Improved aquila optimization-based parameter evaluation framework and meta-heuristic algorithm in radio-over-fiber SpatialMux multi-input multi-output long-term evolution system

In heterogeneous access network, Multiple-Input Multiple-Output (MIMO) radio-over-fiber (RoF) system is an efficient approach for multiple signal transmission with low cost and complexity. The performance of RoF fronthaul system in MIMO system will be varied with different nonlinear effects. By adjusting various transmission parameters, such as the input signal power or the laser bias current, the nonlinear impacts produced by the RoF system can be reduced. In this paper, a novel algorithm Improved Aquila Optimization (IAO) is proposed to optimize transmission circumstances of MIMO RoF system. It determines the appropriate bias current for both lasers and Radio Frequency (RF) signal power in a short period. The input signals are wavelength multiplexed with Intensity Modulation and Direct Detection (IM/DD) applied. The carrier as well as transmission frequency is governed by the MIMO-Long-Term Evolution (LTE) standard. The proposed system is implemented in MATLAB, and the performance is evaluated. The experimental results show that fast convergence and trade-off between noise and nonlinearity are obtained with varying bandwidth. In the experimental scenario, the maximum Error Vector Magnitude (EVM) of 1.88, 3.14, and signal-to-noise ratio (SNR) of 3.204, and 2.698 was attained for both quadrature phase shift keying (QPSK) and quadrature amplitude modulation (QAM) modulation. [Correction added on 24 April 2023, after first online publication: the SNR values were corrected in the preceding sentence.] For 100 iterations, the processing time was reduced to 0.137 s. When compared with the conventional state-of-the-art approaches, the accuracy and computational complexity of the proposed approach are improved.     

Fuzzy Fruit Fly Optimized Node Quality-Based Clustering Algorithm for Network Load Balancing

Recently, the fundamental problem with Hybrid Mobile Ad-hoc Networks (H-MANETs) is to find a suitable and secure way of balancing the load through Internet gateways. Moreover, the selection of the gateway and overload of the network results in packet loss and Delay (DL). For optimal performance, it is important to load balance between different gateways. As a result, a stable load balancing procedure is implemented, which selects gateways based on Fuzzy Logic (FL) and increases the efficiency of the network. In this case, since gateways are selected based on the number of nodes, the Energy Consumption (EC) was high. This paper presents a novel Node Quality-based Clustering Algorithm (NQCA) based on Fuzzy-Genetic for Cluster Head and Gateway Selection (FGCHGS). This algorithm combines NQCA with the Improved Weighted Clustering Algorithm (IWCA). The NQCA algorithm divides the network into clusters based upon node priority, transmission range, and neighbour fidelity. In addition, the simulation results tend to evaluate the performance effectiveness of the FFFCHGS algorithm in terms of EC, packet loss rate (PLR), etc.     

Energy and Trust Management Framework for MANET using Clustering Algorithm

In General, Mobile Ad-Hoc Network (MANET) has limited energy resources, and it cannot recharge itself. This research goal focuses on building a power management scheme that saves energy in the MANET. Due to power instability, there is a chance that cluster heads fail and function incorrectly in cluster-based routing. As a result, instability occurs with the cluster heads while collecting data and communicating with others effectively. This work focuses on detecting the unstable cluster heads, which are replaced by other nodes implementing the envisaged self-configurable cluster mechanism. A self-configurable cluster mechanism with a k-means protocol approach is proposed to designate cluster heads effectively. The proposed k-means procedure is based on periodic irregular cluster head rotations or altering the number of clusters. We also propose a trust management mechanism in this research to detect and avoid MANET vulnerabilities. Because of the continuously changing topology and limited resources (power, bandwidth, computing), the trust management algorithm should only use local data. Consequently, compared to traditional protocols, the proposed approach with the k-means procedure and its experimental results show lower power usage and provide an optimal system for trust management.

     

An Improved Multifactor User Authentication Scheme for Wireless Sensor Networks

Wireless Personal Communications - Wireless Sensor Networks (WSNs) are used to collect and transmitted the data in various applications from normal to those which requires significant security...     

