Federated learning (FL) is a collaborative machine paradigm, which enables deep model training over large volume of decentralized data residing in mobile devices without accessing clients' private data. Driven by the ever increasing demand for applications or devices, vast majority FL tasks are implemented wireless fading channels. Due to time-varying nature channels, however, random delay occurs both uplink and downlink transmissions FL. How analyze overall time consumption task, more...

The purpose of this paper is to propose an algorithm for solving the split common fixed point problems total asymptotically strictly pseudocontractive mappings in infinite‐dimensional Hilbert spaces. results presented improve and extend some recent Moudafi (2011 2010), Xu (2010 2006), Censor Segal (2009), et al. (2005), Masad Reich (2007), Yang (2004), others.

In this paper, we introduce an iterative method for solving the multiple‐set split feasibility problems asymptotically strict pseudocontractions in infinite‐dimensional Hilbert spaces, and, by using proposed method, improve and extend some recent results given authors.

Cryptographic algorithm identification, which refers to analyzing and identifying the encryption used in cryptographic system, is of great significance cryptanalysis. In order improve accuracy identification work, this article proposes a new ensemble learning-based model named hybrid k-nearest neighbor random forest (HKNNRF), constructs block cipher scheme. ciphertext-only scenario, we use NIST randomness test methods extract ciphertext features, carry out binary-classification...

Nowadays, heart disease is one of the important causes human deaths. According to statistics, deaths caused by account for about one-third all in world. With further research, use machine learning predict has become an essential method prevent and treat disease. In recent years, based on big data analysis been widely used various software applications, but it not a large scale prediction. this article, we propose new algorithm named hybrid gradient boosting decision tree with logistic...

The purpose of this paper is to introduce a new splitting iterative algorithm for finding common solution system quasi-variational inclusion problems, equilibrium problems and fixed point quasi-nonexpansive mappings in Hadamard manifolds. It shown that under mild conditions, the sequence generated by proposed converges solution. As applications, we apply our results study minimization saddle

Predicting the popularity of online contents especially videos has drawn a lot attention recently, since successful prediction can benefit many practical applications such as recommender systems and proactive caching, help optimize advertisement strategies or balance throughput in network. In this paper, we formulate problem present an Attention-based Long Short Term Memory (LSTM) with Feature Embedding method (ALFE) to tackle problem. Several features including publish time, follower count,...

Federated learning (FL) is a collaborative machine paradigm, which enables deep model training over large volume of decentralized data residing in mobile devices without accessing clients' private data. Driven by the ever increasing demand for applications or devices, vast majority FL tasks are implemented wireless fading channels. Due to time-varying nature channels, however, random delay occurs both uplink and downlink transmissions FL. How analyze overall time consumption task, more...

Few-shot hyperspectral image classification aims to identify the classes of each pixel in images by only marking few these pixels. And order obtain spatial-spectral joint features pixel, fixed-size patches centering around are often used for classification. However, observing results existing methods, we found that boundary corresponding pixels which located at objects images, hard classify. These patchs mixed with multi-class spectral information. Inspired this, propose augment prototype...

As biomedical data grows rapidly nowadays, we are going to study how efficiently apply cloud computing into problem. In this paper, the process of solving problem based on is presented. First, issue would be focus gene match and generation large amount emulated from real data. Second, a mathematical model proposed describe Third, implemented our MapReduce model, which means simulating application rested computing. Finally, some experiments conducted test performance issue. Besides, at end...

Wireless federated learning (FL) holds the potential of preserving data privacy and reducing network traffic congestion, thereby attracting much recent attention. Due to fading nature wireless channels, FL suffers from random delay in each uplink downlink transmission. As a result, how analyze overall task over channels remains open. To solve this challenging problem, we present saddle point approximation based approach obtain distribution caused by communication systems. In particular,...

To quantify the visual effect of local dimming products by optical parameters, a complete halo testing methodology was proposed. Besides, fitting curve between Halo and CR (contrast ratio) also presented. Based on which different backlights with various zones LED types can be simulated.

Cross-domain few-shot hyperspectral image classification focuses on learning prior knowledge from a large number of labeled samples source domains and then transferring the to tasks which contain few in target domains. Following metric-based manner, many current methods first extract features query support samples, directly predict classes according their distance or prototypes. The relations between have not been fully explored utilized. Different works, this paper proposes learn sample...

Logs normalization is an indispensable and basic work for coal-bed methane（Abbreviated as CBM）logging interpretation, also the key step to realize interpretation from single well multi-well. B block’s DEN GR logs come different time periods logging companies. In order finish following CBM lithofacies type plus histogram method selected according applicable conditions of methods block actual situation. Type can reduce influence man-made factors application, distribution after are more...