Discipline Construction and Practical Reflection during the Founding of the CPC

At the beginning of the founding of the Communist Party of China (CPC), the Party explored discipline construction in early times for dealing with the unprofessional and corrupt CPC members and the unregulated organizational discipline. Although this action was immature, it still reflects the practical wisdom based on ideological construction, guaranteed by the measure of targeted treatment

Enlightenment and Reflection on the Integration of the Red Boat Spirit into the Teaching of The Outline of Modern Chinese History

The Red Boat spirit is the source of the Chinese revolutionary spirit and the source of the advancement of the CCP (Note 1). Its connotation reflects the CCP’s spirit of party building, the cultural label that indicates the initial heart and mission of CCP, and represents the core value requirement of our party. The spirit of the Red Boat has a deep connection with the teaching content of The Outline of Chinese Modern History. Teachers should enrich the teaching forms and encourage students to be thoughtful. In this way, college students can truly feel the role of the Red Boat spirit in promoting the development of modern Chinese history and understand the relationship between the Red Boat spirit and their own growth, which is of positive significance for the cultivation of contemporary college students’ historical views, the shaping of political views and the promotion of Red Boat spirit in the new era

Commonality between Red Boat Spirit and Zhejiang Spirit

The Red Boat spirit is the concentrated embodiment of the party building spirit of the CCP (Note 1), and the Zhejiang spirit is the common value understanding and spiritual pursuit of the Zhejiang people. The forming processes of the Red Boat spirit and Zhejiang spirit have shown the profound historical and cultural origins, have relatively obvious connotative commonalities, and are also given a new meaning and value in the present era. This paper will combine the historical backgrounds of the Red Boat spirit and Zhejiang spirit, analyze their theoretical connotations and explain their value of times, so as to illustrate the commonalities of the two spirits and hope that it will help to carry out a more in-depth and systematic study of the spirit of the Red Boat and the spirit of Zhejiang

The Education of Historical View of People in the Teaching of the Outline of Chinese Modern History

Marxist historical materialism scientifically reveals the law of the development of history, while historical view of people is the key content of historical materialism. To solve the problems existing in college students’ conceptions of history and all kinds of erroneous ideas derived therefrom, it is necessary to implement and emphasize the historical view of people throughout the teaching of the Outline of Chinese Modern History. Based on the discussion of the formation and development of the historical view of people, this paper emphatically analyzes the value of the historical view of people in the teaching of the Outline of Chinese Modern History, and finally discusses the specific strategies for the historical view of people education in this course

A Time-Efficient Strategy For Relay Selection and Link Scheduling In Wireless Communication Networks

Despite the unprecedented success and proliferation of wireless communication, sustainable reliability and stability among wireless users are still considered important issues in the underlying link protocols. Existing link-layer protocols, like ARQ [44] or HARQ [57,67] approaches are designed to achieve this goal by discarding a corrupted packet at the receiver and performing one or more retransmissions until the packet is successfully decoded or a maximum number of retransmission attempts is reached. These strategies suffer from degradation of throughput and overall system instability since packets need to be en/decode in every hop, leading to high burden for relay nodes especially when the traffic load is high. On the other hand, due to the broadcast nature of wireless communication, when a relay transmits a packet to a specific receiver, it could become interference to other receivers. Thus, rather than activating all the relays simultaneously, we can only schedule a subset of relays in each time slot such that the interference among the links will not cause some transmissions to fail. Accordingly, in this dissertation, we mainly address the following two problems: 1) Relay selection: given a route (i.e., a sequence of relays), how to select the relays to en/decode packets to minimize the latency to reach the destination? 2) Link scheduling: how to schedule relays such that the interference among the relays will not cause transmission failure and the throughput is maximized? Relay Selection Problem. To solve the relay selection problem, we propose a Code Embedded Distributed Adaptive and Reliable (CEDAR) link-layer framework that targets low latency. CEDAR is the first theoretical framework for selecting en/decoding relays to minimize packet latency in wireless communication networks. It employs a theoretically-sound framework for embedding channel codes in each packet and performs the error correcting process in selected intermediate nodes in packet\u27s route. To identify the intermediate relay nodes for en/decoding to minimize average packet latency, we mathematically analyze the average packet delay, using Finite State Markovian Channel model and priority queuing model, and then formalize the problem as a non-linear integer programming problem. To solve this problem, we design a scalable and distributed scheme which has very low complexity. The experimental results demonstrate that CEDAR is superior to the schemes using hop-by-hop decoding and destination-decoding in terms of both packet delay and throughput. In addition, the simulation results show that CEDAR can achieve the optimal performance in most cases. Link Scheduling Problem. As for the link scheduling problem, we formulate a new problem called Fading-Resistant Link Scheduling (Fadin-R-LS) problem, which aims to maximize the throughput (the sum data rate) for all the links in a single time slot. The problem is different from the existing link scheduling problems by incorporating the Rayleigh-fading model to describe the interference. This model extends the deterministic interference model based on the Signal-to-Interference Ratio (SIR) using stochastic propagation to address fading effects in wireless networks. Based on the geometric structure of Fadin-R-LS, we then propose three centralized schemes for Fadin-R-LS, with O(g(L)), O(g(L)), and O(1) performance guarantee for packet latency, where g(L) is the number of length magnitudes of link set L. Furthermore, we propose a completely distributed approach based on game theory, which has O(g(L)^2\alpha) performance guarantee. Furthermore, we incorporate a cooperative communication (CC) technique, e.g., maximum ratio combining (MRC), into our system to further improve the throughput, in which receivers are allowed to combine messages from different senders to combat transmission errors. In particular, we formulate two problems named cooperative link scheduling problem (CLS) and one-shot cooperative link scheduling problem (OCLS). The first problem aims to find a schedule of links that uses the minimum number of time slots to inform all the receivers. The second problem aims to find a set of links that can inform the maximum number of receivers in one time slot. We prove both problems to be NP-hard. As a solution, we propose an algorithm for both CLS and OCLS with g(K) approximation ratio, where g(K) is so called the diversity of key links. In addition, we propose a greedy algorithm with O(1) approximation ratio for OCLS when the number of links for each receiver is upper bounded by a constant. In addition, we consider a special case for the link scheduling problem, where there is a group of vehicles forming a platoon and each vehicle in the platoon needs to communicate with the leader vehicle to get the leader vehicle\u27s velocity and location. By leveraging a typical feature of a platoon, we devise a link scheduling algorithm, called the Fast and Lightweight Autonomous link scheduling algorithm (FLA), in which each vehicle determines its own time slot simply based on its distance to the leader vehicle. Finally, we conduct a simulation on Matlab to evaluate the performance of our proposed methods. The experimental results demonstrate the superior performance of our link scheduling methods over the previous methods

