Performance Comparison Between Different Tunneling Techniques Using Different Routing Protocols

Wireless Personal Communications - Migration to IPv6 becomes a priority with the draining of IPv4 addresses. But both IPv4 and IPv6 have different structures, and directly bringing IPv6 into the...     

Influence of the Nature of A Cation on Dynamics of Charge Transfer Processes in Perovskite Solar Cells

The electronic processes occurring within the perovskite solar cells (PSCs) are strongly influenced by the nature of the organic A cations present within the inorganic framework. In this study, the impact of FA (CH(NH₂)₂⁺) and Cs⁺ cations on the intrinsic and interfacial properties in the FAPbBr₃ and CsPbBr₃ PSCs is investigated. The analysis of current density ( J _SC) and photovoltage ( V _OC) as a function of illumination intensity establishes that the interfacial charge transport is more rapid in FAPbBr₃ devices. Small perturbation measurements including intensity modulated photocurrent and photovoltage spectroscopy are applied to explore the resistive and capacitive elements. Furthermore, electrochemical impedance spectroscopy measurements are found to correlate well with the photovoltaic characteristics of FAPbBr₃ and CsPbBr₃ PSCs. Overall, the in‐depth analysis of various phenomena occurring within the bromide PSCs allows to underline the working principle, which provides a key to optimize the device performance. The present protocol is not only valid for PSCs but can also be extended to devices based on alternative light harvesters.     

All Slot-Die Coated Non-Fullerene Organic Solar Cells with PCE 11%

Slot-die (SD) coating is used to fabricate fully solution processed organic solar cells (OSCs) based on a blend of high performance donor polymer (PTB7-Th) and a non-fullerene acceptor (IEICO-4F) for stable devices over extended periods of operation. The optimization of a sequential deposition process of transport and active layers, under ambient conditions, enable high efficiency slot-die coated solar cells with remarkable power conversion efficiencies (PCE) > 11.0% to bridge the gap between lab-to-fab. Fully slot-die coated inverted OSCs are demonstrated with efficiencies reaching 11% along with 1 cm² devices, proving the scalability and reproducibility of the proposed technique. Further, replacing the evaporated Ag electrode with solution processed Ag nanowire (AgNW) electrodes shows the highest light utilization efficiency of 5.26% for semi-transparent OSC with a PCE of 9.07% and average visible transmission of 58%.     

A proactive defense method for the stealthy EDoS attacks in a cloud environment

Cloud computing technology provides flexibility to Cloud Service Provider (CSP) for providing the cloud resources based on the users' requirements. In on‐demand pricing model, the attackers exploit this feature and cause unwanted scaling‐up of the cloud resources without any intent to pay for them. The associated cost for the unpaid malicious usage burdens the CSP, and over a long period, economic losses occur at the CSP end. Thus, the resources and services offered by the CSP become unsustainable, and the attack is termed as Economic Denial‐of‐Sustainability (EDoS) attack. The existing defense approaches for EDoS attacks are reactive. Thus, the associated attack detection/mitigation cost is high; consequently, the approaches are not suitable for the Small and Medium Enterprises (SMEs). The aim of this paper is to detect and mitigate, internal and external, stealthy EDoS attacks proactively. The attack is detected using average CPU utilization threshold and utility function (in terms of cost for the utilized cloud computing resources) and mitigated using virtual firewalls. Amazon Elastic Compute Cloud (Amazon EC2) is used to evaluate the performance of the proposed approach. The proposed approach accurately detects the EDoS attack and mitigates its effect as well with reduced cost. It is observed that the approach provides competitive response time, victim service downtime, and attack reporting time. Thus, the overall performance is improved.     