Effect of process parameters and optimization for photochemical machining of brass and german silver

This article focuses on parametric optimization for photochemical machining (PCM) of brass and german silver. The aim of the study is to analyze the effect of control parameters on response measures, that is, surface roughness, material removal rate, and edge deviation and optimization of parameters considering different weight percentage for each performance measure. The control parameters have been selected as etchant concentration, etching temperature, and etching time. Using full factorial method of design of experiments, PCM has been carried out using ferric chloride as etchant. Surface roughness and edge deviation should be less, while material removal rate is desired high. For satisfying this multi-objective condition, overall evaluation criteria (OEC) have been formulated by assigning different and equal weight percentage to response measures. The optimized condition for particular OEC is obtained, and analysis of variance (ANOVA) has been performed for observing effect of control parameters on response measures. Surface topography study has been performed using scanning electron microscopy, and material composition analysis has been carried out using energy dispersive spectroscopy. The surface roughness is observed lower for brass, while the edge deviation is found lesser for german silver. The material removal rate is observed higher for brass compared to german silver.     

Experimental investigation of impact of diesel particulate filter on smoke and NO<Subscript>x</Subscript> emissions of a Euro-I compression ignition engine with active and off-board regeneration

Old engines (Euro III or earlier) produce more emissions, and it will be difficult to entirely stop their usage especially in developing and under-developed nations; hence, it is desired that appropriate emission reduction technologies are tested on such engines to analyze their feasibility and economical acceptability. While most such studies have been conducted on constant speed stationary engines and modern engines, this study tried to analyze the effectiveness of an uncoated wall-flow type ceramic diesel particulate filter on a Euro-I, water-cooled, direct injection, variable speed, compression ignition engine in a laboratory set-up in India. Also, this study focused on diesel particulate filter regeneration by two methods: active regeneration by diesel injection in the particulate filter using an electronic control unit and off-board regeneration by taking out and heating the diesel particulate filter in an electrical resistance furnace at 650 °C for 10 h. The results, in the form of smoke emission, NO_x emission and engine performance, obtained using both the regeneration methods were analyzed, and conclusions were drawn. It was found that using diesel particulate filter, particulate matter emissions (smoke) were almost entirely eliminated. It was also found that off-board regeneration had numerous advantages compared to active regeneration. Since a furnace would be needed for off-board regeneration, an exchange process for diesel particulate filter is suggested.     

FSE–Ag complex NS: preparation and evaluation of antibacterial activity

Silver (Ag) complexes of drugs and their nanosystems have great potential as antibacterials. Recently, an Ag complex of furosemide (Ag–FSE) has shown to be a promising antimicrobial. However, poor solubility of Ag–FSE could hamper its introduction into clinics. Therefore, the authors developed a nanosuspension of Ag–FSE (Ag–FSE_NS) for its solubility and antibacterial activity enhancement. The aim of this study was to introduce a novel nanoantibiotic with enhanced antibacterial efficacy. Ag–FSE_NS was prepared by precipitation–ultrasonication technique. Size, polydispersity index (PI) and zeta potential (ZP) of prepared Ag–FSE_NS were measured by dynamic light scattering, whereas surface morphology was determined using scanning electron microscopy (SEM). In vitro antibacterial activity was evaluated against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa using broth microdilution method. Size, PI and ZP of optimised Ag–FSE_NS1 were 191.2 ± 19.34 nm, 0.465 ± 0.059 and −55.7 ± 8.18 mV, respectively. SEM revealed that Ag–FSE_NS1 particles were rod or needle‐like with smooth surfaces. Saturation solubility of Ag–FSE in NS increased eight‐fold than pure Ag–FSE. Ag–FSE_NS1 exhibited two‐fold and eight‐fold enhancements in activity against E. coli and S. aureus, respectively. The results obtained showed that developed Ag–FSE_NS1 holds a promise as a topical antibacterial.Inspec keywords: nanomedicine, nanofabrication, light scattering, surface morphology, silver, particle size, solubility, suspensions, scanning electron microscopy, electrokinetic effects, drugs, biomedical materials, antibacterial activity, microorganisms, nanoparticles, drug delivery systems, transmission electron microscopyOther keywords: saturation solubility, topical antibacterial, size 171.86 nm to 210.54 nm, voltage ‐47.52 mV to ‐63.88 mV, Ag, broth microdilution method, Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus, SEM, scanning electron microscopy, surface morphology, dynamic light scattering, particle size, polydispersity index, precipitation–ultrasonication technique, nanoantibiotic, nanosuspension, furosemide, nanosystems, drugs, Ag–FSE_NS preparation, in vitro antibacterial activity, pure Ag–FSE, Ag–FSE_NS1 particles, optimised Ag–FSE_NS1, zeta potential, enhanced antibacterial efficacy, antibacterials     

