This paper provides a self-healing strategy to deal with catastrophic events when power system vulnerability analysis indicates that the is approaching an extreme emergency state. In authors' approach, adaptively divided into smaller islands consideration of quick restoration. Then, load shedding scheme based on rate frequency decline applied. The proposed tested 179-bus, 20-generator sample and shows very good performance.

A novel non-orthogonal multiple access (NOMA) based cache-aided mobile edge computing (MEC) framework is proposed. For the purpose of efficiently allocating communication and computation resources to users' tasks requests, we propose a long-short-term memory (LSTM) network predict task popularity. Based on predicted popularity, long-term reward maximization problem formulated that involves joint optimization offloading decisions, resource allocation, caching decisions. To tackle this...

The success of a text simplification system heavily depends on the quality and quantity complex-simple sentence pairs in training corpus, which are extracted by aligning sentences between parallel articles. To evaluate improve alignment quality, we create two manually annotated sentence-aligned datasets from commonly used corpora, Newsela Wikipedia. We propose novel neural CRF model not only leverages sequential nature documents but also utilizes pair to capture semantic similarity....

A novel reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic optimization problem that involves joint of NOMA user partitioning and RIS phase shifting, aiming at maximizing the sum data rate mobile users (MUs) in networks. To solve challenging problem, we invoke modified object migration automation (MOMA) algorithm to partition into equal-size clusters. optimize shifting matrix,...

Driven by the unprecedented high throughput and low latency requirements anticipated for next generation wireless networks, this article introduces an artificial intelligence (AI)-enabled framework in which unmanned aerial vehicles use non-orthogonal multiple access mobile edge computing techniques to serve terrestrial users (MUs). The proposed enables MUs offload their computational tasks simultaneously, intelligently, flexibly, thus enhancing connectivity as well reducing transmission...

An optimization problem of content placement in cooperative caching is formulated, with the aim maximizing sum mean opinion score (MOS) mobile users. Firstly, as user mobility and popularity have significant impacts on experience, a recurrent neural network (RNN) invoked for prediction prediction. More particularly, practical data collected from GPS-tracker app smartphones tackled to test accuracy Then, based predicted users' positions popularity, learning automata Q-learning (LAQL)...

A novel resource allocation scheme for cache-aided mobile-edge computing (MEC) is proposed, to efficiently offer communication, storage and service intensive computation sensitive latency computational tasks. In this paper, the considered problem formulated as a mixed integer non-linear program (MINLP) that involves joint optimization of tasks offloading decision, cache allocation, dynamic power distribution. To tackle non-trivial problem, Markov decision process (MDP) invoked mobile users...

Caching popular contents at the network edge has been considered as a promising enabler to relieve pressure on networks due fact that substantial portion of global data traffic is repeatedly requested by many subscribers and thus redundantly generated. Recommendation, other hand, attracted spiraling attention for its capability reshaping users' demand patterns. In this paper, we examine practicability recommendation in boosting gains caching with uncharted feature information. To end, first...

Non-orthogonal multiple access-enabled fog radio access networks (NOMA-F-RANs) are thought of as a promising enabler to release network congestion, reduce delivery latency, and improve user equipment (F-UEs) quality service. Never-theless, the effectiveness NOMA-F-RANs highly relies on charted feature information (e.g., preference distribution, positions, mobilities) F-UEs well effective caching, computing, resource allocation strategies. In this article, we explore how artificial...

A novel reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic optimization problem that involves the of phase shifting, aiming at maximizing sum data rate mobile users (MUs) in NOMA networks. For intelligently adjusting shifting matrix point (AP), we propose deep deterministic policy gradient (DDPG) algorithm to collaboratively control reflecting elements (REs) RIS. Extensive...

A novel Twitter context aided content caching (TAC) framework is proposed for enhancing the efficiency by taking advantage of legibility and massive volume data. For purpose promoting efficiency, three machine learning models are to predict latent events popularity, utilizing collected data with geo-tags geographic information adjacent base stations (BSs). Firstly, we propose a Dirichlet allocation (LDA) model forecasting because superiority LDA in natural language processing (NLP). Then,...

Caching during off-peak times can bring popular contents closer to users, and hence improves quality of experience (QoE) users in wireless networks. We formulate an optimization problem cooperative content caching, with the aim maximizing sum mean opinion score (MOS) all network. To solve challenging caching problem, we cluster by global K-means (GKM), based on popularity. For improving effectiveness propose a low complexity ε-greedy Q-learning algorithm which obtains near-optimal solution....

