Explore the vast range of titles available.

The development of multimedia content has resulted in a massive increase in network traffic for video streaming. It demands such types of solutions that can be addressed to obtain the user's Quality-of-Experience (QoE). 360-degree videos have already taken up the user's behavior by storm. However, the users only focus on the part of 360-degree videos, known as a viewport. Despite the immense hype, 360-degree videos convey a loathsome side effect about viewport prediction, making viewers feel uncomfortable because user viewport needs to be pre-fetched in advance. Ideally, we can minimize the bandwidth consumption if we know what the user motion in advance. Looking into the problem definition, we propose an Encoder-Decoder based Long-Short Term Memory (LSTM) model to more accurately capture the non-linear relationship between past and future viewport positions. This model takes the transforming data instead of taking the direct input to predict the future user movement. Then, this prediction model is combined with a rate adaptation approach that assigns the bitrates to various tiles for 360-degree video frames under a given network capacity. Hence, our proposed work aims to facilitate improved system performance when QoE parameters are jointly optimized. Some experiments were carried out and compared with existing work to prove the performance of the proposed model. Last but not least, the experiments implementation of our proposed work provides high user's QoE than its competitors.

In this work, a new prototype of the eight-element MIMO antenna system for 5G communications, internet of things, and networks has been proposed. This system is based on an H-shaped monopole antenna system that offers 200 MHz bandwidth ranges between 3.4–3.6 GHz, and the isolation between any two elements is well below −12 dB without using any decoupling structure. The proposed system is designed on a commercially available 0.8 mm-thick FR4 substrate. One side of the chassis is used to place the radiating elements, while the copper from the other side is being removed to avoid short-circuiting with other components and devices. This also enables space for other systems, sub-systems, and components. A prototype is fabricated and excellent agreement is observed between the experimental and the computed results. It was found that ECC is 0.2 for any two radiating elements which is consistent with the desirable standards, and channel capacity is 38 bps/Hz which is 2.9 times higher than 4 × 4 MIMO configuration. In addition, single hand mode and dual hand mode analysis are conducted to understand the operation of the system under such operations and to identify losses and/or changes in the key performance parameters. Based on the results, the proposed antenna system will find its applications in modern 5G handheld devices and internet of things with healthcare and high rate delivery. Besides that, its design simplicity will make it applicable for mass production to be used in industrial demands.

This article presents compact and novel shape ring slotted antenna array operating at mmWave band on central frequency of 28 GHz. The proposed structure designed at 0.256 mm thin Roggers 5880 is composed of a ring shape patch with a square slot etched at the top mid-section of partial ground plane. Through optimizing the ring and square slot parameters high bandwidth of 8 GHz is achieved ranging from 26 to 32 GHz with simulated gain of 3.95 dBi and total efficiency of 96% for single element. The proposed structure is further transformed in a 4 element linear array manner. With compact dimensions of 20 mm × 22 mm for array, the proposed antenna delivers high simulated gain of 10.7 dBi and is designed in such a way that it exhibits dual beam response over the entire band of interest and simulated results well agree with fabricated prototype measurements.

This paper proposes an energy-efficient scheduling scheme for multi-path TCP (MPTCP) in heterogeneous wireless networks, aiming to minimize energy consumption while ensuring low latency and high throughput. Each MPTCP sub-flow is controlled by an agent that cooperates with other agents using the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm. This approach enables the agents to learn decentralized policies through centralized training and decentralized execution. The scheduling problem is modeled as a multi-agent decision-making task. The proposed energy-efficient scheduling scheme, referred to as EE-MADDPG, demonstrates significant energy savings while maintaining lower latency and higher throughput compared to other state-of-the-art scheduling techniques. By adopting a multi-agent deep reinforcement learning approach, the agents can learn efficient scheduling policies that optimize various performance metrics in heterogeneous wireless networks.

Rotor speed and twist per metres (tpm) are two key parameters in open-end rotor spinning of cotton yarns. High spinning productivity can be obtained by keeping the rotor speed high and twist level as low as possible. However, too high rotor speed may result in yarn imperfections and too low twist level may result in lower tenacity yarns. This study aimed at optimising the multiple yarn characteristics in open-end rotor spinning using the Taguchi method and the grey relational analysis. Cotton yarn samples of 30 tex were produced on rotor spinning machine with different twist levels (i.e. 500, 550, 600 and 700 tpm) at different rotor speeds (i.e. 70,000, 80,000, 90,000 and 100,000 rpm) according to the Taguchi design of experiment. Optimal spinning process parameters were determined using the grey relational grade as the performance index. It was concluded that for the cotton fibres and yarn count used in this study, optimum properties of the yarns could be obtained at 90,000 rpm rotor speed and 700 tpm.

In this study, a multiple response optimization model based on response surface methodology was developed to determine the best rotor speed and yarn twist level for optimum rotor yarn strength and unevenness, and minimum yarn hairiness and imperfections. Cotton yarn of 30 tex, was produced on rotor spinning machine with different twist levels (i.e. 500, 550, 600 and 700 tpm) at different rotor speeds (i.e. 70000, 80000, 90000 and 100000 rpm). Yarn quality characteristics were determined for all the experiments. Based on the results, multiple response optimization model was developed using response surface regression on MINITAB® 16 statistical tool. Optimization results indicate that with the quality of raw material selected for this study, top 50 % quality level, according to USTER® yarn quality benchmarks, can be achieved with 100 % desirability satisfaction for all the selected yarn quality parameters at rotor speed of 77,800 rpm and yarn twist of 700 twists per meter.