A Re-ranking Model for Dependency Parser with Recursive Convolutional Neural Network

In this work, we address the problem to model all the nodes (words or phrases) in a dependency tree with the dense representations. We propose a recursive convolutional neural network (RCNN) architecture to capture syntactic and compositional-semantic representations of phrases and words in a dependency tree. Different with the original recursive neural network, we introduce the convolution and pooling layers, which can model a variety of compositions by the feature maps and choose the most informative compositions by the pooling layers. Based on RCNN, we use a discriminative model to re-rank a $k$-best list of candidate dependency parsing trees. The experiments show that RCNN is very effective to improve the state-of-the-art dependency parsing on both English and Chinese datasets

Identifying Model Weakness with Adversarial Examiner

Machine learning models are usually evaluated according to the average case performance on the test set. However, this is not always ideal, because in some sensitive domains (e.g. autonomous driving), it is the worst case performance that matters more. In this paper, we are interested in systematic exploration of the input data space to identify the weakness of the model to be evaluated. We propose to use an adversarial examiner in the testing stage. Different from the existing strategy to always give the same (distribution of) test data, the adversarial examiner will dynamically select the next test data to hand out based on the testing history so far, with the goal being to undermine the model's performance. This sequence of test data not only helps us understand the current model, but also serves as constructive feedback to help improve the model in the next iteration. We conduct experiments on ShapeNet object classification. We show that our adversarial examiner can successfully put more emphasis on the weakness of the model, preventing performance estimates from being overly optimistic.Comment: To appear in AAAI-2

Wideband Anti-Jamming Based on Free Space Optical Communication and Photonic Signal Processing

We propose and demonstrate an anti-jamming system to defend against wideband jamming attack. Free space optical communication is deployed to provide a reference for jamming cancellation. The mixed signal is processed and separated with photonic signal processing method to achieve large bandwidth. As an analog signal processing method, the cancellation system introduces zero latency. The radio frequency signals are modulated on optical carriers to achieve wideband and unanimous frequency response. With wideband and zero latency, the system meets the key requirements of high speed and real-time communications in transportation systems

MB-TaylorFormer: Multi-branch Efficient Transformer Expanded by Taylor Formula for Image Dehazing

In recent years, Transformer networks are beginning to replace pure convolutional neural networks (CNNs) in the field of computer vision due to their global receptive field and adaptability to input. However, the quadratic computational complexity of softmax-attention limits the wide application in image dehazing task, especially for high-resolution images. To address this issue, we propose a new Transformer variant, which applies the Taylor expansion to approximate the softmax-attention and achieves linear computational complexity. A multi-scale attention refinement module is proposed as a complement to correct the error of the Taylor expansion. Furthermore, we introduce a multi-branch architecture with multi-scale patch embedding to the proposed Transformer, which embeds features by overlapping deformable convolution of different scales. The design of multi-scale patch embedding is based on three key ideas: 1) various sizes of the receptive field; 2) multi-level semantic information; 3) flexible shapes of the receptive field. Our model, named Multi-branch Transformer expanded by Taylor formula (MB-TaylorFormer), can embed coarse to fine features more flexibly at the patch embedding stage and capture long-distance pixel interactions with limited computational cost. Experimental results on several dehazing benchmarks show that MB-TaylorFormer achieves state-of-the-art (SOTA) performance with a light computational burden. The source code and pre-trained models are available at https://github.com/FVL2020/ICCV-2023-MB-TaylorFormer.Comment: ICCV 202