An optimized hybrid deep learning model using ensemble learning approach for human walking activities recognition

The Journal of Supercomputing - Recent advancements in edge computing devices motivate us to develop a sustainable and reliable technique for multiple gait activities recognition using wearable...     

Space Time Regularized Zero Forcing in Downlink Code Division Multiple Access Systems with Complementary Codes

Wireless Personal Communications - Complementary coded code-division multiple access (CC-CDMA) has been originated as one of the extremely robust multiuser access technique in designing high data...     

Microstructure,Thermal, Thermo-mechanical and Fracture Analyses of Hybrid AA2024-SiC Alloy Composites

This research work aims to investigate the inter-correlation between microstructure, thermal (thermal conductivity, thermo-gravimetric analysis), thermo-mechanical (dynamic mechanical analysis) and fracture characteristics of hybrid AA2024-SiC alloy composites fabricated via semi-automatic stir-casting process, as per standard industrial practice. Silicon Carbide (SiC) particulates of varying amount (0–6 wt%; @ step of 2%) were used to reinforce master batch of AA2024 wrought alloy, Silicon Nitride (Si3N4) and graphite particulates. The thermal conductivity and storage-modulus magnitudes of alloy composites have shown diminishing trend with hard SiC reinforcing phase, while material stability, viscous modulus, damping factor and fracture toughness have shown significant improvement. Uniform dispersion and better interfacial adhesion between matrix–reinforcement were observed from metallographic examination. The XRD analysis identified the different phases of the hybrid alloy composites. The trends in variations of physical, mechanical and tribological properties were supported by microstructure analysis, thermal analysis, thermo-mechanical analysis and fracture analysis.     

Humidity Sustained Wearable Pouch‐Type Triboelectric Nanogenerator for Harvesting Mechanical Energy from Human Activities

Triboelectric nanogenerators (TENGs) are gaining much research interest recently owing to their facile and cost‐effective device structure. However, the effect of relative humidity (in moisture atmosphere) on the output performance still needs to be resolved. Herein, a pouch‐type TENG is proposed to significantly reduce the effect of relative humidity on its electrical output and a stable performance is also attained in a humid environment. In this regard, a dielectric and dielectric materials‐based TENG (DD‐TENG) is first developed using nanoarchitecture polydimethylsiloxane (NA‐PDMS) and multiwalled carbon nanotube/nylon composite layers as a triboelectric material with the negative and positive tendencies, respectively. The NA‐PDMS and nylon composite layers play a key role in increasing the surface contact area and surface charge density between the dielectric/triboelectric materials as well as the output performance of DD‐TENG. However, the DD‐TENG device exhibits a stable and high output performance with the effective output power density of ≈25.35 W m^?2. Additionally, the performance of the pouch‐type DD‐TENG device is not almost affected even though the relative humidity is increased from 35 to 81%, while it is dramatically decreased for the nonpouch‐type device. Finally, the pouch‐type DD‐TENG is employed as a wearable device to effectively harvest the mechanical energy from daily human activities.     

Linearly tapered meander line cross dipole circularly polarized antenna for UHF RFID tag applications

In this article, a circularly polarized antenna for ultra‐high frequency radio frequency identification (RFID) tag is presented. The circular polarization is realized by two orthogonal, unequal length linearly tapered meander line cross dipoles. The meander structure with capacitive tip loading is used for size miniaturization of the antenna. A modified T‐match network is employed to feed the cross dipole structure. The measured 10‐dB return loss bandwidth of the cross dipole antenna is 17 MHz (908‐923 MHz) and the corresponding 3‐dB axial ratio bandwidth is 6 MHz (912‐918 MHz). The overall size of the proposed antenna is 0.17λ₀ × 0.17λ₀ at 915 MHz. The maximum read range between the reader and the tag with the proposed antenna is 4.7 m larger than the analogous linearly polarized tag antenna due to the reduction in polarization loss between the tag and reader antennas. Thus, a maximum read range of 15.66 m with the gain of 1.28 dBic is achieved at 915 MHz.     

