin-friction coefficient, the local Nusselt number and the local Sherwood number as well as the velocity, temperature and the nanoparticle volume fraction profiles for some values of the governing parameters, namely, the plate velocity parameter, Prandtl number, Lewis number, the Brownian motion parameter and the thermophoresis parameter. The results indicate that dual solutions exist when the plate and the free stream move in the opposite directions.     

Electrodeposition of tin selenide thin film semiconductor: effect of the electrolytes concentration on the film properties

Tin selenide semiconductor films have been potentiostatically deposited onto a tin substrate from an aqueous solution containing SnCl₂ and Na₂SeO₃. Deposition at various concentrations was attempted in order to investigate the effect of the electrolytes concentration on the film properties and to determine the optimum bath composition. The structure, morphology and photoactivity of the films were studied using X-ray diffraction, scanning electron microscopy and linear sweep photovoltammetry techniques. The semiconducting property of the deposit is strongly affected by the electrolytes concentration. The optimum bath composition was found to be 0.010 M for SnCl₂ and 0.015 M for Na₂SeO₃.     

ANFIS based quadrotor drone altitude control implementation on Raspberry Pi platform

The unmanned aerial vehicles can have complicated dynamics and kinematics that governs the flight of such multirotor devices. PID type controllers are one of the most popular approaches with Raspberry Pi 3 platform for stability of the flight. However, in dynamic environment they are limited in performance and response times. The autonomous tuning of the controller parameters according to the state of the environment with assistance of the adaptive neuro-fuzzy inference system is a well known approach. This paper provides implementation details and feasibility of such a controller with Raspberry Pi 3 platform for use in geological wireless sensing environments. The proposed neuro-fuzzy controller is developed for a Raspberry Pi 3 platform and tested on a physical quadrotor drone and compared to the conventional PID controller during flight.     

Input Displacement Neuro-fuzzy Control and Object Recognition by Compliant Multi-fingered Passively Adaptive Robotic Gripper

The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult make decision strategies using conventional techniques. Here, an adaptive neuro fuzzy inference system (ANFIS) for controlling input displacement and object recognition of a new adaptive compliant gripper is presented. The grasping function of the proposed adaptive multi-fingered gripper relies on the physical contact of the finger with an object. This design of the each finger has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize particular shapes of the grasping objects. Fuzzy based controllers develop a control signal according to grasping object shape which yields on the firing of the rule base. The selection of the proper rule base depending on the situation can be achieved by using an ANFIS strategy, which becomes an integrated method of approach for the control purposes. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. The simulation results presented in this paper show the effectiveness of the developed method.     

Botnet detection techniques: review,future trends,and issues

In recent years, the Interact has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a number of security issues. For instance, the botnet phenomenon is a prominent threat to Intemet security, including the threat of malicious codes. The botnet phenomenon supports a wide range of criminal activities, including distributed denial of service （DDoS） attacks, click fraud, phishing, malware distribution, spam emails, and building machines for illegitimate exchange of information/materials. Therefore, it is imperative to design and develop a robust mechanism for improving the botnet detection, analysis, and removal process. Currently, botnet detection techniques have been reviewed in different ways; however, such studies are limited in scope and lack discussions on the latest botnet detection techniques. This paper presents a comprehensive review of the latest state-of-the-art techniques for botnet detection and figures out the trends of previous and current research. It provides a thematic taxonomy for the classification of botnet detection techniques and highlights the implications and critical aspects by qualitatively analyzing such techniques. Related to our comprehensive review, we highlight future directions for improving the schemes that broadly span the entire botnet detection research field and identify the persistent and prominent research challenges that remain open.     

An appraisal and design of a multi-agent system based cooperative wireless intrusion detection computational intelligence technique

The deployment of wireless sensor networks and mobile ad-hoc networks in applications such as emergency services, warfare and health monitoring poses the threat of various cyber hazards, intrusions and attacks as a consequence of these networks’ openness. Among the most significant research difficulties in such networks safety is intrusion detection, whose target is to distinguish between misuse and abnormal behavior so as to ensure secure, reliable network operations and services. Intrusion detection is best delivered by multi-agent system technologies and advanced computing techniques. To date, diverse soft computing and machine learning techniques in terms of computational intelligence have been utilized to create Intrusion Detection and Prevention Systems (IDPS), yet the literature does not report any state-of-the-art reviews investigating the performance and consequences of such techniques solving wireless environment intrusion recognition issues as they gain entry into cloud computing. The principal contribution of this paper is a review and categorization of existing IDPS schemes in terms of traditional artificial computational intelligence with a multi-agent support. The significance of the techniques and methodologies and their performance and limitations are additionally analyzed in this study, and the limitations are addressed as challenges to obtain a set of requirements for IDPS in establishing a collaborative-based wireless IDPS (Co-WIDPS) architectural design. It amalgamates a fuzzy reinforcement learning knowledge management by creating a far superior technological platform that is far more accurate in detecting attacks. In conclusion, we elaborate on several key future research topics with the potential to accelerate the progress and deployment of computational intelligence based Co-WIDPSs.     

Electronic properties of carbon nanotubes calculated from density functional theory and the empirical <Emphasis Type="Italic">π</Emphasis>-bond model

The validity of the DFT models implemented by FIREBALL for CNT electronic device modeling is assessed. The effective masses, band gaps, and transmission coefficients of semi-conducting, zigzag, (n,0) carbon nanotubes (CNTs) resulting from the ab-initio tight-binding density functional theory (DFT) code FIREBALL and the empirical, nearest-neighbor π-bond model are compared for all semiconducting n values 5≤n≤35. The DFT values for the effective masses differ from the π-bond values by ±9% over the range of n values, 17≤n≤29, most important for electronic device applications. Over the range 13≤n≤35, the DFT bandgaps are less than the empirical bandgaps by 20–180 meV depending on the functional and the n value. The π-bond model gives results that differ significantly from the DFT results when the CNT diameter goes below 1 nm due to the large curvature of the CNT. The π-bond model quickly becomes inaccurate away from the bandedges for a (10,0) CNT, and it is completely inaccurate for n≤8.