Deep neural network and 3D model for face recognition with multiple disturbing environments

This paper presents the proposed bird search-based shuffled shepherd optimization algorithm (BSSSO) for face recognition. Initially, the input image undergoes a noise removal phase to eliminate noise in order to make them suitable for subsequent processing. The noise removal is performed using the type II fuzzy system and cuckoo search optimization algorithm (T2FCS), which detects noisy pixels from the image for improved processing. After the noise removal phase, the feature extraction is carried out using the convolution neural network (CNN) model and landmark enabled 3D morphable model (L3DMM). The obtained features are subjected to deep CNN for face recognition. The training of deep CNN is performed using the bird search-based shuffled shepherd optimization algorithm (BSSSO). Here, the proposed BSSSO is designed by combining the shuffled shepherd optimization algorithm (SSOA) and bird swarm algorithm (BSA) for inheriting the merits of both optimizations towards effective training of deep CNN. The proposed method obtained higher accuracy of 0.8935 and minimum FAR and FRR of 0.2190 and 0.2021 using LFW database with respect to training data.

     

Detection of Low-Rate Cloud DDoS Attacks in Frequency Domain Using Fast Hartley Transform

Distributed Denial-of-Service (DDoS) attack has been a serious threat to the availability feature of cloud computing. As traditional DDoS attacks are implemented using a huge volume of malicious traffic, the detection of such attacks becomes a naive task. To evade this detection, attackers are moving towards the Low-Rate DDoS (LRDDoS) attacks. The stealthy behavior of LRDDoS attack makes it difficult to get detected due to its low volume traffic. The existing frequency-domain approaches for LRDDoS detection are not feasible in terms of computational and storage requirements. This paper aims to propose a lightweight, accurate, and adaptive approach for the detection of LRDDoS attacks in frequency-domain. In this paper, the LRDDoS attack is detected by analyzing the power spectral distribution. The novelty of the proposed approach is to calculate the power spectral density using Fast Hartley Transform (FHT). The FHT processes real-valued input data, and has low computational and storage complexities. The approach is implemented on OpenStack cloud platform, and the aggregate network traffic (external and internal) is captured and analyzed. Experimental results show that the computational and storage complexities involved in FHT are lower than other transformation algorithms’ complexities. Thus, the approach provides faster response with an average detection time of 60.16 s. The average true negative and true positive rates obtained by the proposed approach are 99.83% and 99.46% respectively, which are competitive.

     

Effect of structured parameters on the hot-carrier immunity of transparent gate recessed channel (TGRC) MOSFET

In this work, the impact of parameter variation on hot-carrier effect immunity in transparent gate recessed channel (TGRC)—MOSFET based on the hydrodynamic energy transport model have been studied. The parameters of TGRC-MOSFET investigated include the oxide thickness, negative junction depth, and substrate doping. TCAD analysis shows the performance of TGRC-MOSFET in terms of transfer characteristics, transconductance, electric field, electron velocity, electron mobility and electron temperature. The simulation results indicate the improved hot-carrier immunity for TGRC-MOSFET in 30 nm device.

     

Study of thermally coupled distillation systems for energy-efficient distillation

Distillation is one of the most widely used separation unit operations in process industries, although it is quite energy intensive. In many cases, the enormous energy requirements for distillation make it economically infeasible to carry out the separation. Thermally coupled distillation system (TCDS) is an advanced distillation method that provides significant energy savings of about 30% as compared with conventional distillation column sequences. The most well-known TCDS sequence, the Petlyuk configuration, has some operational challenges due to bidirectional vapour flow, which makes its implementation difficult in two-column mode. To overcome these limitations, a number of unidirectional vapour flow configurations have been proposed in the literature. The work on simulation analysis for such configurations is limited. In this paper, simulation models for two such configurations are developed, analyzed and compared with the Petlyuk and conventional distillation column sequences for separation of equimolar mixture of benzene–toluene–ethylbenzene.     

Pattern identification of different human joints for different human walking styles using inertial measurement unit (IMU) sensor

Artificial Intelligence Review - A bipedal walking robot is a kind of humanoid robot. It is suppose to mimics human behavior and designed to perform human specific tasks. Currently, humanoid robots...