WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service (QoS). SDN having an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance. To implement WiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator. The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30% and enhances the throughput by 20%–50%, hence maintaining user fairness and accommodating more wireless devices and traffic load in the network, when compared to traditional client-driven (CD) approach and state of the art Wi-Balance approach.     

Classification of Electroencephalogram Signals Using LSTM and SVM Based on Fast Walsh-Hadamard Transform

Classification of electroencephalogram (EEG) signals for humans can be achieved via artificial intelligence (AI) techniques. Especially, the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic regions. From this perspective, an automated AI technique with a digital processing method can be used to improve these signals. This paper proposes two classifiers: long short-term memory (LSTM) and support vector machine (SVM) for the classification of seizure and non-seizure EEG signals. These classifiers are applied to a public dataset, namely the University of Bonn, which consists of 2 classes –seizure and non-seizure. In addition, a fast Walsh-Hadamard Transform (FWHT) technique is implemented to analyze the EEG signals within the recurrence space of the brain. Thus, Hadamard coefficients of the EEG signals are obtained via the FWHT. Moreover, the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG recordings. Also, a k-fold cross-validation technique is applied to validate the performance of the proposed classifiers. The LSTM classifier provides the best performance, with a testing accuracy of 99.00%. The training and testing loss rates for the LSTM are 0.0029 and 0.0602, respectively, while the weighted average precision, recall, and F1-score for the LSTM are 99.00%. The results of the SVM classifier in terms of accuracy, sensitivity, and specificity reached 91%, 93.52%, and 91.3%, respectively. The computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s, respectively. The results show that the LSTM classifier provides better performance than SVM in the classification of EEG signals. Eventually, the proposed classifiers provide high classification accuracy compared to previously published classifiers.     

Royal Crown Shaped Polarization Insensitive Perfect Metamaterial Absorber for C-, X-, and Ku-Band Applications

This study proposed a new royal crown-shaped polarisation insensitive double negative triple band microwave range electromagnetic metamaterial absorber (MA). The primary purpose of this study is to utilise the exotic characteristics of this perfect metamaterial absorber (PMA) for microwave wireless communications. The fundamental unit cell of the proposed MA consists of two pentagonal-shaped resonators and two inverse C-shaped metallic components surrounded by a split ring resonator (SRR). The bottom thin copper deposit and upper metallic resonator surface are disjoined by an FR-4 dielectric substrate with 1.6 mm thickness. The CST MW studio, a high-frequency electromagnetic simulator has been deployed for numerical simulation of the unit cell in the frequency range of 4 to 14 GHz. In the TE mode, the offered MA structure demonstrated three different absorption peaks at 6.85 GHz (C-band), 8.87 GHz (X-band), and 12.03 GHz (Ku-band), with 96.82%, 99.24%, and 99.43% absorptivity, respectively. The electric field, magnetic field, and surface current distribution were analysed using Maxwell’s-Curl equations, whereas the angle sensitivity was investigated to comprehend the absorption mechanism of the proposed absorber. The numerical results were verified using the Ansys HFSS (high-frequency structure simulator) and ADS (advanced design system) for equivalent circuit models. Moreover, the proposed MA is polarisation and incident angle independent. Hence, the application of this MA can be extended to a great extent, including airborne radar applications, defence, and stealth-coating technology.     

A color-based face tracking algorithm for enhancing interaction with mobile devices

A color-based face tracking algorithm is proposed to be used as a human-computer interaction tool on mobile devices. The solution provides a natural means of interaction enabling a motion parallax effect in applications. The algorithm considers the characteristics of mobile use-constrained computational resources and varying environmental conditions. The solution is based on color comparisons and works on images gathered from the front camera of a device. In addition to color comparisons, the coherency of the facial pixels is considered in the algorithm. Several applications are also demonstrated in this work, which use the face position to determine the viewpoint in a virtual scene, or for browsing large images. The accuracy of the system is tested under different environmental conditions such as lighting and background, and the performance of the system is measured in different types of mobile devices. According to these measurements the system allows for accurate (7% RMS error) face tracking in real time (20–100 fps).     

Bicriteria robotic operation allocation in a flexible manufacturing cell

Consider a manufacturing cell of two identical CNC machines and a material handling robot. Identical parts requesting the completion of a number of operations are to be produced in a cyclic scheduling environment through a flow shop type setting. The existing studies in the literature overlook the flexibility of the CNC machines by assuming that both the allocation of the operations to the machines as well as their respective processing times are fixed. Consequently, the provided results may be either suboptimal or valid under unnecessarily limiting assumptions for a flexible manufacturing cell. The allocations of the operations to the two machines and the processing time of an operation on a machine can be changed by altering the machining conditions of that machine such as the speed and the feed rate in a CNC turning machine. Such flexibilities constitute the point of origin of the current study. The allocation of the operations to the machines and the machining conditions of the machines affect the processing times which, in turn, affect the cycle time. On the other hand, the machining conditions also affect the manufacturing cost. This study is the first to consider a bicriteria model which determines the allocation of the operations to the machines, the processing times of the operations on the machines, and the robot move sequence that jointly minimize the cycle time and the total manufacturing cost. We provide algorithms for the two 1-unit cycles and test their efficiency in terms of the solution quality and the computation time by a wide range of experiments on varying design parameters.     

Authentication and authorization infrastructure for Grids—issues,technologies, trends and experiences

Authentication and authorization for Grids is a challenging security issue. In this paper, key issues for the establishment of Grid authentication and authorization infrastructures are discussed, and an overview of major Grid authentication and authorization technologies is presented. Related to this, recent developments in Grid authentication and authorization infrastructures suggest adoption of the Shibboleth technology which offers advantages in terms of usability, confidentiality, scalability and manageability. When combined with advanced authorization technologies, Shibboleth-based authentication and authorization infrastructures provide role-based, fine-grained authorization. We share our experience in constructing a Shibboleth-based authentication and authorization infrastructure and believe that such infrastructure provides a promising solution for the security of many application domains.     

Interactive smart battery storage for a PV and wind hybrid energy management control based on conservative power theory

This paper presents interactive smart battery-based storage (BBS) for wind generator (WG) and photovoltaic (PV) systems. The BBS is composed of an asymmetric cascaded H-bridge multilevel inverter (ACMI) with staircase modulation. The structure is parallel to the WG and PV systems, allowing the ACMI to have a reduction in power losses compared to the usual solution for storage connected at the DC-link of the converter for WG or PV systems. Moreover, the BBS is embedded with a decision algorithm running real-time energy costs, plus a battery state-of-charge manager and power quality capabilities, making the described system in this paper very interactive, smart and multifunctional. The paper describes how BBS interacts with the WG and PV and how its performance is improved. Experimental results are presented showing the efficacy of this BBS for renewable energy applications.     

Development of active matrix LCD for use in high‐resolution adaptive headlights

Conventional adaptive driving beam headlamps are limited in achieving still higher quantities of switchable pixels by the number of LEDs and movable elements needed. In this paper, it is shown that by integrating an active matrix liquid crystal display module, it is possible to realize fully adaptive high‐resolution headlights without mechanical elements and a finite number of LED with 30 k switchable pixels.