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In this correspondence a small low profile multiband multi-slot MIMO antenna is proposed. The proposed patch antenna covers five bands. Band I covers 2.71–2.82 GHz, band II covers 3.73–4.64 GHz, band III covers 5.14–6.72 GHz, band IV covers 7.52–8.53 GHz and band V covers 8.66–9.41 GHz. It combines many applications into a single device by designing a single antenna that can be operated in multi-bands. The proposed antenna consists of multi-slot radiator with defected ground plane. Proposed antenna is smaller in size 15 × 20 mm2 (0.14λ0 × 0.18 λ0). It is extended to MIMO and mutual coupling is reduced in three bands (III, IV and V) using Defected Ground Structure (DGS). Mutual coupling in the first band (I, II) is minimized using a decoupling element. The proposed MIMO antenna is fabricated and tested. Simulation and measured results are found to be in good agreement.

An antenna which is used for multipurpose like WiMAX, RADAR altimeter and X-band applications proposed. A tri-band multiple-input–multiple-output antenna resonates at 2.9 GHz, 4.3 GHz and 7.7 GHz is proposed. The uniqueness of the antenna is mutual coupling, − 53.44 dB at 2.9 GHz, − 28 dB at 4.3 GHz and − 26.55 dB at 7.7 GHz. It is evaluated in terms of mutual coupling in two ways (1) DGS (2) DGS with Vias. It is observed that mutual coupling using DGS with Vias is reduced further by 12 dB. The ECC of antenna is less than 0.0001 The simulated and measured results are compared in terms of S-parameters, Co-pol, X-pol and ECC.

Many attempts to predict sports using historical data have been made, but people continue to outperform computers in predicting sports outcomes. There are various trading firms that specialize in sports research and forecasting. They track their data with sophisticated software and statistics algorithms, but they still have experts reviewing games by hand in some cases. In this paper, we recommend that the package have a transition time for live cricket and football scores. For cricbuzz school cricket and ESPN football games, we use the API. The programme displays live scores for all games, including T20, test matches, IPL, one-day international tournaments, and all football matches. The software is written in python.

In the present scenario, the requirement for energy has been increasing in a distressing rate and the availability of the energy resources are not abundant for sustainable development and the need of the hour is to establish an economical pollution free inexhaustible energy resources to compensate the increasing demands. Since, walking is the most common activity in human day to day life, whenever a person walks he exhausts energy to the ground which goes as a waste. In order to preserve and make use of this energy we are converting it into electrical energy using piezoelectric effect. Piezoelectric effect is utilized by piezoelectric sensor producing output energy in the form of AC voltage. To produce energy in a large extent, in this model implementation of the piezoelectric sensor network along the footpath is carried out which is given to the lane of streetlights along with it the smart shoe is implemented for a small production that consists GPS tracking. In this proposed work model, GPS tracking has been added and also streetlights switching technique comparing with existing model.

Three different antennas such as corner cut inset-fed dual-band slot, inset-fed dual-band slot and inset-fed microstrip antennas are presented. These antennas will find applications in Bluetooth/WLAN, Personal Communications service (PCS) and Global System for Mobile Communication (GSM). The antenna simulations are carried using HFSS. The inset-fed antenna is proposed to operate in frequency range of 2.35GHz to 2.42GHz, which finds application in WLAN. The proposed inset-fed dual-band slot antenna is considered among 1.6GHz to 1.64GHz and 2.38GHz to 2.43GHz. By modulating the proper position of slot, the corner cut inset-fed dual-band slot antenna is proposed to operate among the frequency range for lower band as 1.74GHz to 1.78GHz and 1.92GHz to 1.97GHz and for upper band as 2.38GHz to 2.43GHz. The experiment is also carried out for inset-fed microstrip antenna. A comparison among simulation and measured results are presented in this paper.

of wireless network is vital research area for the researchers and scientists. This work demonstrates a deep study of security levels in Wireless Local Area Networks (WLAN). This study includes different security schemes of WLAN like Security Aware Packet Scheduling Algorithm (SPSS), Automated Security-Aware Packet Scheduling (ASPS), Bio-cryptic Security-Aware Packet Scheduling (BSPS), Enhanced Bio-cryptic Security-Aware Packet Scheduling (EBSPS), Enhanced Merged Bio-cryptic Security- Aware Packet Scheduling (EMBSPS) and Multi Merged Bio- cryptic Security-Aware Packet Scheduling (MMBSPS). To analyze the performance of the each algorithm some simulations were conducted by considering different parameters like Security Level (SL), size of Wireless Data Packet (WDP), Speedy Authentication (SA) and Load- on- network Switch (LOS). The simulations were performed using Matlab and Network Simulator-2. Finally our experiment result concludes that, each algorithm has got its own advantages and limitations.

Security and quality of service are two major problems in wireless communications. This work concentrated on improving the security levels for Enhanced Bio-cryptic Security- Aware Packet Scheduling-Algorithm (EBSPS) and also the fast communication between Wireless Node (WN) and Advanced Radius authentication server (ARAS). This paper introduces a novel Enhanced Merged Bio-cryptic Security- Aware Packet Scheduling-Algorithm (EMBSPS). Simulations were conducted using the Matlab and EMBSPS is compared with the results of present EBSPS and BSPS. To accomplish better Quality-of-Service (QoS) in WLAN, it is substituted with the existing EBSPS with novel EMBSPS. This EMBSPS Algorithm assures the finest concert in improving the security levels and speeds up the authentication process. Lastly, simulation result proves that proposed model is performing finer than the present algorithm in terms of the quality of service. General Terms

Computational intelligence techniques are proved to be outperforming compared to standard statistical techniques, specifically when dealing with large, unbalanced and high dimensional data. In this paper we present an enhancement approach for improving the performance of decision tree using Support Vector Machine (SVM) when dealing with unbalanced data. The proposed approach modifies the available training data according to the predictions of SVM and this modified training data is then used to train decision tree. As the dataset at hand i.e. COIL data is highly unbalanced with 94:6 class distribution ratios, we also employed various standard sampling techniques for extensive analysis. Based on sensitivity measure, it is observed that the proposed approach enhanced the efficiency of decision tree exceptionally well. Other intelligent methods can be tested in place of DT.