Gaming Prediction Markets: Equilibrium Strategies with a Market Maker

We study the equilibrium behavior of informed traders interacting with market scoring rule (MSR) market makers. One attractive feature of MSR is that it is myopically incentive compatible: it is optimal for traders to report their true beliefs about the likelihood of an event outcome provided that they ignore the impact of their reports on the profit they might garner from future trades. In this paper, we analyze non-myopic strategies and examine what information structures lead to truthful betting by traders. Specifically, we analyze the behavior of risk-neutral traders with incomplete information playing in a dynamic game. We consider finite-stage and infinite-stage game models. For each model, we study the logarithmic market scoring rule (LMSR) with two different information structures: conditionally independent signals and (unconditionally) independent signals. In the finite-stage model, when signals of traders are independent conditional on the state of the world, truthful betting is a Perfect Bayesian Equilibrium (PBE). Moreover, it is the unique Weak Perfect Bayesian Equilibrium (WPBE) of the game. In contrast, when signals of traders are unconditionally independent, truthful betting is not a WPBE. In the infinite-stage model with unconditionally independent signals, there does not exist an equilibrium in which all information is revealed in a finite amount of time. We propose a simple discounted market scoring rule that reduces the opportunity for bluffing strategies. We show that in any WPBE for the infinite-stage market with discounting, the market price converges to the fully-revealing price, and the rate of convergence can be bounded in terms of the discounting parameter. When signals are conditionally independent, truthful betting is the unique WPBE for the infinite-stage market with and without discounting.     

Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning

Robotic Path planning is one of the most studied problems in the field of robotics. The problem has been solved using numerous statistical, soft computing and other approaches. In this paper we solve the problem of robotic path planning using a combination of A* algorithm and Fuzzy Inference. The A* algorithm does the higher level planning by working on a lower detail map. The algorithm finds the shortest path at the same time generating the result in a finite time. The A* algorithm is used on a probability based map. The lower level planning is done by the Fuzzy Inference System (FIS). The FIS works on the detailed graph where the occurrence of obstacles is precisely known. The FIS generates smoother paths catering to the non-holonomic constraints. The results of A* algorithm serve as a guide for FIS planner. The FIS system was initially generated using heuristic rules. Once this model was ready, the fuzzy parameters were optimized using a Genetic Algorithm. Three sample problems were created and the quality of solutions generated by FIS was used as the fitness function of the GA. The GA tried to optimize the distance from the closest obstacle, total path length and the sharpest turn at any time in the journey of the robot. The resulting FIS was easily able to plan the path of the robot. We tested the algorithm on various complex and simple paths. All paths generated were optimal in terms of path length and smoothness. The robot was easily able to escape a variety of obstacles and reach the goal in an optimal manner.     

Dynamic content-page identification for media-rich websites

Knowledge of the information goal of users is critical in website design, analyzing the efficacy of such designs, and in ensuring effective user-access to desired information. Determining the information goal is complex due to the subjective and latent nature of user information needs. This challenge is further exacerbated in media-rich websites since the semantics of media-based information is context-based and emergent. A critical step in determining information goals lies in the identification of content pages. These are the pages which contain the information the user seeks. We propose a method to automatically determine the content pages by taking into account the organization of the web site, the media-based information content, as well as the influence of a specific user browsing pattern. Given a specific browsing pattern, in our method, putative content pages are identified as the pages corresponding to the local minima of page-content entropy values. For an (unknown) user information goal this intuitively corresponds to modeling the progressive transition of the user from pages with generic information to those with specific information. Experimental investigations on media rich sites demonstrate the effectiveness of the technique and underline its potential in modeling user information needs and actions in a media-rich web.