Spatial interrelations of Chinese housing markets

This paper comprehensively tests the spatial interrelationships of 10 housing markets in the Pan-Pearl River Delta (Pan-PRD) in China, including the properties of spatial causality, convergence and diffusion p

The influence of additive content on microstructure and mechanical properties on the Csf/SiC composites after annealed treatment

AbstractIn this paper, micrometers long and 20–100nm diameter SiC nanowires had been synthesized in the short cut fiber toughened SiC composites (Csf/SiC) by annealing treatment. The present work demonstrated that it was possible to fabricate the in situ SiC nanowires toughened Csf/SiC composites by annealed treatment. The “vapor–liquid–solid” growth mechanism of the SiC nanowires was proposed. The mainly toughened mechanism concluded grain bridging, crack deflection, fiber debonding and SiC nanowires, which can improve fracture toughness

Correlated flat bands in the paramagnetic phase of triangular antiferromagnets Na2_2BaX(PO4_4)2_2 (X = Mn, Co, Ni)

Flat band systems in condensed matter physics are intriguing because they can exhibit exotic phases and unconventional properties. In this work, we studied three correlated magnetic systems, Na$_2$BaX(PO$_4$)$_2$ (X = Mn, Co, Ni), and revealed their unusual electronic structure and magnetic properties. Despite their different effective angular momentum, our first-principles calculations showed a similar electronic structure among them. However, their different valence configurations led to different responses to electronic correlations in the high-temperature paramagnetic phase. Using the dynamical mean-field method, we found that all systems can be understood as a multi-band Hubbard model with Hund'ss coupling. Our calculations of spin susceptibility and the {\it ab-initio} estimation of magnetic exchange coupling indicated strong intra-plane antiferromagnetic coupling and weak inter-plane coupling in all systems. The ground states of these systems are largely degenerate. It is likely that none of these magnetic states would dominate over the others, leading to the possibility of quantum spin liquid states in these systems. Our work unifies the understanding of these three structurally similar systems and opens new avenues for exploring correlated flat bands with distinct electronic and magnetic responses.Comment: 11 pages and 4 figure

Alleviating Distortion Accumulation in Multi-Hop Semantic Communication

Recently, semantic communication has been investigated to boost the performance of end-to-end image transmission systems. However, existing semantic approaches are generally based on deep learning and belong to lossy transmission. Consequently, as the receiver continues to transmit received images to another device, the distortion of images accumulates with each transmission. Unfortunately, most recent advances overlook this issue and only consider single-hop scenarios, where images are transmitted only once from a transmitter to a receiver. In this letter, we propose a novel framework of a multi-hop semantic communication system. To address the problem of distortion accumulation, we introduce a novel recursive training method for the encoder and decoder of semantic communication systems. Specifically, the received images are recursively input into the encoder and decoder to retrain the semantic communication system. This empowers the system to handle distorted received images and achieve higher performance. Our extensive simulation results demonstrate that the proposed methods significantly alleviate distortion accumulation in multi-hop semantic communication

SCAN: Semantic Communication with Adaptive Channel Feedback

In existing semantic communication systems for image transmission, some images are generally reconstructed with considerably low quality. As a result, the reliable transmission of each image cannot be guaranteed, bringing significant uncertainty to semantic communication systems. To address this issue, we propose a novel performance metric to characterize the reliability of semantic communication systems termed semantic distortion outage probability (SDOP), which is defined as the probability of the instantaneous distortion larger than a given target threshold. Then, since the images with lower reconstruction quality are generally less robust and need to be allocated with more communication resources, we propose a novel framework of Semantic Communication with Adaptive chaNnel feedback (SCAN). It can reduce SDOP by adaptively adjusting the overhead of channel feedback for images with different reconstruction qualities, thereby enhancing transmission reliability. To realize SCAN, we first develop a deep learning-enabled semantic communication system for multiple-input multiple-output (MIMO) channels (DeepSC-MIMO) by leveraging the channel state information (CSI) and noise variance in the model design. We then develop a performance evaluator to predict the reconstruction quality of each image at the transmitter by distilling knowledge from DeepSC-MIMO. In this way, images with lower predicted reconstruction quality will be allocated with a longer CSI codeword to guarantee the reconstruction quality. We perform extensive experiments to demonstrate that the proposed scheme can significantly improve the reliability of image transmission while greatly reducing the feedback overhead