A novel framework is proposed to integrate communication, control, and computing (3C) into fifth generation beyond (5GB) wireless networks for satisfying the ultra-reliable low-latency connectivity requirements of remote e-health systems. Non-orthogonal multiple access (NOMA)-enabled 5GB network architecture envisioned, while benefits bringing it systems are demonstrated. First, application NOMA presented. To elaborate further, a unified proposed. As further advance, NOMA-enabled autonomous...

This paper is about regularizing deep convolutional networks (CNNs) based on an adaptive framework for transfer learning with limited training data in the target domain. Recent advances of CNN regularization this context are commonly due to use additional objectives. They guide away from task using some forms concrete tasks. Unlike those related approaches, we suggest that objective without a goal can still serve well as regularizer. In particular, demonstrate Pseudo-task Regularization...

A novel non-orthogonal multiple access (NOMA) enabled cache-aided mobile edge computing (MEC) framework is proposed, for minimizing the sum energy consumption. The NOMA strategy enables users to offload computation tasks point (AP) simultaneously, which improves spectrum efficiency. In this article, considered resource allocation problem formulated as a long-term reward maximization that involves joint optimization of task offloading decision, allocation, and caching decision. To tackle...

This paper presents an automatic network adaptation method that finds a ConvNet structure well-suited to given target task, e.g., image classification, for efficiency as well accuracy in transfer learning. We call the concept target-aware Given only small-scale labeled data, and starting from ImageNet pre-trained network, we exploit scheme of removing its potential redundancy task through iterative operations filter-wise pruning optimization. The basic motivation is compact networks are on...

This article investigates a wireless caching framework based on tweets and their location data collected from Twitter. The tweet texts are associated with the information of corresponding base stations (BSs) for improving efficiency at BSs. Extracted latent topics predicted content probability applied to reduce redundancy A machine learning approach, namely Dirichlet allocation (LDA), is invoked extract location-aware better performances. In an effort predict caching, novel skip-gram long...

Based on the immune theory of biology, a novel evolutionary algorithm, an agent-based evolution learning algorithm (AIEL) is proposed. In AIEL, mechanics and multi-agent technology are combined to overcome premature problem efficiently use agent ability sensing acting environment. AIEL integrates global local search during searching process. By application optimization test functions, it shown that outperforms other algorithms in these benchmark functions. Furthermore, applied determine...

An integrated system for neural network and symbolic inference is presented. In the two intelligent functions, inference, can work together to make greater contributions. By applying it computer simulation detection of foundation piles, proved be effective.

A novel non-orthogonal multiple access (NOMA) based cache-aided mobile edge computing (MEC) framework is proposed. For the purpose of efficiently allocating communication and computation resources to users' tasks requests, we propose a long-short-term memory (LSTM) network predict task popularity. Based on predicted popularity, long-term reward maximization problem formulated that involves joint optimization offloading decisions, resource allocation, caching decisions. To tackle this...

Abstract In this paper, high-density resistivity of the north bank Huangming Reservoir in Yuyao City was detected by Wenner device. Through detection multiple sections longitudinal and transverse sections, distribution rules rock mass slope are summarized, weathering grade is judged. The research results will provide a strong basis for disaster prevention mitigation work later period.

A novel reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic optimization problem that involves joint of NOMA user partitioning and RIS phase shifting, aiming at maximizing the sum data rate mobile users (MUs) in networks. To solve challenging problem, we invoke modified object migration automation (MOMA) algorithm to partition into equal-size clusters. optimize phase-shifting...

Driven by the unprecedented high throughput and low latency requirements in next-generation wireless networks, this paper introduces an artificial intelligence (AI) enabled framework which unmanned aerial vehicles (UAVs) use non-orthogonal multiple access (NOMA) mobile edge computing (MEC) techniques to service terrestrial users (MUs). The proposed enables MUs offload their computational tasks simultaneously, intelligently, flexibly, thus enhancing connectivity as well reducing transmission...

Biases continue to be prevalent in modern text and media, especially subjective bias – a special type of that introduces improper attitudes or presents statement with the presupposition truth. To tackle problem detecting further mitigating bias, we introduce manually annotated parallel corpus WIKIBIAS more than 4,000 sentence pairs from Wikipedia edits. This contains annotations towards both sentence-level types token-level biased segments. We present systematic analyses our dataset results...