A Modelling of Context-Aware Elderly Healthcare Eco-System-(CA-EHS) Using Signal Analysis and Machine Learning Approach

In cloud computing, more often times cloud assets are underutilized because of poor allocation of task in virtual machine (VM). There exist inconsistent factors affecting the scheduling tasks to VMs. In this paper, an effective scheduling with multi-objective VM selection in cloud data centers is proposed. The proposed multi-objective VM selection and optimized scheduling is described as follows. Initially the input tasks are gathered in a task queue and tasks computational time and trust parameters are measured in the task manager. Then the tasks are prioritized based on the computed measures. Finally, the tasks are scheduled to the VMs in host manager. Here, multi-objectives are considered for VM selection. The objectives such as power usage, load volume, and resource wastage are evaluated for the VMs and the entropy is calculated for the measured objectives and based on the entropy value krill herd optimization algorithm prioritized tasks are scheduled to the VMs. The experimental results prove that the proposed entropy based krill herd optimization scheduling outperforms the existing general krill herd optimization, cuckoo search optimization, cloud list scheduling, minimum completion cloud, cloud task partitioning scheduling and round robin techniques.

     

BDN-GWMNN: Internet of Things (IoT) Enabled Secure Smart City Applications

Nowadays, next-generation networks such as the Internet of Things (IoT) and 6G are played a vital role in providing an intelligent environment. The development of technologies helps to create smart city applications like the healthcare system, smart industry, and smart water plan, etc. Any user accesses the developed applications; at the time, security, privacy, and confidentiality arechallenging to manage. So, this paper introduces the blockchain-defined networks with a grey wolf optimized modular neural network approach for managing the smart environment security. During this process, construction, translation, and application layers are created, in which user authenticated based blocks are designed to handle the security and privacy property. Then the optimized neural network is applied to maintain the latency and computational resource utilization in IoT enabled smart applications. Then the efficiency of the system is evaluated using simulation results, in which system ensures low latency, high security (99.12%) compared to the multi-layer perceptron, and deep learning networks.

     

Noise Reduction in VCSEL Based Wavelength Division Multiplexing System

Wavelength division multiplexing (WDM) technique plays a vital role in optical fiber communication. In this paper, a 4?×?1 WDM system has been developed with Vertical Cavity Surface Emitting LASER as optical source for each input. The performance analysis has been carried for Non Return to Zero (NRZ), hyperbolic secant, Gaussian and impulse generators over complex WDM optical fiber up to 50 km with less attenuation of 0.2 dB/Km. The Signal to noise ratio of received signal through Avalanche Photo diode in the receiver is calculated. This work identifies the best pulse generator with reduced noise performance suitable for the proposed system. The proposed system is modeled in optisys13 and insightful discussions are provided from the simulated results.

     

Lower Complex Resource Allocation Methodology based on Graph Theory and Index Matrix Rearrangement for OFDMA/MIMO-OFDMA Systems

Wireless Personal Communications - Resource allocation assigns subcarriers and power at the Base Station (BS) to different users, and is an important aspect in multiuser OFDMA downlink (DL)...     

Method for Processing Metal-Reinforced Ceramic Composites

A new process is developed to form a ceramic containing a three-dimensional network of metal reinforcement. The process involves four steps: (1) forming a powder compact containing a continuous network of either organic or carbon material by pressure filtration, (2) pyrolyzing the network to form channels within the powder compact, (3) densifying the powder while retaining the channel network, and (4) intruding metal into the channel network by squeeze casting. Pressure filtration is used to form the powder compact containing the pyrolyzable network either by mixing slurries of powder with chopped fiber or by packing powder within pyrolyzable preforms. When pressure is removed after filtration, the differential strain recovery of the powder matrix relative to the organic material can cause damage. Such damage is prevalent for a powder matrix formed from flocced slurries. However, this problem is avoided by using dispersed slurries which produce consolidated bodies that alleviate stresses arising from differential strain recovery by viscous flow. Metal-reinforced ceramic composites with different reinforcement architectures, volume fractions, and sizes can be produced with this technique.