One-shot Learning for Channel Estimation in Massive MIMO Systems

In conventional supervised deep learning based channel estimation algorithms, a large number of training samples are required for offline training. However, in practical communication systems, it is difficult to obtain channel samples for every signal-to-noise ratio (SNR). Furthermore, the generalization ability of these deep neural networks (DNN) is typically poor. In this work, we propose a one-shot self-supervised learning framework for channel estimation in multi-input multi-output (MIMO) systems. The required number of samples for offline training is small and our approach can be directly deployed to adapt to variable channels. Our framework consists of a traditional channel estimation module and a denoising module. The denoising module is designed based on the one-shot learning method Self2Self and employs Bernoulli sampling to generate training labels. Besides,we further utilize a blind spot strategy and dropout technique to avoid overfitting. Simulation results show that the performance of the proposed one-shot self-supervised learning method is very close to the supervised learning approach while obtaining improved generalization ability for different channel environments

Game-based Platforms for Artificial Intelligence Research

Games have been the perfect test-beds for artificial intelligence research for the characteristics that widely exist in real-world scenarios. Learning and optimisation, decision making in dynamic and uncertain environments, game theory, planning and scheduling, design and education are common research areas shared between games and real-world problems. Numerous open-sourced games or game-based environments have been implemented for studying artificial intelligence. In addition to single- or multi-player, collaborative or adversarial games, there has also been growing interest in implementing platforms for creative design in recent years. Those platforms provide ideal benchmarks for exploring and comparing artificial intelligence ideas and techniques. This paper reviews the game-based platforms for artificial intelligence research, discusses the research trend induced by the evolution of those platforms, and gives an outlook

Использование интернет-технологий для активизации процесса развития въездного туризма в РФ (на примере Томской области)

РЕФЕРАТ Объем работы – 102., рисунков – 7 , таблиц – 2, источников –61 . ИСПОЛЬЗОВАНИЕ ИНТЕРНЕТ ТЕХНОЛОГИЙ ДЛЯ АКТИВИЗАЦИИ ПРОЦЕССА РАЗВИТИЯ ВЪЕЗДНОГО ТУРИЗМА В РФ (НА ПРИМЕРЕ ТОМСКОЙ ОБЛАСТИ) Ключевые слова: интернет – технологии, туризм, въездной туризм, порталы. Актуальность Предмет исследования – исследования является интернет-технологии для повышения привлекательности региона для туристов. Объект исследования – интернет технологии. Проблему исследования Цель данной работы – исследования заключается в разработке предложений по совершенствованию туристского портала томской области. Для достижения поставленной цели определены следующие задачи: • Дать понятие и рассмотреть интернет технологии; • Рассмотреть состояние въездного туризма в зарубежных странах; • ПESSAY Volume of work - 102, figures - 7, tables - 2, sources -61. USING INTERNET TECHNOLOGY TO ENHANCE THE PROCESS OF DEVELOPMENT OF TOURISM IN THE RUSSIAN FEDERATION (THE EXAMPLE OF THE TOMSK REGION) Keywords: Internet - technology, tourism, inbound tourism portals. Relevance Subject of research - the study is an Internet-based technologies to enhance the attractiveness of the region for tourists. The object of study - Internet technology. research problem The purpose of this work - the research is to develop proposals for improving the tourist portal of the Tomsk region. To achieve this goal the following tasks: • Writing the concept and consider the Internet technology; • Consider the state of tourism in foreign countries; • Analyze the impact of Internet technology on the inbound t